PROV-DM, the PROV conceptual data model, is a data model for provenance that describes
the entities, people and activities involved in
producing a piece of data or thing.
PROV-DM distinguishes core structures, forming the essence of provenance descriptions, from
extended structures catering for more advanced uses of provenance.
PROV-DM is structuredorganized in six components, respectively dealing with:
(1) entities and activities, and the time at which they were created, used, or ended;
(2) agents bearing responsibility for entities that were generated and activities that happened;
(3) derivations of entities from entities;
(4) properties to link entities that refer to the same thing;
(5) a notion of bundle, a mechanism to support provenance of provenance; and,
(6) collections forming a logical structure for its members;
(6) a simple annotation mechanism.members.
This document introduces the provenance concepts found in
PROV and defines PROV-DM types and
relations. PROV data model is domain-agnostic, but is equipped with
extensibility points allowing domain-specific information to be included.
Two further documents complete the specification of PROV-DM.
First, a companion document specifies the set of constraints that
provenance descriptions should follow. Second,
a separate document describes a provenance notation for expressing
instances of provenance for human consumption; this notation is used in examples in
this document.
Status of This Document
This section describes the status of this document at the time of its publication. Other documents may supersede this document. A list of current W3C publications and the latest revision of this technical report can be found in the W3C technical reports index at http://www.w3.org/TR/.
Intended to be Last Call (TBC)
This is the fifth public release of the PROV-DM document.
Publication as Last Call working draft means that
the Working Group believes that it has satisfied the relevant technical requirements outlined in its charter on this document. The design is not expected to change significantly, going forward, and now is the key time for external review, before the implementation phase.
Please Comment By (date TBD)
The PROV Working group seeks public feedback on this Working Draft.
The end date of the Last Call review period is TBD, and we would appreciate comments by that date to public-prov-comments@w3.org
PROV Family of Specifications
This document is part of the PROV family of specifications, a set of specifications defining various aspects that are necessary to achieve the vision of inter-operable
interchange of provenance information in heterogeneous environments such as the Web. The specifications are:
PROV-DM, the PROV data model for provenance (this document);
PROV-CONSTRAINTS, a set of constraints applying to the PROV data model;
PROV-N, a notation for provenance aimed at human consumption;
PROV-O, the PROV ontology, an OWL-RL ontology allowing the mapping of PROV to RDF;
PROV-AQ, the mechanisms for accessing and querying provenance;
PROV-PRIMER, a primer for the PROV data model;
PROV-SEM, a formal semantics for the PROV data model;
PROV-XML, an XML schema for the PROV data model.
How to read the PROV Family of Specifications
The primer is the entry point to PROV offering an introduction to the provenance model.
The Linked Data and Semantic Web community should focus on PROV-O defining PROV classes and properties specified in an OWL-RL ontology. For further details, PROV-DM and PROV-CONSTRAINTS specify the constraints applicable to the data model, and its interpretation. PROV-SEM provides a mathematical semantics.
The XML community should focus on PROV-XML defining an XML schema for PROV. Further details can also be found in PROV-DM, PROV-CONSTRAINTS, and PROV-SEM.
Developers seeking to retrieve or publish provenance should focus on PROV-AQ.
Readers seeking to implement other PROV serializations
should focus on PROV-DM and PROV-CONSTRAINTS. PROV-O, PROV-N, PROV-XML offer examples of mapping to RDF, text, and XML, respectively.
Fourth Public Working Draft
This is the fourth public release of the PROV-DM document. Following feedback, the Working Group has decided to reorganize this document substantially, separating the data model from its contraints and the notation used to illustrate it. The PROV-DM release is synchronized with the release of the PROV-O, PROV-PRIMER, PROV-N, and PROV-CONSTRAINTS documents. We are now clarifying the entry path to the PROV family of specifications.This document was published by the Provenance Working Group as a Workingan Editor's Draft. This document is intendedIf you wish to become a W3C Recommendation. If you wishmake comments regarding this document, please send them to make comments regarding this document, please send them to public-prov-wg@w3.orgpublic-prov-comments@w3.org (subscribe, archives). All feedback is welcome.
Publication as a Workingan Editor's Draft does not imply endorsement by the W3C Membership. This is a draft document and may be updated, replaced or obsoleted by other documents at any time. It is inappropriate to cite this document as other than work in progress.
For the purpose of this specification, provenance is defined as a record that describes the people,
institutions, entities, and activities involved in producing,
influencing, or delivering a piece of data or a thing.
In particular, the provenance of information is crucial in deciding
whether information is to be trusted, how it should be integrated with
other diverse information sources, and how to give credit to its
originators when reusing it. In an open and inclusive environment
such as the Web, where users find information that is often contradictory or
questionable, provenance can help those users to make trust judgements.
We
consider a coregeneric data model for provenance that allows domain and application specific representations of provenance to be translated into such a data model and interchanged between systems.
Thus, heterogeneous systems can export their native provenance into such a core data model, and applications that need to make sense of provenance in heterogeneous systems can then import it,
process it, and reason over it.
A set of specifications, referred
The PROV data model distinguishes core structures from
extended structures: core structures form the essence of
provenance descriptions, and are commonly found in various
domain-specific vocabularies. Extended structures enhance and refine core
structures with more expressive capabilities to as the PROV family of specifications, define the various aspects
that are necessary to achieve this vision in an interoperable
way:A data modelcater for provenance, which is presented in three documents:
PROV-DM (part I): the provenance data model, informally described (this document);
PROV-CONSTRAINTS (part II): constraints underpinning the data model [PROV-CONSTRAINTS];
PROV-N (part III): a notation to express instances of that data model for human consumption [PROV-N];
PROV-O: the PROV ontology, an OWL-RL ontology allowing the mapping of PROV to RDF [PROV-O];PROV-AQ: the mechanisms for accessing and querying provenance [PROV-AQ];PROV-PRIMER: a primer for the PROV approach [PROV-PRIMER];PROV-SEM: semantics of the PROV-DM data model [PROV-SEM];PROV-XML: an XML schema for the PROV data model.more
advanced uses of provenance.
The PROV data model, comprising both core and extended structures, is a domain-agnostic model, but with clear extensibility points allowing further domain-specific and
application-specific extensions to be defined.
The PROV data model has a modular design and is a domain-agnostic model, but with clear extensibility points allowing further domain-specific and
application-specific extensionsstructured according to be defined.
The PROV data model is structured according to six components covering various aspectsfacets of provenance:
component 1: entities and activities, and the time at which they were created, used, or ended;
component 2: agents bearing responsibility for entities that were generated and activities that happened;
component 3: derivations of entities from others;
component 4: properties to link entities that refer to a same thing;
component 5: collections formingbundles, a logical structure for its members;mechanism to support provenance of provenance;
component 6: collections forming a simple annotation mechanism.logical structure for its members.
This specification presents the key concepts of the PROV Data Model, and
provenance types and relations, without specific concern for how they are applied.
With these, it becomes possible to write useful provenance descriptions, and publish or embed them along sidealongside the data they relate to.
However, if something about which provenance is expressed is subject to change, then it is challenging to express its provenance precisely (e.g. the data from which a daily weather report is derived changes from day to day).
To address this challenge, a refinementit is proposed to enrich simple provenance, with extrarefined descriptions that help qualify the specific subject of provenance and provenance itself, with attributes and temporal information, intended to satisfy a comprehensive set of constraints. These aspects are covered in the companion specification [PROV-CONSTRAINTS].
1.1 Structure of this Document
Section 2 provides an overview of the PROV Data Model,starting points for the PROV Data Model, listingdistinguishing a core set of types and relations, which allows users to make initialcommonly found in provenance descriptions.descriptions, from extended structures catering for advanced uses. It also introduces a modular organization of the data model in components.
Section 3 overviews the Provenance Notation used to illustrate examples of provenance descriptions.
Section 34 illustrates how the PROV data model can be used
to express the provenance of a report published on the Web.
Section 45 provides the definitions of PROV concepts, structured according to six components.
Section 67 introduces the idea that constraints can be applied to the PROV data model to refinevalidate provenance descriptions; these are covered in the companion specification [PROV-CONSTRAINTS].
1.2 Notational Conventions
The key words "must", "must not", "required", "shall", "shall
not", "should", "should not", "recommended", "may", and
"optional" in this document are to be interpreted as described in
[RFC2119].
The following namespaces prefixes are used throughout this document.
Table 1: Prefix and Namespaces used in this specification
All other namespace prefixes are used in examples only. In particular, URIs starting with "http://example.com" represent some application-dependent URI [URI]
Examples throughout this document use the PROV-N Provenance
Notation, briefly introduced in Section 3 and specified fully in a separate document [PROV-N].
2.1 Entity and ActivityThings we want to describe the provenance of are called entities in PROV. The term "things" encompasses a broad diversity of notions, including digital objects such as a file or web page,
physical things such as a building or a printed book, or a car as well as abstract concepts and ideas.
An entity is a physical, digital, conceptual, or other kind of thing; entities may be real or imaginary. An entity may be the document at URI http://www.bbc.co.uk/news/science-environment-17526723, a file in a file system, a car, or an idea. An activity is something that occurs over a period of time and acts upon or with entities; it may include consuming, processing, transforming, modifying, relocating, using, generating, or being associated with entities. Activities that operate on digital entities may for example move, copy, or duplicate them.
An activity may be the publishing of a document on the Web, sending a twitter message, extracting metadata embedded in a file, driving a car from Boston to Cambridge, assembling a data set based on a set of measurements, performing a statistical analysis over a data set, sorting news items according to some criteria, running a SPARQL query over a triple store, or editing a file.2.2 Generation, Usage, DerivationActivities and entities are associated with each other in two different ways: activities utilize entities and activities produce entities. The act of utilizing or producing an entity may have a duration.
The term 'generation' refers to the completion of the act of producing; likewise, the term 'usage' refers to the beginning of the act of utilizing entities. Thus, we define the following notions of generation and usage. Generation is the completion of production of a new entity by an activity. This entity did not exist before generation and becomes available for usage after this generation. Usage is the beginning of utilizing an entity by an activity. Before usage, the activity had not begun to utilize this entity and could not have been affected by the entity. Examples of generation are the completed creation of a file by a
program, the completed creation of a linked data set, and the completed
publication of a new version of a document.
Usage examples include a procedure beginning to consume an argument, a service starting to read a value on a port, a program beginning to read a configuration
file, or the point at which an ingredient, such as eggs, is being added in a baking activity. Usage may entirely consume an entity (e.g. eggs are no longer available after being added to
the mix); in contrast, the same entity may be used multiple times, possibly by different activities (e.g. a file on a file system can be read indefinitely).
Activities utilize entities and producer entities. In some cases, utilizing an entity influences the creation of another in some way. This notion is captured by derivations, defined as follows. A derivation is a transformation of an entity into another, a construction of an entity into another, or an update of an entity, resulting in a new one.Examples of derivation include the transformation of a relational table into a
linked data set, the transformation of a canvas into a painting, the transportation of a work of art from London to New York, and a physical transformation such as the melting of ice into water.2.3 Agents, Attribution, Association, and ResponsibilityPROV Core Structures
The motivation for introducingcore of PROV consists of essential provenance structures commonly found in provenance descriptions.
It is summarized graphically by
the UML diagram of Figure 1,
illustratingagents in the model isthree types (entity, activity, and agent) and how they relate to express the agent's responsibility for activities that happened and entities that were generated.each other. In the core of PROV, all associations are binary.
An agent is something that bears some form of responsibility for an activity taking place or for the existence of an entity. An agent may be a particular type of entity. This means that the model can be
used to express provenance of the agents themselves.
Software for checking the use of grammar in a document may be defined as an agent of a document preparation activity, and at the same time one can describe its provenance, including for instance the vendor and the version history.
A site selling books on the Web, the services involved in the processing of orders, and the companies hosting them are also agents.
Figure 1: PROV Core Structures
Agents may adopt sets of actions or steps to achieve their goals. This is captured by the notion of plan.
A plan is an entity that represents a set of actions or steps intended by one or more agents to achieve some goals.
There exist no
prescriptive requirement on the nature of plans, their representation, the
actions or steps they consist of, or their intended goals. Since plans may evolve over time,
it may become necessary to track their provenance, so plans themselves are
entities. Representing the plan explicitly in the provenance can be useful for various tasks: for example, to
validate the execution as represented in the provenance record, to
manage expectation failures, or to provide explanations.
A plan can be a blog post tutorial for how to set up a web server, a list of instructions for a micro-processor execution, a cook's written recipe for a chocolate cake, or a workflow for a scientific experiment.
Agents can be related to entities, activities, and other agents.Attribution is the ascribing of an entity to an agent. A blog post can be attributed to an author, a mobile phone to its manufacturer.
AgentsThe concepts found in the core of PROV are defined as having some kind of responsibility for activities. In some
cases, those activities reflect the execution of a plan that was
designedintroduced in advance to guide the execution. Thus,
a plan may also be linked to an activity. An activity association is an assignment of responsibility to an agent for an activity, indicating that the agent had a rolethe rest of this section.
They are summarized in the activity. It further allows for a plan to be specified, which is the plan intended by the agent to achieve some goals in the context of this activity. Examples of association between an activity and an agent are:
creation of a web page under the guidance of a designer;various forms of participation in a panel discussion, including audience member, panelist, or panel chair;a public event, sponsored by a company, and hosted by a museum;an XSLT transform launched by a user based on an XSL style sheet (a plan).Responsibility is the fact that an agent is accountable for the actions of a "subordinate" agent, in the context of an activity. The nature of this relation is intended to be broad, including delegation or contractual relation. A student publishing a web page describing an academic
department could result in both the student and the department being
agents associated with the activity, and it may not matter which
student published a web page but it matters a lot that the department
told the student to put up the web page.
2.4 Further Entities: Collections and AccountsThere are two further types of entities, collections and accounts, which are now introduced. A collection is an entity that provides a structure to some constituents, which are themselves entities. These constituents are said to be member of the collections. This concept allows for the provenance of the collection itself to be expressed in addition to that of the members. Many different types of collections exist, such as a set, dictionaries, or lists, all of which involve a membership relationship between the constituents and the collection.
An example of collection is an archive of documents. Each document has its own provenance, but the archive itself also has some provenance: who maintained it, which documents it contained at which point in time, how it was assembled, etc.
An account is an entity that contains a bundle of provenance descriptions. Making an account an entity allows for provenance of provenance to be expressed.
For users to decide whether they can place their trust in
a resource, they may want to analyze the resource's provenance, but also determine
who its provenance is attributed to, and when it was
generated. In other words, users need to be able to determine the provenance of provenance.
Hence, provenance is also
regarded as an entity (of type Account), by which provenance of provenance can then be
expressed.
2.5 Simplified Overview DiagramSo far, we have introduced a series of concepts underpinning provenance. PROV-DM is a conceptual data model consisting of types and relations between these.Table 2 shows how provenance concepts can be mapped to types and relations in PROV-DM: the, where they are categorized as
type or relation.
The first column lists concepts introduced in this section,concepts, the second column indicates whether a concept maps to a type or a relation, whereas the third column contains the corresponding name. Names of relations have a verbal form in the past tense to express what happened in the past, as opposed to what may or will happen.
Table 2: Mapping of ProvenancePROV core concepts to types and relations
In PROV, things we want to describe the provenance of are called entities and have some fixed aspect. The term "things" encompasses a broad diversity of notions, including digital objects such as a file or web page,
physical things such as a mountain, a building, a printed book, or a car as well as abstract concepts and ideas.
An entity is a physical, digital, conceptual, or other kind of thing with some fixed aspects; entities may be real or imaginary.
An activity is something that occurs over a period of time and acts upon or with entities; it may include consuming, processing, transforming, modifying, relocating, using, generating, or being associated with entities. Activities that operate on digital entities may for example move, copy, or duplicate them.
An activity may be the publishing of a document on the Web, sending a twitter message, extracting metadata embedded in a file, driving a car from Boston to Cambridge, assembling a data set based on a set of measurements, performing a statistical analysis over a data set, sorting news items according to some criteria, running a SPARQL query over a triple store, or editing a file.
Figure 1 illustrates the three types (entity, activity,Activities and agent)entities are associated with each other in two different ways: activities utilize entities and how they relateactivities produce entities. The act of utilizing or producing an entity may have a duration.
The term 'generation' refers to eachthe completion of the act of producing; likewise, the term 'usage' refers to the beginning of the act of utilizing entities. Thus, we define the following concepts of generation and usage.
Generation is the completion of production of a new entity by an activity. This entity did not exist before generation and becomes available for usage after this generation.
Usage is the beginning of utilizing an entity by an activity. Before usage, the activity had not begun to utilize this entity and could not have been affected by the entity.
Examples of generation are the completed creation of a file by a
program, the completed creation of a linked data set, and the completed
publication of a new version of a document.
Usage examples include a procedure beginning to consume an argument, a service starting to read a value on a port, a program beginning to read a configuration
file, or the point at which an ingredient, such as eggs, is being added in a baking activity. Usage may entirely consume an entity (e.g. eggs are no longer available after being added to
the mix); in contrast, the same entity may be used multiple times, possibly by different activities (e.g. a file on a file system can be read indefinitely).
The generation of an entity by an activity and its subsequent usage by another activity is termed communication.
Communication is the exchange of an entity by two activities, one activity using the entity generated by the other.
The activity of writing a celebrity article was informed by (a
communication instance) the activity of intercepting voicemails.
2.1.2 Agents and Responsibility
The motivation for introducingAt this stage, all relationsagents in the model is to express the agent's responsibility for activities that happened and entities that were generated.
An agent is something that bears some form of responsibility for an activity taking place or for the existence of an entity. An agent may be a particular type of entity or activity. This means that the model can be
used to express provenance of the agents themselves.
Software for checking the use of grammar in a document may be defined as an agent of a document preparation activity; one can also describe its provenance, including for instance the vendor and the version history.
A site selling books on the Web, the services involved in the processing of orders, and the companies hosting them are shownalso agents.
Agents can be related to entities, activities, and other agents.
Attribution is the ascribing of an entity to an agent.
A blog post can be binary. Definitions of Section 4 reveal that some relations, while involving two primary elements, are n-ary. attributed to an author, a mobile phone to its manufacturer.
Figure 1: Simplified Overview of PROV-DM
Figure 1
Agents are defined as having some kind of responsibility for activities.
An activity association is an assignment of responsibility to an agent for an activity, indicating that the agent had a role in the activity.
Examples of association between an activity and an agent are:
creation of a web page under the guidance of a designer;
various forms of participation in a panel discussion, including audience member, panelist, or panel chair;
a public event, sponsored by a company, and hosted by a museum;
Delegation is the assignment of authority to an agent (by itself or by another agent) to carry out a specific activity as a delegate or representative, while the agent that it represents remains responsible for the outcome of the delegated work. The nature of this relation is intended to be broad, including contractual relation, but also altruistic initiative by the representative agent.
A student publishing a web page describing an academic
department could result in both the student and the department being
agents associated with the activity. It may not intendedmatter which actual
student published a web page, but it may matter significantly that the department
told the student to be complete: it only illustratesput up the web page.
2.1.3 Derivation
Activities utilize entities and produce entities. In some cases, utilizing an entity influences the creation of another in some way. This notion of 'influence' is captured by derivations, defined as follows.
A derivationtypesis a transformation of an entity into another, an update of an entity, resulting in a new one, or based on an entity, the construction of another.
Examples of derivation include the transformation of a relational table into a
linked data set, the transformation of a canvas into a painting, the transportation of a work of art from London to New York, and relations introduced in this section (Section 2), exploited in the example discussed in Section 3, and explained in detail in Section 4.
Names of relations depicted in Figure 1
are listed in
the third column of Table 2. These names are part of a textual notation to write instances of the PROV data model, which we introduce in the next section. physical transformation such as the melting of ice into water.
2.6 PROV-N: 2.2 PROV Extended Structures
While the core of PROV focuses on essential provenance structures commonly found in provenance descriptions, extended structures
are designed to support more advanced uses of provenance.
The Provenance Notationpurpose of this section is twofold. First, mechanisms to specify these extended structures are introduced. Second, two further kinds of provenance structures are overviewed: they cater for provenance of provenance and collections, respectively.
2.2.1 Mechanisms to Define Extended Structures
Extended structures are defined by a variety of mechanisms
outlined in this section: subtyping, expanded relations, optional
identification, and new relations.
2.2.1.1 Subtyping
Subtyping can be applied to core types. For example, a software agent is special kind of agent, defined as follows.
A software agent is running software.
Subtyping can also be applied to core relations. For example, a revision is a special kind of derivation, defined as follows.
A revision is a derivation that revises an entity into a revised version.
2.2.1.2 Expanded Relations
Section 2.1 shows that seven concepts are mapped to binary relations in the core of PROV. However, some advanced uses of these concepts cannot be captured by a binary relation, but require relations to be expanded to n-ary relations.
To illustrate the application of PROVexpanded relations, we consider the concept of
association, described
in section
2.1.2. Agents may adopt sets of actions or steps to achieve their
goals in the context of an activity: this is captured by the notion of
a plan. Thus, an activity may reflect the execution of a plan that was
designed in advance to guide the execution. Hence, an expanded
association relation allows a plan be linked to an
activity. Plan is defined by subtyping and full association by an expanded relation, as follows.
A plan is an entity that represents a set of actions or steps intended by one or more agents to achieve some goals.
There exist no
prescriptive requirement on the nature of plans, their representation, the
actions or steps they consist of, or their intended goals. Since plans may evolve over time,
it may become necessary to track their provenance, so plans themselves are
entities. Representing the plan explicitly in the provenance can be useful for various tasks: for example, to
validate the execution as represented in the provenance record, to
manage expectation failures, or to provide explanations.
An activity association is an assignment of responsibility to an agent for an activity, indicating that the agent had a role in the activity. It further allows for a plan to be specified, which is the plan intended by the agent to achieve some goals in the context of this activity.
An example of association between an activity and an agent involving a plan is:
an XSLT transform (an activity) launched by a user (an agent) based on an XSL style sheet (a plan).
2.2.1.3 Optional Identification and New Relations
Some concepts exhibit both a core use, expressed as
binary relation, and an extended use, expressed as n-ary relation. In
some cases, mapping the concept to a concrete example (see Section 3)relation, whether binary or
n-ary, is not sufficient: instead, it may be required to
identify an instance of such concept. In those cases, PROV-DM allows for
an optional identifier to be
expressed to identify an instance of an association between two or
more elements. This optional identifier can then be used to refer to
an instance as part of other concepts.
A service may read a same configuration file on two different occasions. Each usage can be identifed by its own identifier, allowing them to be distinguished.
Finally, PROV-DM supports further relations that are not subtypes or expanded versions of existing relations.
2.2.2 Provenance of Provenance
A bundle is a named set of provenance descriptions, and is itself an entity, so allowing provenance of provenance to provide examples of concepts (see Section 4),
we introduce PROV-N, be expressed.
For users to decide whether they can place their trust in
a notationresource, they may want to analyze the resource's provenance, but also determine
who its provenance is attributed to, and when it was
generated. In other words, users need to be able to determine the provenance of provenance.
Hence, provenance is also
regarded as an entity (of type Bundle), by which provenance of provenance can then be
expressed.
2.2.3 Collections
A collection is an entity that provides a structure to some constituents, which are themselves entities. These constituents are said to be member of the collections. This concept allows for writing instances of the PROV data model. For full details, the reader is referredthe provenance of the collection itself to the companion specification [PROV-N].
PROV-N isbe expressed in addition to that of the members. Many different types of collections exist, such as a notation aimed at human consumption, with the following characteristics:PROV-N expressions adopt a functional notation consisting
of a name and a list of arguments in parentheses.The interpretation of PROV-N arguments is defined according to their position in the list of arguments. This convention allows for a compact notation.
PROV-N optional arguments need not be specified:
the general rule for optional arguments is that, if none of them are used in the expression, then they are simply omitted, resulting in a simpler expression. However, it may be the case that only some of the optional arguments need to be specified. Because the position of the arguments in the expression matters, in this case an additional marker must be used to indicate that a particular term is not available. The syntactic marker - is used for this purpose.
Most expressions
include an identifier
and a set of attribute-value pairs; both are optional unless otherwise specified. By convention, the identifier occurs in the first positionsets, dictionaries, or lists, all of which involve a membership relationship between the constituents and the the set of attribute-value pairscollection.
An example of collection is an archive of documents. Each document has its own provenance, but the archive itself also has some provenance: who maintained it, which documents it contained at which point in the last position.
Consistent with the convention on arguments, the markertime, how it was assembled, etc.
2.3 Modular Organization
Besides the separation between core and extended structures, PROV-DM
is further organized according to components, grouping concepts in a
thematic manner.
Table 3 enumerates the six components, five of which have already been implicitly overviewed in this section. All components specify extended structures, whereas only the first three- can be used when the identifier is not available, or can be omitted altogether with no ambiguity arising.
define core structures.
An activity with identifier a1
Table 3: Components Overview
Component
Core Structures
Overview
Specification
Description
1
Entities and an attribute type with value createFile.
activity(a1, [prov:type="createFile"])
TwoActivities
about entities with identifiers e1 and e2.
entity(e1)
entity(e2)
The activity a1 used e1,activities, and e2 was generated by a1.
used(a1,e1)
wasGeneratedBy(e2,a1)
Thetheir interrelations
about collections and the syntactic marker - to mark the absence of identifier in the generation.
used(u1,a1,e1)
wasGeneratedBy(-,e2,a1)
concepts capturing their transformation, such as insertion and removal
3. The Provenance Notation
To illustrate the application of PROV concepts to a concrete example (see Section 4) and to provide examples of concepts (see Section 5),
we introduce PROV-N, a notation for writing instances of the PROV data model. For full details, the reader is referred to the companion specification [PROV-N].
PROV-N is a notation aimed at human consumption, with the following characteristics:
PROV-N expressions adopt a functional notation consisting
of a name and a list of arguments in parentheses.
The interpretation of PROV-N arguments is defined according to their position in the list of arguments. This convention allows for a compact notation.
PROV-N optional arguments need not be specified:
the general rule for optional arguments is that, if none of them are used in the expression, then they are simply omitted, resulting in a simpler expression. However, it may be the case that only some of the optional arguments need to be specified. Because the position of the arguments in the expression matters, in this case, an additional marker must be used to indicate that a particular term is not available. The syntactic marker '-' is used for this purpose.
Most expressions
include an identifier
and a set of attribute-value pairs; both are optional unless otherwise specified. By convention, the identifier occurs in the first position, and the set of attribute-value pairs in the last position.
Consistent with the convention on arguments, the marker '-' can be used when the identifier is not available, or can be omitted altogether with no ambiguity arising. To further disambiguate expressions that contains an optional identifier, the optional identifier or marker must be followed by ';'.
An activity with identifier a1 and an attribute type with value createFile.
activity(a1, [prov:type="createFile"])
Two entities with identifiers e1 and e2.
entity(e1)
entity(e2)
The activity a1 used e1, and e2 was generated by a1.
used(a1,e1)
wasGeneratedBy(e2,a1)
The same descriptions, but with an explicit identifier u1 for the usage, and the syntactic marker '-' to mark the absence of identifier in the generation. Both are followed by ';'.
used(u1;a1,e1)
wasGeneratedBy(-;e2,a1)
3.4.Illustration of PROV-DM by an Example
Section 2 has introduced some provenance concepts, and how they are expressed as types or relations in the PROV data model. The purpose of this section is to put these concepts into practice in order to express the provenance of some document published on the Web.
With this realistic example, PROV concepts are composed together, and a graphical illustration shows a provenance description forming a directed graph, rooted at the entity we want to explain the provenance of, and pointing to the entities, activities, and agents it depended on. This example also shows that, sometimes, multiple provenance descriptions about the same entity can co-exist, which then justifies the need for provenance of provenance.
In this example, we consider one of the many documents published by the World Wide Web Consortium, and describe its provenance.
Specifically, we consider the document identified by
http://www.w3.org/TR/2011/WD-prov-dm-20111215. Its provenance can be expressed from several perspectives: first, provenance can take the authors' viewpoint; second, it can be concerned with the W3C process. Then, attribution of these two provenance descriptions is provided.
3.14.1The Authors View
Description: A document
is edited by some editor, using contributions from various
contributors.
In this perspective, provenance of the document
http://www.w3.org/TR/2011/WD-prov-dm-20111215 is concerned with the editing activity as perceived by authors. This kind of information could be used by authors in their CV or in a narrative about this document.
We paraphrase some PROV-DM descriptions, express them with the PROV-N notation, and then depict them with a graphical illustration (see Figure 12).
Full details of the provenance record can be found here.
Figure 2: Provenance of a Document (1)
There was a document tr:WD-prov-dm-20111215, which from the author's perspective was a document in its second version.
Provenance descriptions can be illustrated graphically. The illustration is not intended to represent all the details of the model, but it is intended to show the essence of a set of
provenance descriptions. Therefore, it should not be seen as an alternate notation for expressing provenance.
The graphical illustration takes the form of a graph. Entities, activities and agents are represented as nodes, with oval, rectangular, and pentagonal shapes, respectively. Usage,
Generation, Derivation, and Association are represented as directed edges.
Entities are laid out according to the ordering of their generation. We endeavor to show time progressing from left to right. This means that edges for Usage, Generation,
Derivation, Association typically point leftwards
Figure 2: Provenance of a Document (1)
3.24.2The Process View
Description: The World Wide Web
Consortium publishes documents according to its publication
policy. Working drafts are published regularly to reflect the work
accomplished by working groups. Every publication of a working draft
must be preceded by a "publication request" to the Webmaster. The
very first version of a document must also be preceded by a
"transition request" to be approved by the W3C director. All working
drafts are made available at a unique URI. In this scenario, we consider two successive versions of a given document, the policy according to which they were published, and the associated requests.
We describe the kind of provenance record that the WWW Consortium could keep for auditors to check that due processes are followed. All entities involved in this example are Web resources, with well definedwell-defined URIs (some of which refer archived email messages, available to W3C Members).
Documents were published according to the process rules (process:rec-advance), a plan in PROV-DM terminology.
We now paraphrase some PROV descriptions, and express them with the PROV-N notation, and then depict them with a graphical illustration (see Figure 23). Full details of the provenance record can be found here.
Figure 3: Provenance of a Document (2)
There was a document, a working draft on the recommendation track (process:RecsWDrec54:WD), which is an entity so that we can describe its provenance. Similar descriptions exist for all entities.
This simple example has shown a variety of PROV concepts, such as Entity, Agent, Activity, Usage, Generation, Derivation, and Association. In this example, it happens that all entities were already Web resources, with readily available URIs, which we used. We note that some of the resources are public, whereas others have restricted access: provenance statements only make use of their identifiers. If identifiers do not pre-exist, e.g. for activities, then they can be generated, for instance ex:act2, occurring in the namespace identified by prefix ex. We note that the URI scheme developed by W3C is particularly suited for expressing provenance of these documents, since each URI denotes a specific version of a document. It then becomes easy to relate the various versions with PROV-DM relations. We note that an Association is a ternary relation (represented by a multi-edge labeled wasAssociatedWith) from an activity to an agent and a plan.
3.34.3Attribution of Provenance
The two previous sections offer two different perspectives on the provenance of a document. PROV allows for multiple sources to provide two different perspectives on the provenance of a document By design, the PROV approach allows for the provenance of a subjectsubject. For users to be provided by multiple sources. For usersdecide whether they can place their trust in the document, they may want to decide whether they can place their trust in the document, they may want to analyze its provenance, but also determine
who the provenance is attributed to, and when it was
generated, etc. In other words, we need to be able to express the provenance of provenance.
No new mechanismPROV-DM offers a construct to name a bundle of provenance descriptions (full details: ex:author-view).
To express their respective provenance, these bundles must be seen as entities, and all PROV constructs are now available to express their provenance. In the example below, ex:author-view is requiredattributed to support this requirement.the agentPROV-DM makes the assumption that provenance statements have been bundled up, and named, by some mechanism outside the scope of PROV-DM. For instance, in this case, provenance statements were put in a file and exposed on the Web, respectively at ex:w3c-publication1.pn and ex:w3c-publication3.pn. To express their respective provenance, these resources must be seen as entities, and all the constructs of PROV-DM are now availableex:Simon, whereas ex:process-view to characterize their provenance. In the example below, ex:w3c-publication1.pn is attributed to the agent w3:Consortium, whereas ex:w3c-publication3.pn to ex:Simon.
Provenance concepts, expressed as PROV-DM types and relations, are structuredorganized according to six components that are introduceddefined in this section.
ComponentsThe components and their dependencies are illustrated in Figure 4. A component that relies on concepts defined in another also sitsis displayed above it in thisthe figure.
PROV-DM consists of the following components. So, for example, component 6 (collections) depends on concepts defined in component 3 (derivation), itself dependen on concepts defined in component 1 (entity and activity).
Component 1: entities and activities. The first component consists of entities, activities, and concepts linking them, such as generation, usage, start, end. The first component is the only one comprising time-related concepts.
Component 2: agents and responsibility. The second component consists of agents and concepts ascribing responsibility to agents.
Component 3: derivations. The third component is formed with derivations and derivation subtypes.
Component 4: alternate. The fourth component consists of relations linking entities referring to the same thing.
Component 5: collections.bundles. The fifth component is about collections and concepts capturing their transformation, such as insertion and removal. concerned with bundles, a mechanism to support provenance of provenance.
Component 6: annotations.collections. The sixth component is concerned with annotations to PROV-DM instances.about collections and concepts capturing their transformation, such as insertion and removal.
Figure 4: PROV-DM Components
While not all PROV-DM relations are binary, they all involve two primary elements. Hence, Table 34 indexes all relations according to their two primary elements.elements (referred to as subject and object). The table adopts the same color scheme as Figure 4, allowing components to be readily identified.
Note that for simplicity, this table does not include bundle-oriented and collection-oriented relations.
Relation names appearing in bold correspond to the core structures introduced
in Section 2.1.
Table 45 is a complete index of all the types and relations of PROV-DM, color-coded according to the component they belong to. In the first column, concept names link to their informal definition, whereas, in the second column, representations link to the information used to represent the concept. Concept names appearing in bold are the core structures introduced in Section 2.1.
In the rest of the section, each type and relation is defined informally,
followed by a summary of the information used to represent the concept, and
illustrated with PROV-N examples.
4.15.1Component 1: Entities and Activities
The first component of PROV-DM is concerned with entities and activities, and their interrelations: Usage, Generation, Start, End, Invalidation, and Communication, and Start by Activity. Figure 5 uses UML to depict the first component, withcomponent.
Core structures are displayed in the yellow area, consisting of two classes (Entity, Activity) and three binary associations between them. Associations are not just binary: indeed, them (Usage, Generation, and Communication). The rest of the figure displays extended structures, including UML association classes (see [UML], section 7.3.4, p. 42), represented in gray, to express expanded n-ary relations (for Usage, Generation, Invalidation, Start, End). The figure also includemakes explicit associations withtimeattributes.for these concepts (time being marked with the primitive stereotype).
Figure 5: Entities and Activities Component Overview
4.1.15.1.1Entity
An entity is a physical, digital, conceptual, or other kind of thing;thing with some fixed aspects; entities may be real or imaginary.
An entity, written entity(id, [attr1=val1, ...]) in PROV-N, has:
id: an identifier for an entity;
attributes: an optional set of attribute-value pairs ((attr1, val1), ...) representing additional information about this entity.
states the existence of an entity, denoted by identifier tr:WD-prov-dm-20111215, with type document and version number 2. The attribute ex:version is application specific, whereas the attribute type (see Section 4.7.4.45.7.4.4) is reserved in the PROV namespace.
4.1.25.1.2Activity
An activity is something that occurs over a period of time and acts upon or with entities; it may include consuming, processing, transforming, modifying, relocating, using, generating, or being associated with entities.
An activity, written activity(id, st, et, [attr1=val1, ...]) in PROV-N, has:
id: an identifier for an activity;
startTime: an optional time (st) for the start of the activity;
endTime: an optional time (et) for the end of the activity;
attributes: an optional set of attribute-value pairs ((attr1, val1), ...) representing additional information about this activity.
states the existence of an activity with identifier a1, start time 2011-11-16T16:05:00, and end time 2011-11-16T16:06:00, running on host server.example.org, and of type edit. The attribute host is application specific (declared in some namespace with prefix ex). The attribute type is a reserved attribute of PROV-DM, allowing for sub-typing to be expressed (see Section 4.7.4.45.7.4.4).
Further considerations:
An activity is not an entity. This distinction is similar to the distinction between
'continuant' and 'occurrent' in logic [Logic].
4.1.35.1.3Generation
Generation is the completion of production of a new entity by an activity. This entity did not exist before generation and becomes available for usage after this generation.
Generation, written wasGeneratedBy(id,e,a,t,attrs)wasGeneratedBy(id; e, a, t, attrs) in PROV-N, has:
id: an optional identifier for a generation;
entity: an identifier (e) for a created entity;
activity: an optional identifier (a) for the activity that creates the entity;
time: an optional "generation time" (t), the time at which the entity was completely created;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this generation.
While each of id, activity, time, and attributes is optional, at least one of them must be present.
state the existence of two generations (with respective times 2001-10-26T21:32:52 and 2001-10-26T10:00:00), at which new entities, identified by e1 and e2, are created by an
activity, identified by a1.
The first one is available on port p1, whereas the other is available on port p2. The semantics of port are application specific.
In some cases, we may want to record the time at which an entity was generated without having to specify the activity that generated it. To support this requirement, the activity element in generation is optional. Hence, the following expression indicates the time at which an entity is generated, without naming the activity that did it.
Usage is the beginning of utilizing an entity by an activity. Before usage, the activity had not begun to utilize this entity and could not have been affected by the entity.
Usage, written used(id,a,e,t,attrs)used(id; a, e, t, attrs) in PROV-N, has:
id: an optional identifier for a usage;
activity: an identifier (a) for the consuming activity;activity that used an entity;
entity: an optional identifier (e) for the consumed entity; entity being used;
time: an optional "usage time" (t), the time at which the entity started to be used;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this usage.
While each of id, entity, time, and attributes is optional, at least one of them must be present.
A reference to a given entity may appear in multiple usages that share
a given activity identifier.
state that the activity identified by a1 used two entities identified by e1 and e2, at times 2011-11-16T16:00:00 and 2011-11-16T16:00:01, respectively; the first
one was found as the value of parameter p1, whereas the second was found as value of parameter p2. The semantics of parameter is application specific.
4.1.55.1.5 Communication
Communication is the exchange of an entity by two activities, one activity using the entity generated by the other.
A communication implies that activity a2 is dependent on another a1, by way of some unspecified entity that is generated by a1 and used by a2.
A communication, written as
wasInformedBy(id; a2, a1, attrs) in PROV-N, has:
id: an optional identifier identifying the relation;
informed: the identifier (a2) of the informed activity;
informant: the identifier (a1) of the informant activity;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this communication.
Consider two activities a1 and a2, the former performed by a government agency, and the latter by a driver caught speeding.
The last line indicates that some implicit entity was generated by a1 and used by a2; this entity may be a traffic ticket that had a notice of fine, amount, and payment mailing details.
5.1.6Start
Start is when an activity is deemed to have started. The activity did not exist before its start. Any usage or generation involving an activity follows the activity's start. A start may refer to an entity, known as trigger, that initiated the activity.
An activity start, written wasStartedBy(id,a,e,t,attrs)wasStartedBy(id; a2, e, a1, t, attrs) in PROV-N, has:
id: an optional identifier for the activity start;
activity: an identifier (aa2) for the started activity;
trigger: an optional identifier (e) for the entity triggering the activity;
starter: an optional identifier (a1) for the activity that generated the (possibly unspecified) entity (e);
time: the optional time (t) at which the activity was started;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this activity start.
The following example contains the description of an activity a1 (a discussion), which was started at a specific time, and was triggered by an email message e1.
In this example, filling fuel was started as a consequence of
observing low fuel. The trigger entity is unspecified, it could
for instance have been the low fuel warning light, the fuel tank
indicator needle position, or the engine not running properly.
The relations wasStartedBy and used are orthogonal, and thus need to be expressed independently, according to the situation being described.
4.1.65.1.7End
End is when an activity is deemed to have ended. The activity no longer exists after its end. Any usage, generation, or invalidation involving an activity precedes the activity's end. An end may refer to an entity, known as trigger, that terminated the activity.activity, or to an activity, known as ender that generated the trigger.
An activity end, written wasEndedBy(id,a,e,t,attrs)wasEndedBy(id; a2, e, a1, t, attrs) in PROV-N, has:
id: an optional identifier for the activity end;
activity: an identifier (aa2) for the ended activity;
trigger: an optional identifier (e) for the entity triggering the activity ending;
ender: an optional identifier (a1) for the activity that generated the (possibly unspecified) entity (e);
time: the optional time (t) at which the activity was ended;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this activity end.
Invalidation is the start of the destruction, cessation, or expiry of an existing entity by an activity. The entity is no longer available for use (or further invalidation) after invalidation. Any generation or usage of an entity precedes its invalidation.
Entities have a duration. Generation marks the beginning of an entity. entity, whereas invalidation marks its end.
An entity's lifetime can end for different reasons:
an entity was destroyed: e.g. a painting was destroyed by fire; a Web page is taken out of a site;
an entity was consumed: e.g. Bob ate all his soup, Alice ran out of gas when driving to work;
an entity expires: e.g. a "buy one beer, get one free" offer is valid during happy hour (7-8pm);
an entity is time limited: e.g. the BBC news site on April 3rd, 2012;
an entity attribute is changing: e.g. the traffic light changed from green to red.
In the first two cases, the entity has physically disappeared after its termination: there is no more soup, or painting. In the last twothree cases, there may be an "offer voucher" that still exists, but it is no longer valid; likewise, on April 4th, the BBC news site still exists but it is not the same entity as BBC news Web site on April 3rd; or the traffic light became red and therefore is regarded as a different entity to the green light.
Invalidation, written wasInvalidatedBy(id,e,a,t,attrs)wasInvalidatedBy(id; e, a, t, attrs) in PROV-N, has:
id: an optional identifier for a invalidation;
entity: an identifier for the invalidated entity;
activity: an optional identifier for the activity that invalidated the entity;
time: an optional "invalidation time", the time at which the entity began to be invalidated;
attributes: an optional set of attribute-value pairs representing additional information about this invalidation.
While each of id, activity, time, and attributes is optional, at least one of them must be present.
The Painter,Painter, a Picasso painting, is known to have been destroyed in a plane accident.
The BBC news home page on 2012-04-03 ex:bbcNews2012-04-03
contained a reference to a given news item
bbc:news/uk-17595024,
but the BBC news home page on the next day did not.
We refer to example anexample-specializationExample 40
for further descriptions of the BBC Web site, and to Section Membership5.6.5 for a description of the relation memberOf.
In this example, the "buy one beer, get one free" offer expired at the end of the happy hour.
We see that the offer was both used to be converted into twoBeers and invalidated by the redeemOffer activity: in other words, the combined usage and invalidation indicate consumption of the offer.
4.1.8 CommunicationCommunication is the exchange of an entity by two activities, one activity using the entity generated by the other. A communication implies that activity a2 is dependent on another a1, by way of some unspecified entity that is generated by a1 and used by a2.
A communication, written as
wasInformedBy(id,a2,a1,attrs) in PROV-N, has:
id: an optional identifier identifying the relation;informed: the identifier (a2) of the informed activity;
informant: the identifier (a1) of the informant activity;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this communication.
Consider two activities a1 and a2, the former performed by a government agency, and the latter by a driver caught speeding.
activity(a1, [prov:type="traffic regulations enforcing"])
activity(a2, [prov:type="fine paying, check writing, and mailing"])
wasInformedBy(a2,a1)
The last line indicates that some implicit entity was generated by a1 and used by a2; this entity may be a traffic ticket that had a notice of fine, amount, and payment mailing details.
4.1.9 Start by ActivityStart by Activity is the start of an activity with an implicit trigger generated by another activity.
A start by activity, written as
wasStartedByActivity(id, a2, a1, attrs) in PROV-N, has:
id: an optional identifier of the relation;started: the identifier (a2) of the started activity;
starter: the identifier (a1) of the activity that started the other;attributes: an optional set (attrs) of attribute-value pairs representing additional information about this start by activity.
Suppose activities a1 and a2 are computer processes that are executed on different hosts, and that a1 started a2. This can be expressed as in the following fragment:activity(a1,t1,t2,[ex:host="server1.example.org",prov:type="workflow"])
activity(a2,t3,t4,[ex:host="server2.example.org",prov:type="subworkflow"])
wasStartedByActivity(a2,a1)
It is assumed that the activities a1 and a2 are of type "workflow" and "subworkflow", respectively; the latter was started by the former.
4.25.2Component 2: Agents and Responsibility
The second component of PROV-DMPROV-DM, depicted in Figure 6, is concerned with agents and the notions of
Attribution, Association, ResponsibilityDelegation, relating agents to entities, activities, and agents, respectively.
Figure figure-component2 depicts the second component with four
Core structures are displayed in the yellow area and include three classes (Entity, Activity, Agent, and Plan)three binary associations. Outside the yellow area, extended structures comprise and associations between them. UML association classes to express expanded n-ary relations, and subclasses Plan, Person, SofwareAgent, and Organization. The subclasses are usedmarked by the UML stereotype "prov:type" to express n-ary relations.indicate that that these are valid values for the attribute prov:type
Figure 6: Agents and ResponsibilitiesResponsibility Component Overview
4.2.15.2.1Agent
An agent is something that bears some form of responsibility for an activity taking place or for the existence of an entity.
An agent, written agent(id, [attr1=val1, ...]) in PROV-N, has:
id: an identifier for an agent;
attributes: a set of attribute-value pairs ((attr1, val1), ...) representing additional information about this agent.
It is useful to define some basic categories of agents from an interoperability perspective.
There are three types of agents that are common across most anticipated domains of use; Itit is acknowledged that these types do not cover all kinds of agent.
SoftwareAgent
A software agent is running software.
Organization
Agents of type Organization are social or legal institutions such as companies, societies, etc.
Person
Agents of type Person are people.
The following expression is about an agent identified by e1, which is a person, named Alice, with employee number 1234.
It is optional to specify the type of an agent. When present, it is expressed using the prov:type attribute.
4.2.25.2.2Attribution
Attribution is the ascribing of an entity to an agent.
When an entity e is attributed to agent ag, entity e was generated by some unspecified activity that in turn was associated to agent ag. Thus, this relation is useful when the activity is not known, or irrelevant.
An attribution relation, written wasAttributedTo(id,e,ag,attrs)wasAttributedTo(id; e, ag, attrs) in PROV-N, has:
id: an optional identifier for the relation;
entity: an entity identifier (e);
agent: the identifier (ag) of the agent whom the entity is ascribed to;to, and therefore bears some responsibility for its existence;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this attribution.
Revisiting the example of Section 3.14.1,
we can ascribe tr:WD-prov-dm-20111215 to some agents without an explicit activity. The reserved attribute role (see Section 4.7.4.35.7.4.3) allows for role of the agent in the attribution to be specified.
An activity association is an assignment of responsibility to an agent for an activity, indicating that the agent had a role in the activity. It further allows for a plan to be specified, which is the plan intended by the agent to achieve some goals in the context of this activity.
A plan is an entity that represents a set of actions or steps intended by one or more agents to achieve some goals.
An activity association, written wasAssociatedWith(id,a,ag,pl,attrs)wasAssociatedWith(id; a, ag, pl, attrs) in PROV-N, has:
id: an optional identifier for the association between an activity and an agent;
activity: an identifier (a) for the activity;
agent: an optional identifier (ag) for the agent associated with the activity;
plan: an optional identifier (pl) for the plan adopted by the agent in the context of this activity;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this association of this activity with this agent.
In the following example, a designer agent and an operator agentsagent are associated with an activity. The designer's goals are achieved by a workflow ex:wf, described as an an entity of type plan.
Since the workflow ex:wf is itself an entity, its provenance can also be expressed in PROV-DM: it can be generated by some activity and derived from other entities,
for instance.
In some cases, one wants to indicate a plan was followed, without having to specify which agent was involved.
In this case, it is assumed that an agent exists, but it has not been specified.
4.2.4 Responsibility5.2.4 Delegation
ResponsibilityDelegation is the factassignment of authority to an agent (by itself or by another agent) to carry out a specific activity as a delegate or representative, while the agent that an agent is accountableit represents remains responsible for the actions of a "subordinate" agent, in the context of an activity. outcome of the delegated work.
PROV offersFor example, a mild version of responsibility
in the form of a relation to represent when an agent acted on another
agent's behalf. So for example someone running a mail program,
the program and the person are both
agents of the activity; furthermore, the mail software
agent is running on the person's behalf. In another example, the
student acted on behalf of his supervisor, who acted on behalf of the
department chair, who acted on behalf of the university; all those
agents are responsible in some way for the activity that took place but
we do not say explicitly who bears responsibility and to what
degree.
A responsibilitydelegation link, written actedOnBehalfOf(id,ag2,ag1,a,attrs)actedOnBehalfOf(id; ag2, ag1, a, attrs) in PROV-N, has:
id: an optional identifier for the responsibilitydelegation link between subordinatedelegate and responsible;
subordinatedelegate: an identifier (ag2) for the agent associated with an activity, acting on behalf of the responsible
agent;
responsible: an identifier (ag1) for the agent, on behalf of which the subordinatedelegate agent acted;
activity: an optional identifier (a) of an activity for which the responsibilitydelegation link holds;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this responsibilitydelegation link.
The following fragment describes three agents: a programmer, a researcher, and a funder. The programmer and researcher are associated with a workflow activity. The programmer acts on behalf
of the researcher (delegation)(line-management) encoding the commands specified by the researcher; the researcher acts on behalf of the funder, who has a contractual agreement with the researcher. The terms
'delegation''line-management' and 'contact''contract' used in this example are domain specific.
The third component of PROV-DM is concerned withwith:derivations of entities from others, andothers; derivation subtypes Revision, Quotation, and Original Source, and; derivation-relatedTrace.
Figure figure-component37 depicts the third component
with three PROV core structures in the yellow area, including two classes (Entity, Activity,
(Entity, Activity) and Agent) and associations between them.binary association
(Derivation). PROV extended structures are found outside this
area. UML association classes express expanded n-ary relations.
Figure 7: Derivation Component Overview
4.3.15.3.1Derivation
A derivation is a transformation of an entity into another, an update of an entity, resulting in a new one, or based on an entity, the construction of an entity into another, or an update of an entity, resulting in a new one.another.
According to Section 2, for an entity to be transformed from, created from, or resulting from an update to another, there must be some
underpinning activities performing the necessary actions resulting in such a derivation.
A derivation can be described at various levels of precision. In its simplest form, derivation relates two entities. Optionally, attributes can be added to represent further information about the derivation. If the derivation is the result of a single known activity, then this activity can also be optionally expressed. To provide a completely accurate description of the derivation, the generation and usage of the generated and used entities, respectively, can be provided.provided, so as to make the derivation path, through usage, activity, and generation, explicit. Optional information such as activity, generation, and usage can be linked to derivations to aid analysis of provenance and to facilitate provenance-based reproducibility.
A derivation, written wasDerivedFrom(id,wasDerivedFrom(id; e2, e1, a, g2, u1, attrs) in PROV-N, has:
id: an optional identifier for a derivation;
generatedEntity: the identifier (eee2) of the entity generated by the derivation;
usedEntity: the identifier (e1) of the entity used by the derivation;
activity: an optional identifier (a) for the activity using and generating the above entities;
generation: an optional identifier (g2) for the generation involving the generated entity (e2) and activity;
usage: an optional identifier (u1) for the usage involving the used entity (e1) and activity;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this derivation.
The following descriptions are about derivations between e2 and e1, but no information is provided as to the identity of the activity (and usage and generation) underpinning the derivation. In the second line, a type attribute is also provided.
The following description expresses that activity a,
using the entity e1 according to usage u1,
derived the
entity e2 and generated it according to generation
g2. It is followed by descriptions for generation g2 and usage u1.
wasDerivedFrom(e2, e1, a, g2, u1)
wasGeneratedBy(g2,wasGeneratedBy(g2; e2, a, -)
used(u1,used(u1; a, e1, -)
With such a comprehensive description of derivation, a program that analyzes provenance can identify the activity underpinning the derivation, it can identify how the original entity e1 was used by the activity (e.g. for instance, which argument it was passed as, if the activity is the result of a function invocation), and which output the derived entity e2 was obtained from (say, for a function returning multiple results).
4.3.25.3.2Revision
A revision is a derivation that revises an entity into a revised version.
Deciding whether something is made available as a revision of something else usually involves an agent who takes responsibility for approving that the former is a due variant of the latter.
The agent who is responsible for the revision may optionally be specified.
Revision is a particular case of derivation of an entity into its revised version.
A revision relation, written wasRevisionOf(id,e2,e1,ag,attrs) in PROV-N, has:id: an optional identifier for the relation;newer: the identifier (e2) of the revised entity;
older: the identifier (e1) of the older entity;
responsibility: an optional identifier (ag) for the agent who approved the newer entity as a variant of the older;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this relation.
Revisiting the example of Section 3.24.2,
we can now state that the report
tr:WD-prov-dm-20111215iswas a revision of
the report tr:WD-prov-dm-20111018, approved by
agent w3:Consortium.
A quotation is the repeat of (some or all of) an entity, such as text or image, by someone other thanwho may or may not be its original author.
Quotation
is a particular case of derivation in which an entity e2 is derived from an original entity e1 by copying, or "quoting", some or all of it.
A quotation relation, written wasQuotedFrom(id,e2,e1,ag2,ag1,attrs) in PROV-N, has:
id: an optional identifier for the relation;quote: an identifier (e2) for the entity that represents the quote (the partial copy);
original: an identifier (e1) for the original entity being quoted;
quoterAgent: an optional identifier (ag2) for the agent who performs the quote;
originalAgent: an optional identifier (ag1) for the agent to whom the original entity is attributed;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this relation.
"During the workshop, it became clear to me that the consensus based models (which are often graphical in nature) can not only be formalized but also be directly connected to these database focused formalizations. I just needed to get over the differences in syntax. This could imply that we could have nice way to trace provenance across systems and through databases and be able to understand the mathematical properties of this interconnection."
An original source refers to the source material that is closest to the person, information, period, or idea being studied.
An original source relation is a particular case of derivation
that aims to give
credit to the source that originated some information. It is recognized that it may be
hard to determine which entity constitutes an original source. This definition is inspired by
original-source as defined in
http://googlenewsblog.blogspot.com/2010/11/credit-where-credit-is-due.html.
An original source relation, written hadOriginalSource(id,e2,e1,attrs), has:id: an optional identifier for the relation;derived: an identifier (e2) for the derived entity; source: an identifier (e1) for the original source entity;attributes: an optional set (attrs) of attribute-value pairs representing additional information about this relation.
Let us consider the concept introduced in the current section, identified as dm:concept-original-source, and
the Google page go:credit-where-credit-is-due.html, where the notion original-source was originally described (to the knowledge of the authors).
Trace is the ability to link back an entity to another by means of derivation or responsibility relations, possibly repeatedly traversed.
A trace relation between two entities e2 and e1 is a generic dependency of e2
on e1 that indicates either that e1 may have been necessary for e2 to be created, or that e1 bears
some responsibility for e2's existence.
A Trace relation , written tracedTo(id,e2,e1,attrs)tracedTo(id; e2, e1, attrs) in PROV-N, has:
id: an optional identifier identifying the relation;
entity: an identifier (e2) for an entity;
ancestor: an identifier (e1) for an ancestor entity that the former depends on;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this relation.
We note that the ancestor is allowed tomay be an agent since agents are may be entities.
We refer to the example of Section 3.14.2, and specifically to Figure 3. We can see that there is a path from
tr:WD-prov-dm-20111215 to
w3:Consortium and to
process:rec-advance. This is expressed as follows.
The fourth component of PROV-DM is concerned with
relations specialization and alternate between entities.
Figure figure-component48 depicts
the fourth component with a single class and two binary associations.
Figure 8: Alternates Component Overview
Wherever two people describe theTwo provenance of adescriptions about the same thing,
one cannot expect them to coordinate and agree on the identifiers to use to denotething may emphasize differents aspects of that thing.
User Alice writes an article. In its provenance, she wishes to refer to the precise version of the article with a date-specific URI,IRI, as she might edit the article later. Alternatively, user Bob refers to the article in general, independently of its variants over time.
To allow for identifiers to be chosen freelyThe PROV data model introduces relations, called specialization and independently by each user, the PROV data model introduces relationsalternate,
that allow entities to be linked together.
The following two relations They are introduced for expressing specialized or alternate entities.defined as follows.
4.4.15.4.1Specialization
An entity that is a specialization of another if they refer to some commonshares all aspects of the latter, and additionally presents more specific aspects of the same thing but the former is a more constrainedas the latter. In particular, the lifetime of the specialized entity than the latter. The common thing does not need to be identified. contains that of any specialization.
Examples of constraints aspects include a time period, an abstraction, and a context associated with the entity.
A specialization relation, written specializationOf(sub, super)specializationOf(infra, supra) in PROV-N, has:
specializedEntityspecialization: an identifier (subinfra) of the specialized entity;
generalEntity: an identifier (supersupra) of the entity that is being specialized.
The BBC news home page on 2012-03-23 ex:bbcNews2012-03-23
is a specialization of the BBC news page in general
bbc:news/. This can be expressed as follows.
specializationOf(ex:bbcNews2012-03-23, bbc:news/)
We have created a new qualified name, ex:bbcNews2012-03-23, in the namespace ex, to identify the specific page carrying this day's news, which would otherwise be the generic bbc:news/ page.
4.4.25.4.2Alternate
An entity isTwo alternate of another if they are both a specialization of some common entity. The common entity doesentities present aspects of the same thing. These aspects may be the same or different, and the alternate entities may or may not need to be identified. overlap in time.
An alternate relation, written alternateOf(e1, e2) in PROV-N, has:
alternate1: an identifier (e1) of the first of the two entities;
alternate2: an identifier (e2) of the second of the two entities.
entity(bbc:news/science-environment-17526723, [ prov:type="a news item for desktop"])
entity(bbc:news/mobile/science-environment-17526723, [ prov:type="a news item for mobile devices"])
alternateOf(bbc:news/science-environment-17526723, bbc:news/mobile/science-environment-17526723)
They are both specialization of an (unspecified) entity.
Considering again the two versions of the technical report tr:WD-prov-dm-20111215 (second working draft) and tr:WD-prov-dm-20111018 (first working draft). They are alternate of each other.
The fifth component of PROV-DM is concerned with bundles, a mechanism to support provenance of provenance.
Figure 9 depict a UML class diagram for the fifth component. It comprises a Bundle class, a subclass of Entity and a novel n-ary relation, Provenance Locator.
Figure 9: Bundle Component Overview
5.5.1 Bundle constructor
A bundle is a named set of provenance descriptions, and is itself an entity, so allowing provenance of provenance to be expressed.
A bundle constructor allows the content and the name of a bundle to be specified; it is written bundle id description_1 ... description_n endBundle and consists of:
id: an identifier for the bundle;
descriptions: a set of provenance descriptions
description_1, ..., description_n.
A bundle's identifier id identifies a unique set of descriptions.
5.5.2 Bundle Description
A bundle is a named set of descriptions, but it is also an entity so that its provenance can be described.
A bundle description is of the form entity(id,[prov:type='prov:Bundle', attr1=val1, ...])
where id is an identifier denoting a bundle,
a type prov:Bundle and
an optional set of attribute-value pairs ((attr1, val1), ...) representing additional information about this bundle.
The provenance of provenance can then be described using PROV constructs, as illustrated by
Example 43
and
Example 44.
Let us consider two entities ex:report1 and ex:report2.
The new bundle is given a new identifier agg:bundle3 and is attributed to the ex:aggregator01 agent.
5.5.3 Provenance Locator
In Example 43, we initially presented a scenario involving two entities report1 and report2, and showed how their descriptions can be organized into two bundles. There is no explicit indication that the second bundle "is a continuation" of the description offered by the first bundle. Given that bundles may be retrieved separately [PROV-AQ], it is not obvious for a provenance consumer to navigate descriptions across bundles. To aid consumers,
Alice may wish to express that there is further provenance information about report1 in bundle bob:bundle1. To this end, PROV introduces the notion of provenance locator, inspired by [PROV-AQ].
A provenance locator is information that helps locate provenance descriptions. It can identify a bundle within which provenance descriptions can be found. It may further identify a service, or may offer a IRI where provenance descriptions can be found.
A provenance locator,
written
hasProvenanceIn(id, subject, bundle, target, attrs), has:
id: an identifier for a provenance locator;
subject: an identifier denoting something (entity, activity, agent, or relation instance);
bundle: an optional identifier (bundle) for a bundle;
target: an optional identifier (target) denoting something described in another set of descriptions (referred to as Target-URI in [PROV-AQ]);
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this locator; it optionally includes
prov:service-uri
or
prov:provenance-uri.
If the target is not specified, it is assumed that target is the same identifier as subject.
When the subject and optional target denote entities,
a provenance locator not only provides a located context, but it also expresses an alternate relation between the entity denoted by subject and the entity described in the located context. This is an alternate since the entity denoted by subject in the current context presents other aspects than the entity in the located one.
According to the following provenance locator, provenance descriptions about ex:report1 can be found in bundle bob:bundle1.
hasProvenanceIn(ex:report1, bob:bundle1, -)
According to the following provenance locator, provenance descriptions about ex:report1 can be found in bundle bob:bundle1, which is available from the provenance service identified by the provided URI.
In bundle alice:bundle5, there is a description for entity ex:report1, and
a provenance locator pointing to bundle bob:bundle4.
The locator indicates that some provenance description for ex:report1 can be found in bundle bob:bundle4. The purpose of the locator is twofold. First, it allows for incremental navigation of provenance [PROV-AQ]. Second, it makes entity ex:report1 described in alice:bundle5 an alternate of ex:report1 described in bob:bundle4.
Alternatively, Alice may have decided to use a different identifier for ex:report1.
Alice can specify the target in the provenance locator to be ex:report1.
With such a statement, Alice states that provenance information about alice:report1 can be found in bundle
bob:bundle4 under the name ex:report1. In effect, alice:report1 and ex:report1 are declared to be alternate.
Consider the following bundle of descriptions, in which derivation and generations have been identified.
Bundle obs:bundle7 is rendered by a visualisation tool. It may useful for the tool configuration for this bundle to be shared along with the provenance descriptions, so that other users can render provenance as it was originally rendered. The original bundle obviously cannot be changed. However, one can create a new bundle, as follows.
bundle tool:bundle8
entity(tool:bundle8, [ prov:type='viz:Configuration', prov:type='prov:Bundle' ])
wasAttributedTo(tool:bundle8, viz:Visualizer)
entity(ex:report1, [viz:color="orange"]) // ex:report1 is a reused identifier
hasProvenanceIn(ex:report1, obs:bundle7, -)
entity(tool:r2, [viz:color="blue"]) // tool:r2 is a new identifier
hasProvenanceIn(tool:r2, obs:bundle7, ex:report2)
wasDerivedBy(ex:d; ex:report2, ex:report1, [viz:style="dotted"])
hasProvenanceIn(ex:d, obs:bundle7, -)
endBundle
In bundle tool:bundle8, the prefix viz is used for naming visualisation-specific attributes, types or values.
Bundle tool:bundle8 is given type viz:Configuration to indicate that it consists of descriptions that pertain to the configuration of the visualisation tool. This type attribute can be used for searching bundles containing visualization-related descriptions.
For the purpose of illustration, we show that the visualisation tool
reused identifier ex:report1, but created a new identifier tool:r2.
They denote entities which are alternates of with ex:report1 and ex:report2, described in bundle obs:bundle7, with visualization attribute for the color to be used when rendering these entities.
Likewise, the derivation has a style attribute.
According to their definition,
derivations have an optional identifier.
To express an alternate for a derivation, we need to be able to reference it, by means of an identifier. Hence, it is necessary for it to have an identifier in the first place (ex:d).
5.6 Component 6: Collections
The fifth component of PROV-DM is concerned with the notion of collections.
A collection is an entity that has some members. The members are themselves entities, and therefore their provenance can be expressed. Some applications need to be able to express the provenance of the collection itself: e.g. who maintains the collection, which members it contains as it evolves, and how it was assembled. The purpose of Component 5 is to define the types and relations that are useful to express the provenance of collections. In PROV, the concept of Collection is implemented by means of dictionaries, which we introduce in this section.
Figure figure-component510 depicts
the fifthsixth component with fourthree new classes (Collection, Dictionary, and Pair) and three associations.associations (insertion, removal, and memberOf).
Figure 9:10: Collections Component Overview
The intent of these relations and types is to express the history of changes that occurred to a collection.
Changes to collections are about the insertion of entities in collections and the removal of members from collections.
Indirectly, such history provides a way to reconstruct the contents of a collection.
4.5.15.6.1Collection
A collection is an entity that provides a structure to some constituents, which are themselves entities. These constituents are said to be member of the collections.
In PROV, the concept of Collection is provided as an extensibility point for other kinds of collections. Collections are implemented by means of dictionaries, which are introduced next.
4.5.25.6.2Dictionary
PROV-DM defines a specific type of collection: a dictionary, specified as follows.
A dictionary is a collection whose members are indexed by keys.
Conceptually, a dictionary has a logical structure consisting of key-entity pairs. This structure is often referred to as a map, and is a generic indexing mechanism that can abstract commonly used data structures, including associative lists (also known as "dictionaries" in some programming languages), relational tables, ordered lists, and more. The specification of such specialized structures in terms of key-value pairs is out of the scope of this document.
A given dictionary forms a given structure for its members. A different structure (obtained either by insertion or removal of members) constitutes a different dictionary. Hence,
for the purpose of provenance, a dictionary entity is viewed as a snapshot of a structure. Insertion and removal operations result in new snapshots, each snapshot forming an identifiable dictionary entity.
PROV-DM defines the following types related to dictionaries:
prov:Dictionary denotes an entity of type dictionary, i.e. an entity that can participate in relations amongst dictionaries;
prov:EmptyDictionary denotes an empty dictionary.
entity(d0, [prov:type="prov:EmptyDictionary" %% xsd:QName])[prov:type='prov:EmptyDictionary' ]) // d0 is an empty dictionary
entity(d1, [prov:type="prov:Dictionary"[prov:type='prov:Dictionary'%% xsd:QName])]) // d1 is a dictionary, with unknown content
4.5.35.6.3Insertion
Insertion is a derivation that transforms a dictionary into another, by insertion of one or more key-entity pairs.
An Insertion relation, written derivedByInsertionFrom(id,derivedByInsertionFrom(id; d2, d1, {(key_1, e_1), ..., (key_n, e_n)}, attrs), has:
id: an optional identifier identifying the relation;
after: an identifier (d2) for the dictionary after insertion;
before: an identifier (d1) for the dictionary before insertion;
key-entity-set: the inserted key-entity pairs (key_1, e_1), ..., (key_n, e_n) in which each key_i is a value, and e_i is an identifier for the entity that has been inserted with the key;
each key_i is expected to be unique for the key-entity-set;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this relation.
An Insertion relation derivedByInsertionFrom(id,derivedByInsertionFrom(id; d2, d1, {(key_1, e_1), ..., (key_n, e_n)}) states that d2 is the state of the dictionary
following the insertion of pairs (key_1, e_1), ..., (key_n, e_n) into dictionary d1.
d2 is the set { ("k1", e1), ("k2", e2), ("k3", e3) }
Insertion provides an "update semantics" for the keys that are already present in a dictionary,
since a new pair replaces an existing pair with the same key in the new dictionary. This is illustrated by the following example.
This is a case of update of e1 to e3 for the same key, "k1".
From this set of descriptions, we conclude:
d0 is the set { }
d1 is the set { ("k1", e1), ("k2", e2) }
d2 is the set { ("k1", e3), ("k2", e2) }
4.5.45.6.4Removal
Removal is a derivation that transforms a dictionary into another, by removing one or more key-entity pairs.
A Removal relation, written derivedByRemovalFrom(id,derivedByRemovalFrom(id; d2, d1, {key_1, ... key_n}, attrs), has:
id: an optional identifier identifying the relation;
after: an identifier (d2) for the dictionary after the deletion;
before: an identifier (d1) for the dictionary before the deletion;
key-set: a set of deleted keys key_1, ..., key_n, for which each key_i is a value;
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this relation.
A Removal relation derivedByRemovalFrom(id,derivedByRemovalFrom(id; d2,d1, {key_1, ..., key_n}) states that d2 is the state of the dictionary following the removal of the set of pairs corresponding to keys key_1...key_n from d1.
d2 is the set { ("k1", e1), ("k2", e2), ("k3", e3) }
d3 is the set { ("k2", e2) }
4.5.55.6.5Membership
Membership is the belonging of a key-entity pair to dictionary.
The insertion and removal relations make insertions and removals explicit as part of the history of a dictionary. This, however, requires explicit mention of the state of the dictionary prior to each operation. The membership relation removes this needs,need, allowing the state of a dictionary c to be expressed without having to introduce a prior state.
A membership relation, written memberOf(id,memberOf(id; c, {(key_1, e_1), ..., (key_n, e_n)}, cplt, attrs), has:
id: an optional identifier identifying the relation;
after: an identifier (c) for the dictionary whose members are asserted;
key-entity-set: a set of key-entity pairs (key_1, e_1), ..., (key_n, e_n) that are members of the dictionary;
complete: an optional boolean
Value (cplt); if true, it indicates that no other member belongs to the dictionary; if false, it indicates that other members belong to the dictionary; if unspecified, other members may belong to the dictionary.
attributes: an optional set (attrs) of attribute-value pairs representing additional information about this relation.
The description memberOf(c, {(key_1, e_1), ..., (key_n, e_n)}) states that c is known to include (key_1, e_1), ..., (key_n, e_n)}, without having to introduce a previous state.
entity(d1, [prov:type="prov:Dictionary"[prov:type='prov:Dictionary'%% xsd:QName])]) // d1 is a dictionary, with unknown content
entity(d2, [prov:type="prov:Dictionary"[prov:type='prov:Dictionary'%% xsd:QName])]) // d2 is a dictionary, with unknown content
entity(e1)
entity(e2)
memberOf(d1, {("k1", e1), ("k2", e2)} )
memberOf(d2, {("k1", e1), ("k2", e2)}, true)
entity(e3)
entity(d3, [prov:type="prov:Dictionary"[prov:type='prov:Dictionary'%% xsd:QName])])
derivedByInsertionFrom(d3, d1, {("k3", e3)})
From these descriptions, we conclude:
d1 has the following pairs as members: ("k1", e1), ("k2", e2), and may contain others.
d2 exactly has the following pairs as members: ("k1", e1), ("k2", e2), and does not contain any other.
d3 has the following pairs as members: ("k1", e1), ("k2", e2), ("k3", v3), and may contain others.
Thus, the states of d1 and d3 are only partially known.
Further considerations:
The state of a dictionary (i.e., the set of key-entity pairs it contains) at a given point in a sequence of operations is never stated explicitly. Rather, it can be obtained by querying the chain of derivations involving insertions and removals. Entity type emptyDictionary can be used in this context as it marks the start of a sequence of dictionary operations.
The representation of a dictionary through these relations makes no assumption regarding the underlying data structure used to store and manage dictionaries. In particular, no assumptions are needed regarding the mutability of a data structure that is subject to updates. Entities, however, are immutable and this applies to those entities that represent dictionaries. This is reflected in the constraints listed in [PROV-CONSTRAINTS].
4.6 Component 6: AnnotationsThe sixth component of PROV-DM is concerned with notes and annotations.
As provenance descriptions are exchanged between systems, it may be useful for a third party to add extra information to what they are describing. For instance, a "trust service" may add value-judgements about the
trustworthiness of some of the entities or agents occurring in provenance records it is given access to. Likewise, an interactive visualization component may want to enrich an existing set of provenance descriptions with information helping reproduce their
visual representation. To help with interoperability, PROV-DM introduces a simple annotation mechanism allowing anything that is identifiable to be associated with notes.
For this, a type and and a relation are introduced.The annotation mechanism (with note and annotation) forms a key aspect of the extensibility mechanism of PROV-DM (see extensibility section).4.6.1 Note A note is an identified set of application-specific attribute-value pairs.A note, written note(id, [attr1=val1, ...]) in PROV-N, has:
id: an identifier for a note;attributes: a set of attribute-value pairs ((attr1, val1), ...) representing application-specific information.
The following note consists of a set of application-specific attribute-value pairs, intended
to help the rendering of the pre-existing entity it is associated with, by
specifying its color and its position on the screen.note(ex:n1,[draw:color="blue", draw:screenX=20, draw:screenY=30])
hasAnnotation(tr:WD-prov-dm-20111215,ex:n1)
The note is linked to the entity tr:WD-prov-dm-20111215, with
relation hasAnnotation
discussed in Section 4.6.2.
The note's identifier is declared in the namespace denoted by prefix ex to illustrate that the rendering application may differ from the application involving entity tr:WD-prov-dm-20111215. The prefix draw also denotes an application-specific namespace.
In contrast, a reputation service may enrich an existing provenance record with notes providing reputation ratings about agents. In the following fragment, both agents ex2:Simon and ex2:Paolo are rated "excellent".note(ex3:n2,[trust:reputation="excellent"])
hasAnnotation(ex2:Simon,ex3:n2)
hasAnnotation(ex2:Paolo,ex3:n2)
The note's identifier is declared in a separate namespace denoted by prefix ex3. The prefix trust also denotes an application specific namespace.4.6.2 Annotation An annotation is a link between something that is identifiable and a note referred to by its identifier.Multiple notes can
be associated with a given identified object; symmetrically, multiple objects can be associated with a given note. Since notes have identifiers, they can also be
annotated. An annotation relation, written hasAnnotation(r,n) in PROV-N, has:
something: the identifier (r) of something being annotated;note: an identifier (n) of a note.
The following expressionsentity(e1,[prov:type="document"])
entity(e2,[prov:type="document"])
activity(a,t1,t2)
used(u1,a,e1,[ex:file="stdin"])
wasGeneratedBy(e2, a, [ex:file="stdout"])
note(n1,[ex:icon="doc.png"])
hasAnnotation(e1,n1)
hasAnnotation(e2,n1)
note(n2,[ex:style="dotted"])
hasAnnotation(u1,n2)
describe two documents (attribute-value pair: prov:type="document") identified by e1 and e2, and their annotation with a note indicating that the icon (an application specific way of rendering provenance) is doc.png. The example also
includes an activity, its usage of the first entity, and its generation of the second entity. The usage is annotated with a style (an application specific way
of rendering this edge graphically). To be able to express this annotation, the usage was provided with an identifier u1, which was then referred to in hasAnnotation(u1,n2).
4.75.7Further Elements of PROV-DM
This section introduces further elements of PROV-DM.
4.7.15.7.1Namespace Declaration
A PROV-DM namespace is identified by an IRI [IRI]. In PROV-DM, attributes, identifiers, and values with qualified names as data type can be placed in a namespace using the mechanisms described in this specification.
A namespace declaration consists of a binding between a prefix and a namespace. Every qualified name with this prefix in the scope of this
declaration refers to this namespace.
A default namespace declaration consists of a namespace. Every un-prefixed qualified name in the scope of this default namespace declaration
refers to this namespace.
A qualified name is a name subject to namespace interpretation. It consists of a namespace, denoted by an optional prefix, and a local name.
PROV-DM stipulates that a qualified name can be mapped into an IRI
by concatenating the IRI associated with the prefix and the local part.
A qualified name's prefix is optional. If a prefix occurs in a
qualified name, it refers to a namespace declared in a namespace declaration. In the absence of prefix, the qualified name
refers to the default namespace.
The PROV data model introduces a pre-defined set of attributes in the PROV namespace, which we define below.
This specification does not provide any interpretation for any attribute declared in any other namespace.
The attribute prov:label provides a human-readable representation of a PROV-DM element or relation. The value associated with the attribute prov:labelmust be a string.
The following entity is provided with a label attribute.
entity(ex:e1, [prov:label="This is a label"])
4.7.4.25.7.4.2prov:location
A location can be an identifiable geographic place (ISO 19112), but it can also be a non-geographic place such as a directory, row, or column. As such, there are numerous ways in which location can be expressed, such as by a coordinate,
address, landmark, and so forth. This document does not specify how to concretely express locations, but instead provide a mechanism to introduce locations, by means of a reserved attribute.
The attribute prov:location is an optional attribute of entity, activity, usage, and generation. The value associated with the attribute prov:locationmust be a PROV-DM Value, expected to denote a location.
The following expression describes entity Mona Lisa, a painting, with a location attribute.
The attribute prov:role denotes the function of an entity with respect to an activity, in the context of a usage, generation,usage, generation,association,association,start,start, and end.end. The attribute prov:role is allowed to occur multiple times in a list of attribute-value pairs. The value associated with a prov:role attribute must be a PROV-DM Value.
The following activity is associated with an agent acting as the operator.
wasAssociatedWith(a, ag, [prov:role="operator"])
4.7.4.45.7.4.4prov:type
The attribute prov:type provides further typing information for an element or relation. PROV-DM liberally
defines a type as a category of things having common characteristics. PROV-DM is agnostic about the representation of types, and only states that
the value associated with a prov:type attribute must be a PROV-DM Value. The attribute prov:type
is allowed to occur multiple times.
The following describes an agent of type software agent.
The attribute prov:value provides a Value associated with an entity.
The attribute prov:value is an optional attribute of entity. The value associated with the attribute prov:valuemust be a PROV-DM Value. The attribute prov:valuemay occur at most once in a set of attribute-value pairs.
The following example illustrates the provenance of the number 4 obtained by an activity that computed the length of an input string "abcd".
The input and the output are expressed as entities ex:in and ex:out, respectively. They each have a prov:value attribute associated with the corresponding value.
The attribute prov:provenance-uri provides
an optional IRI in the context of a Provenance Locator; when this IRI is dereferenced, it allows access to provenance descriptions. It is referred to as Provenance-URI in [PROV-AQ].
According to the following provenance locator, provenance descriptions about ex:report1 can be found in bundle bob:bundle1, which is available from the provenance service identified by the provided URI.
The attribute prov:service-uri provides
an optional IRI in the context of a Provenance Locator; this IRI denotes a provenance service from which provenance can be retrieved. It is referred to as Service-URI in [PROV-AQ].
By means of attribute-value pairs, the PROV data model can refer to values such as strings, numbers, time, qualified names, and IRIs.
The interpretation of such values is outside the scope of PROV-DM.
Each kind of such values is called a datatype. The datatypes are taken from
the set of XML Schema Datatypes, version 1.1 [XMLSCHEMA-2] and the RDF specification [RDF-CONCEPTS]. The normative definitions of these datatypes are provided by the respective specifications.
Each datatype is identified by its XML xsd:QName.
We note that PROV-DM time instants are defined according to xsd:dateTime [XMLSCHEMA-2].
In the following example, the generation time of entity e1 is expressed according to
xsd:dateTime [XMLSCHEMA-2].
wasGeneratedBy(e1,a1, 2001-10-26T21:32:52)
We need to check that we are including all xsd types that are the latest versions of XML Schema/RDF.
5.6.PROV-DM Extensibility Points
The PROV data model provides extensibility points that allow designers to specialize it tofor specific applications or domains. We summarize these extensibility points here:
Attribute-value lists occur in all types and relations of the data model. Applications designers are free to introduce further application-specific attributes. Attributes for a given application can be distinguished by qualifying them with a prefix denoting a namespace
declared in a namespace declaration.
New namespaces and associated prefixes can be declared, allowing attributes and names to be qualified.
Notes allow arbitrary metadata to be associated with anything identifiable in PROV-DM. Notes consist of attribute-value pairs. Attributes are qualified by a
namespace.
The PROV data model is designed to be application and technology independent, but specializations of PROV-DM are welcome and encouraged. To ensure interoperability, specializations of
the PROV data model that exploit the extensibility points summarized in this section must preserve the semantics specified in this document and in [PROV-CONSTRAINTS].
6.7.Creating Valid Provenance
This specification defines PROV-DM, a data model that allows
descriptions of the people, institutions, entities, and activities,
involved in producing, influencing, or delivering a piece of data or a
thing to be expressed. However, with this data model, it is also possible to compose
descriptions that would not make sense: for instance, one could
express that an entity was used before it was generated, or that the
activity that generated an entity began its existence after the entity
generation. A set of constraints have been defined for PROV-DM and
can be found in a companion specification [PROV-CONSTRAINTS].
They should be used by developers to compose provenance descriptions that are valid, and
by implementers of reasoning engines aiming to check whether provenance descriptions have problems.
The example of section 3 contains identifiers such as tr:WD-prov-dm-20111215, which denotes a specific version of a technical report. On the other hand, a URI such as http://www.w3.org/TR/prov-dm/ denotes the latest version of a document. One needs to ensure that provenance descriptions for the latter resource remain valid as the resource state changes.
To this end, PROV-DM allows asserters to describe "partial states" of entities by means of attributes and associated values. Some further constraints apply to the use of these attributes, since the values associated with them are expected to remain unchanged for some period of time. The constraints associated to attributes allow provenance descriptions to be refined, they can also be found in the companion specification [PROV-CONSTRAINTS].
The idea of bundling provenance descriptions is crucial to the PROV approach. Indeed, it allows multiple provenance perspectives to be provided for a given entity. It is also the mechanism by which provenance of provenance can be expressed. Such a named bundle is referred
Descriptions in bundles are expected to as an account and is regarded as an Account so that its provenance can be expressed. The notion of account issatisfy constraints specified in the companion specification [PROV-CONSTRAINTS], as well as the constraints that structurally well-formed descriptions should satisfy.].
