Datasets published on the web are accessed and experienced by consumers in a variety of ways, but little information about these experiences is typically conveyed. Dataset publishers many times lack feedback from consumers about how datasets are used. Consumers lack an effective way to discuss experiences with fellow collaborators and explore referencing material citing the dataset. Datasets as defined by DCAT are a collection of data, published or curated by a single agent, and available for access or download in one or more formats. The Dataset Usage Vocabulary (DUV) is used to describe consumer experiences, citations, and feedback about the dataset from the human perspective.
By specifying a number of foundational concepts used to collect dataset consumer feedback, experiences, and cite references associated with a dataset, APIs can be written to support collaboration across the web by structurally publishing consumer opinions and experiences, and provide a means for data consumers and producers advertise and search for published open dataset usage.
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This is a draft document which may be merged with the Data Quality Vocabulary or remain as a standalone document. Feedback is sought on the overall direction being taken as much as the specific details of the proposed vocabulary.
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This section is non-normative.
This vocabulary is meant to fill a niche that helps standardize the way web published dataset usage be conveyed and shared. At this time is no clear standard way to describe dataset usage on the Web. Without a means to systematically describe dataset usage, searching and conveying techniques are application specific and discovery and collaboration across the Web is more difficult. This vocabulary also recommends and requires data publishers to provide a mechanism of receiving data usage from data consumers in the form of feedback,citation and data correction.
The namespace for DCAT is
However, it should be noted that DCAT makes extensive use of terms from
other vocabularies, in particular Dublin
Core. DCAT itself defines a minimal set of classes and properties
of its own. A full set of namespaces and prefixes used in this document
is shown in the table below.
The DUV is intended for data producers and publishers interested in tracking, sharing, and persisting consumer dataset usage. It is also intended for collaborators who require an exchange medium to advertise and interactively convey dataset usage.
The scope of DUV is defined by the Data on the Web Best Practices (DWBP) Use Case document based on the data usage requirements about datasets. These requirements include: citing data on the Web, tracking the usage of data, sharing feedback and rating data. These requirements were derived from fourteen real world use cases examples provided in the use case document.
The DUV is a “glue” vocabulary reusing and extending existing vocabulary classes and properties to support citation, feedback, and usage. This section provides our rationale and approach for vocabulary selection and re-use.
Core to the dataset usage vocabulary is the “dataset”. The DUV uses the Data Catalog (DCAT) vocabulary dcat:Dataset class and all properties associated with the class. From a data usage perspective the DUV can be considered an extension of the dcat:Dataset.
The Web Annotation Vocabulary is used to describe duv:Feedback as a subclass inheriting the behavior of oa:Annotation. A crucial part of the Web Annotation Model are “motivations” that describe the role of particular Annotation. Each duv:Feedback must have at least one oa:motivated_by property with a relationship to an instance of oa:Motivation. A subset of the Motivation instances are important to describe feedback to data publishers, and blogs between dataset consumers. In addition to supporting duv:Feedback because the Web Annotation vocabulary provides a generic way of annotating any web resource, it is recommended that Web Annotation vocabulary be used to annotate the duv:Dataset for uses beyond the scope of the DUV.
The Provenance Ontology (Prov-O) is a vocabulary used by data providers to pass details about the data history to data users. Properties associated with prov:Activity provide relationships (prov:used, prov:hasGenerated) from a historical perspective using past tense forms of words and phrases. The developed and duv:WebThing reuses these properties by creating subProperties from Prov-O to describe usage from a present tense perspective.
Both the Citation Typing Ontology (CiTO) and Dublin Core vocabularies are used to describe citations and references between datasets and cited sources.
This section shows some examples to illustrate the application of the Dataset Usage Vocabulary.
Example 1 - Usage: A 2-D plot application developed by Laufer can be used to create temperature plots and consumes temperature readings from a dataset to produce the plot. A data logger used to provide temperature readings uses a configuration file for operation of the data logger.
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix dct: <http://purl.org/dc/terms/> . @prefix duv: <http://www.w3.org/ns/duv#> . @prefix : <http://example.org#> . :laufer a foaf:Agent, foaf:Person; foaf:givenName "Laufer"; foaf:mbox <mailto:email@example.com> duv:develops :xyplotter; . :xyplotter a duv:Application; rdfs:label "2dplotter" ; duv:consumes :dataset-03312004 duv:developedBy :laufer ; . :insitu-measurement-data-logger a duv:WebThing; rdfs:label "surface meteorology data logger" ; duv:consumes :configfile ; . :configfile-csv a dcat:Distribution; . :configfile a dcat:Dataset ; dct:title "configuration settings" ; dcat:distribution :configfile-csv ; . :dataset-Jan-Mar-2004-csv a dcat:Distribution; . :dataset-03312004 a dcat:Dataset; dct:title "Mars Quarterly Temperature Plot"; dcat:distribution :dataset-Jan-Mar-2004-csv; .
Example 2 - Feedback: Laufer provides feedback about the temperature readings dataset.
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix dct: <http://purl.org/dc/terms#> . @prefix oa: <http://www.w3.org/ns/oa#> . @prefix duv: <http://www.w3.org/ns/duv#> . @prefix : <http://example.org#> . :laufer a duv:Person ; foaf:givenName "Laufer" ; foaf:mbox <mailto:firstname.lastname@example.org> ; . :dataset-03312004 a dcat:Dataset ; dct:title "Mars Quarterly Temperature Plot" ; . :comment1 a duv:Feedback ; oa:hasBody "Written in MS-DOS text format." ; oa:hasTarget :dataset-03312004 ; oa:annotatedBy :laufer ; . :comment2 a duv:Feedback; duv:hasRating "3 Star"; oa:hasBody "Linked Data Rating"; oa:hasTarget :dataset-03312004; .
Example 3 - Citation: A technical report :paperA identified by a DOI cites the dataset. The :dataset-03312013 is also identified by a digital object identifier (DOI).
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix dct: <http://purl.org/dc/terms#> . @prefix oa: <http://www.w3.org/ns/oa#> . @prefix cito: <http://purl.org/spar/cito#> . @prefix duv: <http://www.w3.org/ns/duv#> . @prefix : <http://example.org#> . :dataset-03312013 a dcat:Dataset; dc:identifier "doi:10.1038/ex2158"; dct:title "Mars Quarterly Temperature Plot"@en ; dct:alternative "Qtrly Temp Plot"@en; dct:description "This plot features average surface temperatures measured by the Mars Land Rover. "@en ; dct:created "2013-03-31T15:18:00Z"^^xsd:dateTime ; dct:creator "Laufer" ; dct:license <http://creativecommons.org/licenses/by-sa/3.0/> ; dcat:keyword "Mars"; dct:language <http://www.lexvo.org/page/iso639-3/eng> ; cito:isCitedAsDataSourceBy :paperA ; . :thisCitation a duv:Citation; cito:hasCitingEntity :dataset-03312004; cito:hasCitedEntity :paperA; . :paperA a foaf:document dc:identifier "doi:20.1055/ex7758"; dct:title "Mars Weather Technical Report"@en; duv:cites :dataset-03312004; .
This section is non-normative.
This section depicts the vocabulary as a conceptual model. Shaded boxes are used to identify each class. Labeled open arrows identify example properties between the classes. Unlabeled shaded arrows are used to show inheritance with the parent class identified by the arrow head.
The classes duv:Application, duv:WebThing, and prov:Activity are used to convey dataset usage. The classes duv:Citation, bibo:Document, cito:CitationAct are used to represent citation. The classes duv:Feedback, oa:Annotation, duv:Rating are used to represent feedback.
|Definition||An agent (eg. person, group, software or physical artifact).|
|Definition||Information about a web resource or associations between resources.|
|Definition||A name given to the Annotation|
|Definition||A free-text description of the Annotaion|
|Definition||Software that is capable of reading and processing a corresponding dataset.|
|Definition||A name given to the Application|
|Definition||A free-text description of the Application|
|Definition||Describes the agent associated with the development of an application|
|Definition||A dataset being consumed by an application.|
|Definition||Usage experience associated with the dataset being generated.|
|Definition||A collection of data, published or curated by a single source, and available for access or download in one or more formats.|
|Definition||A name given to the Dataset|
|Definition||A free-text account of the Dataset|
|Definition||The Document class represents those things which are, broadly conceived, 'documents'.|
|Definition||A name given to the Document|
|Definition||A free-text account of the Document|
|Definition||The citing entity cites the cited entity, either directly and explicitly (as in the reference list of a journal article), indirectly (e.g. by citing a more recent paper by the same group on the same topic), or implicitly (e.g. as in artistic quotations or parodies, or in cases of plagiarism).|
|Definition||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, or generating entities.|
|Definition||Metric used to evaluate the dataset.|
|Definition||Citation in document that references dataset.|
|Definition||The citation act relates to the entity containing that citation.|
|Label||has citing entity|
|Definition||Feedback on the dataset. Expresses whether the dataset was useful or not, for example.|
|Definition||Agent provided feedback providing endorsement of dataset.|
|Definition||Feedback resource that identifies the agent responsible for creating the Annotation.|
|Definition||A feedback annotation may refer to another feedback annotation.|
|Definition||An optional rating provided as part of feedback.|
|Definition||An optional data correction provided as part of feedback.|
|Definition||A dataset correction suggested by user as part of a feedback.|
|Definition||A Web of Things (WoT) device, sensor, or hardware on the Web that consumes a dataset.|
This section shows some of the requirements that motivated the development of the Dataset Usage Vocabulary. These requirements were derived from the use cases described in Data on the Web Best Practices Use Cases & Requirements document.
It should be possible to track the usage of data.
Capability of tracking data usage can help enhancing reputation of the datasets. Records of data usage shows all the successful outcome of the data usage and all the entities associated with it such as the person, organisation, application, research projects that has used these datasets. It increases trust in the data. It also provides provence about how data versions over the time.
|Use Case||R-TrackDataUsage Benefits|
Airborne Snow Observatory
is used in decision making process by Water Reservoir Managers.
Capability to track usage of data will lead to identification of
all the decisions and policy changes made by authorities based
on this data. It will also list applications, tools and
frameworks suitable for analysis of this kind of data.
||Data is used in Research; Policy Making, Journalism; Development; Investments; Governance; Food security; Poverty; Gender issues. Usage tracking will help in assessing the impact of published data.|
is put in public for reuse and reference in nature conservation
activities. Information about use of this data will
determined impact of this framework. Usage of this data MUST lead
to future publications of less heterogenous data and more and more
used of standardised thesauri.
Open Experimental Field Studies
is used in computational models and studies. Capabilities to
track usage of data will enable data publishers to identify all
the users communities making use of this data. It will also
identify combined use of multiple datasets in one big study.
This will identify related datasets which can be recommended to
is published in Linked Data Format for discovery and
recommendations of related datasets. Capability to keep track of
its usage will list all the tools and application suitable to be
used with this data. Because RDESC is not data publisher but
more of a data facilitator, usage tracking will identify highly
search dataset and the trends in the temporal, spatial and
domain specific search queries.
is published with intelligent
openness to support research projects. Capability to track data
usage will provide adequate acknowledgement to data originator.
Data consumers should have a way of sharing feedback and rating data.
User feedback is important to address data quality concerns about published dataset. Different users may have different experience with the same dataset so it is important to capture the context in which data was used and the profile of the user who uses it. R-UsageFeedback should also provide a way to communicate suggested corrections and update to the datasets by the users back to data publisher. Data publishers should have a review mechanism to incorporate submitted corrections.
|Use Case||R-UsageFeedback Benefits|
Airborne Snow Observatory
grows rapidly each year. User feedback can reports issues of
data completeness and correctness.
came from various publishers. As a catalog, the site has faced
several challenges, one of them was to integrate the various
technologies and formulas used by publishers to provide datasets
in the portal. User feedback can provided usabilities of those
technologies and formulas. User feedback can be used to
crowdsource discrepancies in the vocabularies used to
multilingualism is one of the challenge for this use case. User
feedback can be used to crowdsource multilingual text alignment.
is used in computational models and studies. User feedback can
be used to identify good quality data required for good quality
research. completeness, time resolution and usability can be
captured using user feedback.>
curate different data source and publish metadata in Linked Data
Format. User feedback is useful to assess metadata quality.
Availability of the source datasets, Correctness of persistent
URI, Correctness of the concepts defined in RDESC such as FOAF
Agents, Organizations, Physical Properties and Usability of the
search interface can be captured in user feedback.
It should be possible to cite data on the Web.
|Use Case||R-Citable Benefits|
Open Experimental Field Studies
experiments and fields studies are performed to generate data
which is used in computational
models and bigger studies.Capability
to capture all the citations of the published data can justify
the efforts used in publishing. Citation information can be used
to identify all the user communities interested in data source.
||On 27 March 2014, the LA Times published a story Women earn 83 cents for every $1 men earn in L.A. city government. It was based on an Infographic released by LA's City Controller, Ron Galperin. This report could only cite data portal of all the resource. It could not cite to exact dataset because tool long URI.|
is a data curator so it uses data from different sources. But
this usage is not communicated to data publishers because of
lack of such mechanism provided by publishers.