Nomenclature for data publications and citations

The meaning of the word “dataset” is ambiguous, changing with context.  In FaBiO , the FRBR-aligned bibliographic ontology, we define “dataset” at the conceptual level (i.e. as a frbr:Work) thus:

fabio:Dataset: “A collection of related facts, often expressed in numerical form and encoded in a defined structure.”

In situations demanding precision in terminology, such as data repository metadata and data citation, I think it is wiser to avoid the use of the term “dataset”, and instead to use the terms “data file” and “data package“, as the entities that data repositories handle and to which identifiers pertain.

In FaBiO, a data file is defined as follows:

fabio:DataFile: “A realisation of a fabio:Dataset (a frbr:Work) containing a defined collection of data with specific content and possibly with a specific version number, that can be embodied as a fabio:Digital Manifestation (a frbr:Manifestation with a specific format) and represented by a specific fabio:ComputerFile (a frbr:Item) on someone’s hard drive.”

FaBiO also has the class

fabio:MetadataDocument “A document that contains metadata information describing one or more characteristics of an entity”, which is a realization of fabio:Metadata
“A separate work that provides information describing one or more characteristics of a resource or entity”.

Using ORE, a data package containing data files and a metadata manifest can be defined as type of ore:Aggregation.  However, ORE is not sufficiently expressive to meet the need of repositories who may wish to refer specifically to data packages, to manifests and to the landing pages displaying metadata relating to data packages and individual data files in their RDF metadata. For this reason, we have developed two tiny new ontologies, DaPO, the Data Package Ontology, and LaPO, the Landing Page Ontology, that provide the missing nomenclature, as will be detailed in a future blog post.

Cite this article as: davidshotton, "Nomenclature for data publications and citations," in OpenCitations blog, 30/06/2011,

DataCite2RDF – Mapping DataCite Metadata Scheme Terms to ontologies

The DataCite Metadata Kernel version 2.0 [1] specifies the minimal metadata, and optional metadata, that should accompany a DataCite DOI for the identification of a published data entity. Within the Metadata Kernel document there is an XML mapping of these metadata terms, using DCMI Metadata Terms, and an example encoded in XML.

Silvio Peroni and I recently published a mapping of the DataCite metadata elements to RDF using ontology terms [2], in order to enable data repositories to publish DataCite metadata in RDF as Open Linked Data, enabling these metadata to be understood programmatically and integrated automatically with similar data from elsewhere.

Our mapping covers all the main terms, and the Relation Type sub-properties that describe the relationship of the related resource to the resource being registered, but does not address DataCite sub-terms, e.g. 2.2.1 nameIdentifierScheme.

Wherever possible, commonly used Dublin Core Elements, DCMI (Dublin Core Metadata Initiative) Metadata Terms, FOAF (Friend of a Friend Vocabulary) and PRISM (Publishing Requirements for Industry Standard Metadata) terms have been used.

These have been supplemented, as appropriate, by terms:

from FRBR (Functional Requirements for Bibliographic Records),

from the following SPAR (Semantic Publishing and Referencing) Ontologies:

                CiTO, Citation Typing Ontology

                FaBiO, FRBR-aligned Bibliographic Ontology, and

CiTO4Data, an extension of CiTO for datasets that provides the properties cito4data:compiles and cito4data:isCompiledBy that the DataCite Metadata Kernel requires;

and from a new DataCite Ontology ( that we created to provide the following four object properties lacking in other Ontologies:





Use of DCMI Metadata Terms in RDF

An object property has a class or a URI as its object, while a data property has a literal (e.g. text, number, date) as its object, and may have a W3C XML Schema Definition Language (XSD) datatype qualifier, e.g. ^^xsd:date. (See

Many Dublin Core properties are not formally specified to be one or another, leading to potential confusion. In the following mapping, Dublin Core Elements are always used as data properties, while Dublin Core Metadata Initiative Metadata Terms are used either as data properties or as object properties, as helpfully specified by the Max Planck Digital Library in their document entitled How to use DCMI Metadata as linked data.  

In our DataCite2RDF mapping document [2], alternative mappings are given where appropriate, separated by semi-colons.  Both dc: and dcterms: properties are listed.  Preferred terms are shown bold.  RDF statements are given in Turtle notation.

Accompanying this DataCite2RDF mapping document, we published as Google docs both an RDF mapping of the DataCite XML example, and an RDF mapping of the metadata for a Dryad repository holding, showing how DataCite2RDF can be used for real data.

We welcome feedback on these documents: <> and <>.

[1]    The DataCite Metadata Kernel version 2.0 (2011).

[2]     David Shotton and Silvio Peroni (2011). Mapping DataCite Metadata Scheme Terms (v2.0) to ontologies (DataCite2RDF). Google docs.

Cite this article as: davidshotton, "DataCite2RDF – Mapping DataCite Metadata Scheme Terms to ontologies," in OpenCitations blog, 30/06/2011,


Using FaBiO to describe data entities

In addition to using CiTO and CiTO4Data to describe relationships of relevance to data entities, as discussed in the previous blog post, FaBiO, the FRBR aligned Bibliographic Ontology described elsewhere, another member of the suite of SPAR (Semantic Publishing and Referencing) Ontologies, also has a number of classes and properties specifically designed for addressing data, software, metadata and other non-bibliographic entities. The purpose of this short post is simply to list these in one place.

Sub-classes of fabio:Work

fabio:ControlledVocabulary, sub-class of fabio:Vocabulary, with sub-classes






fabio:Image, with sub-classes



fabio:Metadata, with sub-classes







fabio:Specification, with sub-classes



                    fabio:Workflow among others


Sub-classes of fabio:Expression



fabio:DataBase, with sub-classes


                    fabio:Triplestore among others




fabio:Movie, with sub-class


fabio:Repository, with sub-classes







fabio:VocabularyDocument, with sub-class


Sub-classes of fabio:Manifestation


Sub-classes of fabio:Item

fabio:DigitalItem, with sub-class


Object properties

fabio:stores, and its inverse         fabio:isStoredOn

Data properties





Cite this article as: davidshotton, "Using FaBiO to describe data entities," in OpenCitations blog, 30/06/2011,

CiTO4Data – a new data-centric citation typing ontology

This is the first of a series of blog posts on the Open Citations blog that address the problem of citing data entities, for example a data package in a data repository, rather than bibliographic entities such as journal articles. For these purposes, the existence of DataCite to assign DOIs to datasets, and extensions to the SPAR (Semantic Publishing and Referencing) Ontologies to handle data items, are both important. This post addresses the second of these two issues.

As described in the previous blog post, CiTO, the Citation Typing Ontology, focuses on providing ontological properties to characterize citations of bibliographic entities. However, several of its relationships can also be used in relation to data entities:

Sub-classes of cito:cites







When attempting to map the DataCite metadata elements to ontology terms, to be described in a subsequent blog post, we encountered the DataCite requirement for the properties compiles and isCompiledBy, which are absent from CiTO and other ontologies that we know about and which cannot be conceived as relating to bibliographic entities.

Conscious of a growing need to specify metadata for data entities as well as bibliographic entities, and reluctant to include in CiTO relationships that cannot be applied to bibliographic entities, Silvio Peroni and I have thus created CiTO4Data, a new ontology within the SPAR ontology suite, to be found at

CiTO4Data, the Citation Typing Ontology for Data, is an extension ontology written in OWL 2 DL that imports CiTO, the Citation Typing Ontology, and adds extra object properties that are relevant only for datasets, computer programs and other similar digital objects, but not for conventional bibliographic entities.

To date, CiTO4Data adds just a single new object property


and its inverse


created to meet the need of encoding the DataCite Metadata Kernel v2.0 into RDF. We intend to expand CiTO4Data to include other properties relevant only for citing data entities, as the need arises.

NOTE: In the summer of 2012, we decided for simplicity to include these two properties within CiTO itself (as cito:compiles and cito:isCompiledBy), and to deprecate the CiTO4Data ontology.

Cite this article as: davidshotton, "CiTO4Data – a new data-centric citation typing ontology," in OpenCitations blog, 30/06/2011,
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