Walking into the Future with PROV Pingback: An Application to OPeNDAP Using Prizms

Lebo, Timothy; West, Patrick; McGuinness, Deborah L.

doi:10.1007/978-3-319-16462-5_3

Cited by 26 publications

(39 citation statements)

References 7 publications

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“…The major influences on this work have been Dodds and Davis' catalogue of design patterns [6], especially the modelling patterns section, the W3C PROV ontology [7] and Open Annotation [8]. In terms of ontology engineering process, the many works of Gómez-Pérez, e.g.…”

Section: Related Workmentioning

confidence: 99%

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Building the Seshat Ontology for a Global History Databank

Brennan

Feeney

Mendel-Gleason

et al. 2016

The Semantic Web. Latest Advances and New Domains

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Abstract. This paper describes OWL ontology re-engineering from the wikibased social science codebook (thesaurus) developed by the Seshat: Global History Databank. The ontology describes human history as a set of over 1500 time series variables and supports variable uncertainty, temporal scoping, annotations and bibliographic references. The ontology was developed to transition from traditional social science data collection and storage techniques to an RDF-based approach. RDF supports automated generation of high usability data entry and validation tools, data quality management, incorporation of facts from the web of data and management of the data curation lifecycle.This ontology re-engineering exercise identified several pitfalls in modelling social science codebooks with semantic web technologies; provided insights into the practical application of OWL to complex, real-world modelling challenges; and has enabled the construction of new, RDF-based tools to support the large-scale Seshat data curation effort. The Seshat ontology is an exemplar of a set of ontology design patterns for modelling unncertainty or temporal bounds in standard RDF. Thus the paper provides guidance for deploying RDF in the social sciences. Within Seshat, OWL-based data quality management will assure the data is suitable for statistical analysis. Publication of Seshat as highquality, linked open data will enable other researchers to build on it.

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Section: Related Workmentioning

confidence: 99%

“…In this section we introduce the Seshat ontology 7 , describe the development process and describe the key design patterns deployed in the ontology.…”

mentioning

confidence: 99%

Building the Seshat Ontology for a Global History Databank

Brennan

Feeney

Mendel-Gleason

et al. 2016

The Semantic Web. Latest Advances and New Domains

View full text Add to dashboard Cite

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“…This metadata is taken from the W3C recommended provenance ontology [31] that is used to express the origin of resources, including classes.…”

Section: W3c Recommended Rdf Schema Inferencementioning

confidence: 99%

“…Instead the intended meaning is clearly that bpo:has event has one domain that is the union of the three types. Elsewhere, for example the provenance ontology [31], the above interpretation is made explicit by using owl:unionOf frequently for the domain and range triples, for example property prov:wasInfluencedBy has the following range:…”

Section: Note On Recommendations For Multiple Domain and Range Propermentioning

confidence: 99%

A descriptive type foundation for RDF Schema

Ciobanu

Horne

Sassone

2016

Journal of Logical and Algebraic Methods in Programming

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This paper provides a type theoretic foundation for descriptive types that appear in Linked Data. Linked Data is data published on the Web according to principles and standards supported by the W3C. Such Linked Data is inherently messy: this is due to the fact that instead of being assigned a strict a priori schema, the schema is inferred a posteriori. Moreover, such a posteriori schema consists of opaque names that guide programmers, without prescribing structure. We employ what we call a descriptive type system for Linked Data. This descriptive type system differs from a traditional type system in that it provides hints or warnings rather than errors and evolves to describe the data while Linked Data is discovered at runtime. We explain how our descriptive type system allows RDF Schema inference mechanisms to be tightly coupled with domain specific scripting languages for Linked Data, enabling an interactive feedback to Web developers.

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“…The Provenance Ontology (PROV) (Lebo et al, 2013) (The W3C SPARQL Working Group, 2013)). This then enables the retrieval and reuse of FAIR data to 78 encourage reproducible science.…”

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confidence: 99%

The health care and life sciences community profile for dataset descriptions

Dumontier

Gray

Marshall

et al. 2017

Preprint

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Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization.This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization. This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets.

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Walking into the Future with PROV Pingback: An Application to OPeNDAP Using Prizms

Cited by 26 publications

References 7 publications

Building the Seshat Ontology for a Global History Databank

Building the Seshat Ontology for a Global History Databank

A descriptive type foundation for RDF Schema

The health care and life sciences community profile for dataset descriptions

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