Five stars of Linked Data vocabulary use

Janowicz, Krzysztof; Hitzler, Pascal; Adams, Benjamin; Kolas, Dave; Vardeman, Charles

doi:10.3233/sw-140135

Cited by 87 publications

(66 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At the system level, the SNDM and SNDB work as two separate worlds and due to these drawbacks we propose improving the interoperability with the use of Linked Data (LD) (Janowicz et al, 2014).…”

Section: Cross-disciplinary Research Cruisesmentioning

confidence: 99%

Data Interoperability Between Elements of the Global Ocean Observing System

et al. 2019

View full text Add to dashboard Cite

The data management landscape associated with the Global Ocean Observing System is distributed, complex, and only loosely coordinated. Yet interoperability across this distributed landscape is essential to enable data to be reused, preserved, and integrated and to minimize costs in the process. A building block for a distributed system in which component systems can exchange and understand information is standardization of data formats, distribution protocols, and metadata. By reviewing several data management use cases we attempt to characterize the current state of ocean data interoperability and make suggestions for continued evolution of the interoperability standards underpinning the data system. We reaffirm the technical data standard recommendations from previous OceanObs conferences and suggest incremental improvements to them that can help the GOOS data system address the significant challenges that remain in order to develop a truly multidisciplinary data system.

show abstract

Section: Cross-disciplinary Research Cruisesmentioning

confidence: 99%

Data Interoperability Between Elements of the Global Ocean Observing System

et al. 2019

View full text Add to dashboard Cite

show abstract

“…To generate metrics that are in line with recommendations of the FAIR framework, we combine FAIR metrics [3] with the 5-star rating for data [25]/ linked open data [24] as illustrated in Table A1. The decision of the final metric is based on a generalization of FAIR interoperability metrics and data rating concepts.…”

Section: Methodsmentioning

confidence: 99%

“…These include: syntactic, semantic, technical and organizational interoperability. To ensure that data providers publish a machine-readable open data in an interoperable way, Barners-lee [24,25] introduces a five-star rating for data that relates to the levels of interoperability defined by Rezaei et al [23].…”

Section: Disaster Data Interoperabilitymentioning

confidence: 99%

An Empirical Evaluation of Data Interoperability—A Case of the Disaster Management Sector in Uganda

Mazimwe

Hammouda

Gidudu

2019

IJGI

View full text Add to dashboard Cite

One of the grand challenges of disaster management is for stakeholders to be able to discover, access, integrate and analyze task-appropriate disaster data together with their associated algorithms and work-flows. Even with a growing number of initiatives to publish disaster data using open principles, integration and reuse are still difficult due to existing interoperability barriers within datasets. Several frameworks for assessing data interoperability exist but do not generate best practice solutions to existing barriers based on the assessment they use. In this study, we assess disaster data interoperability in Uganda and identify generic solutions to interoperability challenges in the context of disaster data. Semi-structured interviews and focus group discussions were used to collect qualitative data from stakeholders in the disaster sector in Uganda. Data interoperability was measured to provide an understanding of interoperability in the disaster sector. Interoperability maturity is measured using qualitative methods, while data compatibility metrics are computed from identifiers in the RDF-triple model. Results indicate high syntactic and technical interoperability maturity for disaster data. On the contrary, there exists considerable semantic and legal interoperability barriers that hinder disaster data integration and reuse. A mapping of the interoperability challenges in the disaster management sector to solutions reveals a potential to reuse established patterns for managing interoperability. These include; the federated pattern, linked data patterns, broadcast pattern, rights and policy harmonization patterns, dissemination and awareness pattern, ontology design patterns among others. Thus a systematic approach to combining patterns is critical to managing data interoperability barriers among actors in the disaster management ecosystem.

show abstract

“…In the process of development of OpenBiodiv-O [29], several other established ontologies and vocabularies were reused in accordance with the principles advocated by the proponents of the Semantic Web [6,46]. Reusing vocabularies facilitates linking of entities within the OpenBiodiv LOD to entities from external data stores that use these vocabularies.…”

Section: Openbiodiv As a Major Step Towards Fair Data And Open Sciencementioning

confidence: 99%

OpenBiodiv: A Knowledge Graph for Literature-Extracted Linked Open Data in Biodiversity Science

et al. 2019

View full text Add to dashboard Cite

Hundreds of years of biodiversity research have resulted in the accumulation of a substantial pool of communal knowledge; however, most of it is stored in silos isolated from each other, such as published articles or monographs. The need for a system to store and manage collective biodiversity knowledge in a community-agreed and interoperable open format has evolved into the concept of the Open Biodiversity Knowledge Management System (OBKMS). This paper presents OpenBiodiv: An OBKMS that utilizes semantic publishing workflows, text and data mining, common standards, ontology modelling and graph database technologies to establish a robust infrastructure for managing biodiversity knowledge. It is presented as a Linked Open Dataset generated from scientific literature. OpenBiodiv encompasses data extracted from more than 5000 scholarly articles published by Pensoft and many more taxonomic treatments extracted by Plazi from journals of other publishers. The data from both sources are converted to Resource Description Framework (RDF) and integrated in a graph database using the OpenBiodiv-O ontology and an RDF version of the Global Biodiversity Information Facility (GBIF) taxonomic backbone. Through the application of semantic technologies, the project showcases the value of open publishing of Findable, Accessible, Interoperable, Reusable (FAIR) data towards the establishment of open science practices in the biodiversity domain.

show abstract

Five stars of Linked Data vocabulary use

Cited by 87 publications

References 9 publications

Data Interoperability Between Elements of the Global Ocean Observing System

Data Interoperability Between Elements of the Global Ocean Observing System

An Empirical Evaluation of Data Interoperability—A Case of the Disaster Management Sector in Uganda

OpenBiodiv: A Knowledge Graph for Literature-Extracted Linked Open Data in Biodiversity Science

Contact Info

Product

Resources

About