The Canadian Linked Data Initiative: Charting a Path to a Linked Data Future

Ballegooie, Marlene van; Borie, Juliya; Senior, Andrew

doi:10.1080/0361526x.2017.1292751

Cited by 7 publications

(6 citation statements)

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“…The Canadian Linked Data Initiative (CLDI) was formed to leverage the existing collaboration between the technical services departments of Canada's top five research libraries. 7 CLDI investigated a variety of areas such as grant application, education and training, identifiers, digital projects, BIB-FRAME Editor, etc. through different working groups.…”

Section: Notes On Operationsmentioning

confidence: 99%

“…through different working groups. 8 The cross institutional collaboration allowed the staff members to cover more ground in a coordinated manner and share skill sets and documentation, thus strengthening the existing relationships while forging new ones. 9 One of CLDI's future goals is to build a culture of learning and experimentation within the organizations, allowing the group to move forward both individually and collectively.…”

Section: Notes On Operationsmentioning

confidence: 99%

“…8 The cross institutional collaboration allowed the staff members to cover more ground in a coordinated manner and share skill sets and documentation, thus strengthening the existing relationships while forging new ones. 9 One of CLDI's future goals is to build a culture of learning and experimentation within the organizations, allowing the group to move forward both individually and collectively. 10 In an International Linked Data Survey for Implementers conducted by OCLC Research in 2014, 2015, and 2018 respectively, 143 institutions from twenty-three countries responded to the surveys and reported on their Linked Data projects.…”

Section: Notes On Operationsmentioning

confidence: 99%

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Collaborative Learning on Linked Data through a Virtual Study Group

Liu¹,

Reidt²,

Pappas³

et al. 2023

LRTS

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This paper examines the challenges and successes of a virtual Linked Data Study Group that began at a multi-campus academic institution in 2018, and later grew to include a total of seven librarians from multiple institutions across the country. It describes the group’s planning for their monthly meetings and the discussions at the meetings which covered such topics as Linked Data basic concepts, BIBFRAME Editor, Sinopia Editor, and Wikidata. It also presents a collaborative project the group undertook after two years’ learning. The paper concludes with a summary of what the Linked Data Study Group has achieved thus far, the challenges they faced, and their future plans.

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Section: Notes On Operationsmentioning

confidence: 99%

Section: Notes On Operationsmentioning

confidence: 99%

Section: Notes On Operationsmentioning

confidence: 99%

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Collaborative Learning on Linked Data through a Virtual Study Group

Liu¹,

Reidt²,

Pappas³

et al. 2023

LRTS

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“…In this context, the University of Illinois at Champaign-Urbana Library and OCLC experimented on CONTENTdm collections metadata [143]. Van Ballegooie et al [144] reported on the work of the Canadian Linked Data Initiative (CLDI), a collaboration between five of Canada's largest research libraries, Library and Archives Canada, Bibliothe `que et Archives nationals du Que ´bec and Canadiana.org. Smith-Yoshimura [145] provided an overview of 112 linked data projects or services institutions or organisations that had implemented linked data and discussed the limits and barriers encountered.…”

Section: Linked Data Implementation In the Cultural Heritage Domainmentioning

confidence: 99%

Linked data for libraries: Creating a global knowledge space, a systematic literature review

Gaitanou

Andreou

Sicilia

et al. 2022

Journal of Information Science

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The Semantic Web in general and the Linked Open Data Initiative, in particular, are a growing movement for organisations to make their existing data available in a machine-readable format. Thus, institutions are highly encouraged to publish, share and interlink their data publicly. The more data are opened on the Web (Open Data), the more integrated sets of data will be connected in the Semantic Web (Linked Open Data). Within this context, libraries can complement their data by linking it to other, external data sources. The purpose of this article is to identify papers that refer to linked data in libraries, emphasising the ways that linked data empower libraries to put their knowledge in the context of the open-world, thus enhancing semantic technology innovations. The study considered papers published between 2008 and 2019 in English and presents the collected literature by grouping it according to the topic each paper refers to. The results show that libraries are facing a period of continuing change which present several challenges and indicate that they are moving towards developing new practices, policies and services.

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“…; Margan et al,1 http://www.oeg-upm.net/index.php/es/linkeddata/73geolinkeddata/index.html 2 http://data.ordnancesurvey.co.uk/datasets/os-linked-data 2018;Wiemann and Bernard 2016;Ballegooie et al, 2017; Ding et al, 2009. Kohlo et al, implemented linking historical data to the external related datasets.…”

mentioning

confidence: 99%

Semantic Linking Spatial RDF Data to the Web Data Sources

Karakol¹,

Kara²,

Yılmaz³

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Large amounts of spatial data are hold in relational databases. Spatial data in the relational databases must be converted to RDF for semantic web applications. Spatial data is an important key factor for creating spatial RDF data. Linked Data is the most preferred way by users to publish and share data in the relational databases on the Web. In order to define the semantics of the data, links are provided to vocabularies (ontologies or other external web resources) that are common conceptualizations for a domain. Linking data of resource vocabulary with globally published concepts of domain resources combines different data sources and datasets, makes data more understandable, discoverable and usable, improves data interoperability and integration, provides automatic reasoning and prevents data duplication. The need to convert relational data to RDF is coming in sight due to semantic expressiveness of Semantic Web Technologies. One of the important key factors of Semantic Web is ontologies. Ontology means “explicit specification of a conceptualization”. The semantics of spatial data relies on ontologies. Linking of spatial data from relational databases to the web data sources is not an easy task for sharing machine-readable interlinked data on the Web. Tim Berners-Lee, the inventor of the World Wide Web and the advocate of Semantic Web and Linked Data, layed down the Linked Data design principles. Based on these rules, firstly, spatial data in the relational databases must be converted to RDF with the use of supporting tools. Secondly, spatial RDF data must be linked to upper level-domain ontologies and related web data sources. Thirdly, external data sources (ontologies and web data sources) must be determined and spatial RDF data must be linked related data sources. Finally, spatial linked data must be published on the web. The main contribution of this study is to determine requirements for finding RDF links and put forward the deficiencies for creating or publishing linked spatial data. To achieve this objective, this study researches existing approaches, conversion tools and web data sources for relational data conversion to the spatial RDF. In this paper, we have investigated current state of spatial RDF data, standards, open source platforms (particularly D2RQ, Geometry2RDF, TripleGeo, GeoTriples, Ontop, etc.) and the Web Data Sources. Moreover, the process of spatial data conversion to the RDF and how to link it to the web data sources is described. The implementation of linking spatial RDF data to the web data sources is demonstrated with an example use case. Road data has been linked to the one of the related popular web data sources, DBPedia. SILK, a tool for discovering relationships between data items within different Linked Data sources, is used as a link discovery framework. Also, we evaluated other link discovery tools e.g. LIMES, Silk and results are compared to carry out matching/linking task. As a result, linked road data is shared and represented as an information resource on the web and enriched with definitions of related different resources. By this way, road datasets are also linked by the related classes, individuals, spatial relations and properties they cover such as, construction date, road length, coordinates, etc.</p>

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The Canadian Linked Data Initiative: Charting a Path to a Linked Data Future

Cited by 7 publications

References 0 publications

Collaborative Learning on Linked Data through a Virtual Study Group

Collaborative Learning on Linked Data through a Virtual Study Group

Linked data for libraries: Creating a global knowledge space, a systematic literature review

Semantic Linking Spatial RDF Data to the Web Data Sources

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