“The WarSampo system 1) initiates and fosters large scale Linked Open Data (LOD) publication of WW2 data from distributed, heterogeneous data silos and 2) demonstrates and suggests its use in applications and DH research. WarSampo is to our best knowledge the first large scale system for serving and publishing WW2 LOD on the Semantic Web for machine and human users. Its knowledge graph metadata contains over 9 million associations (triples) between data items including, e.g., a complete set of over 95,000 death records of Finnish WW2 soldiers, 160,000 authentic photos taken during the war, 32,000 historical places on historical maps, 23,000 war diaries of army units, and 3,400 memoir articles written by the veterans after the war. WarSampo data comes from several Finnish organizations and sources, such as National Archives, Defense Forces, Land Survey of Finland, Wikipedia/DBpedia, text books, and magazines.
WarSampo has two separate components: 1) WarSampo Data Service for machines and 2) WarSampo Semantic Portal with various applications for human users.”
“Linguistic Linked Open Data (LLOD) is a movement about publishing open language resources for different use cases in academic research, applied linguistics or natural language processing. The LLOD cloud comprises lexical-conceptual resources (dictionaries, knowledge bases), corpora, terminology repositories (thesauri, ontologies), and metadata collections (language resource metadata, bibliographies)….”
Abstract: The concept of Linked Data has been an emerging theme within the computing and digital heritage areas in recent years. The growth and scale of Linked Data has underlined the need for greater commonality in concept referencing, to avoid local redefinition and duplication of reference resources. Achieving domain-wide agreement on common vocabularies would be an unreasonable expectation; however, datasets often already have local vocabulary resources defined, and so the prospects for large-scale interoperability can be substantially improved by creating alignment links from these local vocabularies out to common external reference resources. The ARIADNE project is undertaking large-scale integration of archaeology dataset metadata records, to create a cross-searchable research repository resource. Key to enabling this cross search will be the ‘subject’ metadata originating from multiple data providers, containing terms from multiple multilingual controlled vocabularies. This paper discusses various aspects of vocabulary mapping. Experience from the previous SENESCHAL project in the publication of controlled vocabularies as Linked Open Data is discussed, emphasizing the importance of unique URI identifiers for vocabulary concepts. There is a need to align legacy indexing data to the uniquely defined concepts and examples are discussed of SENESCHAL data alignment work. A case study for the ARIADNE project presents work on mapping between vocabularies, based on the Getty Art and Architecture Thesaurus as a central hub and employing an interactive vocabulary mapping tool developed for the project, which generates SKOS mapping relationships in JSON and other formats. The potential use of such vocabulary mappings to assist cross search over archaeological datasets from different countries is illustrated in a pilot experiment. The results demonstrate the enhanced opportunities for interoperability and cross searching that the approach offers.
“We’re happy to announce that the OpenAIRE Linked Open Data (LOD) Services are now available as a beta version at http://beta.lod.openaire.eu/. OpenAIRE already makes its data freely available for re-use via APIs. In line with its commitment to openness, OpenAIRE has been busy mapping OpenAIRE’s data onto suitable standard vocabularies in order to make OpenAIRE’s data available as Linked Open Data. This started with a specification of the OpenAIRE data model as a Resource Description Framework (RDF) vocabulary, and then entailed mapping of the OpenAIRE data to the graph-based RDF data model. To interlink the OpenAIRE data with related data on the Web, we have identified a list of potential datasets with which to interlink, including the DBpedia dataset extracted from Wikipedia and the publication databases DBLP and CiteSeer. Making our data available in this way extends OpenAIRE’s technical interoperability and enables new user communities to engage with our data …”
“The Dakar Declaration on Open Science in Africa was prepared for and signed by the participants to the Sci-GaIA Workshop on “Promoting Open Science in Africa”, to the 2nd TANDEM Workshop and to the WACREN Conference 2016, all held in Dakar in March 2016. After those events, the Sci-GaIA Consortium has decided to put the declaration on the website of the project to allow everybody sharing it to sign it online. The declaration is released under the Creative Commons Attribution ShareAlike 4.0 International License….”