Inproceedings,

FAIR Linked Data - Towards a Linked Data Backbone for Users and Machines

, and .
Companion of The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021, page 431--435. ACM / IW3C2, (2021)
DOI: 10.1145/3442442.3451364

Abstract

Although many FAIR principles could be fulfilled by 5-star LinkedOpen Data, the successful realization of FAIR poses a multitudeof challenges. FAIR publishing and retrieval of Linked Data is stillrather a FAIRytale than reality, for users and machines. In thispaper, we give an overview on four major approaches that tackleindividual challenges of FAIR data and present our vision of a FAIRLinked Data backbone. We propose 1) DBpedia Databus - a flex-ible, heavily automatizable dataset management and publishingplatform based on DataID metadata; that is extended by 2) thenovel Databus Mods architecture which allows for flexible, uni-fied, community-specific metadata extensions and (search) overlaysystems; 3) DBpedia Archivo an archiving solution for unified han-dling and improvement of FAIRness for ontologies on publisher andconsumer side; as well as 4) the DBpedia Global ID managementand lookup services to cluster and discover equivalent entities andproperties.

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