TY - JOUR
T1 - Classifying the LOD Cloud
T2 - Digging into the Knowledge Graph
AU - Ávila, Daniel Martínez
AU - Smiraglia, Richard P.
AU - Szostak, Rick
AU - Scharnhorst, A.M.
AU - Beek, Wouter
AU - Siebes, Ronald
AU - Ridenour, Laura
AU - Schlais, Vanessa
PY - 2018
Y1 - 2018
N2 - Massive amounts of data from different contexts and produc-ers are collected and connected relying often solely on statis-tical techniques. Problems to the acclaimed value of data lie in the precise definition of data and associated contexts as well as the problem that data are not always published in meaningful and open ways. The Linked Data paradigm offers a solution to the limitations of simple keywords by having unique, resolvable and shared identifiers instead of strings This paper reports on a three-year research project “Digging Into the Knowledge Graph,” funded as part of the 2016 Round Four Digging Into Data Challenge (https://diggingintodata.org/awards/2016/project/digging-knowledge-graph). Our project involves comparing terminol-ogy employed within the LOD cloud with terminology em-ployed within two general but different KOSs – Universal Decimal Classification and Basic Concepts Classification. We are exploring whether these classifications can encourage greater consistency in LOD terminology and linking the largely distinct scholarly literatures that address LOD and KOSs. Our project is an attempt to connect the Linked Open Data community, which has tended to be centered in comput-er science, and the KO community, with members from lin-guistics, metaphysics, library and information science. We focus on the shared challenges related to Big Data between both communitie
AB - Massive amounts of data from different contexts and produc-ers are collected and connected relying often solely on statis-tical techniques. Problems to the acclaimed value of data lie in the precise definition of data and associated contexts as well as the problem that data are not always published in meaningful and open ways. The Linked Data paradigm offers a solution to the limitations of simple keywords by having unique, resolvable and shared identifiers instead of strings This paper reports on a three-year research project “Digging Into the Knowledge Graph,” funded as part of the 2016 Round Four Digging Into Data Challenge (https://diggingintodata.org/awards/2016/project/digging-knowledge-graph). Our project involves comparing terminol-ogy employed within the LOD cloud with terminology em-ployed within two general but different KOSs – Universal Decimal Classification and Basic Concepts Classification. We are exploring whether these classifications can encourage greater consistency in LOD terminology and linking the largely distinct scholarly literatures that address LOD and KOSs. Our project is an attempt to connect the Linked Open Data community, which has tended to be centered in comput-er science, and the KO community, with members from lin-guistics, metaphysics, library and information science. We focus on the shared challenges related to Big Data between both communitie
KW - Linked Open Data; Knowledge Organisation Systems; Big Data; Knowledge Graph
M3 - Article
VL - 12
SP - 6
EP - 10
JO - BRAJIS - Brazilian Journal of Information Science: research trends
JF - BRAJIS - Brazilian Journal of Information Science: research trends
SN - 1981-1640
IS - 4
ER -