The diversity of datasets published according to Linked Data (LD) principles has increased in the last few years and also led to the emergence of a wide range of data suitable in educational settings. However, sufficient insights into the state, coverage and scope of available educational Linked Data seem to be missing, for instance, about represented resource types or domains and topics. In this work, we analyse the scope and coverage of educational linked data on the Web, identifying the most popular resource types and topics, apparent gaps and underlining the strong correlation of resource types and topics. Our results indicate a prevalent bias to-wards data in areas such as the life sciences as well as computing-related topics.
Towards Analysing the Scope and Coverage of Educational Linked Data on the Web
Davide Taibi;Giovanni Fulantelli;
2015
Abstract
The diversity of datasets published according to Linked Data (LD) principles has increased in the last few years and also led to the emergence of a wide range of data suitable in educational settings. However, sufficient insights into the state, coverage and scope of available educational Linked Data seem to be missing, for instance, about represented resource types or domains and topics. In this work, we analyse the scope and coverage of educational linked data on the Web, identifying the most popular resource types and topics, apparent gaps and underlining the strong correlation of resource types and topics. Our results indicate a prevalent bias to-wards data in areas such as the life sciences as well as computing-related topics.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
