Exploiting Semantic Annotation of Content with Linked Open Data (LoD) to Improve Searching Performance in Web Repositories of Multi-disciplinary Research Data

Searching for relevant information in web repositories of multi-disciplinary scientific
research data is becoming a challenge for research communities such as the Social
Sciences. Researchers use the available keywords-based online search which often fall
short of producing the desired search results due to known issues of content
heterogeneity, volume of data and terminological obsolescence. This leads to a number of
problems including insufficient content exposure, unsatisfied researchers and lack of trust
in such repositories of valuable knowledge.
This research explores the appropriateness of alternative searching based on Linked Open
Data (LoD)-based semantic annotation and indexing in online repositories such as the
ReStore repository (www.restore.ac.uk) containing content from multiple Social Science
research methods projects . We explore websites content annotations using LoD to
generate contemporary semantic annotations. We investigate whether we can improve
accuracy and relevance in search results affected by concepts and terms obsolescence in
repositories of scientific content.