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EnviLOD

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Semantic Enrichment and Search with Linked Open Data: A Case Study on Environmental Science Literature

Overview

From June to December 2012, we're running a small exploratory project funded by JISC to experiment with Linked Open Data ontologies for environmental science. The consortium consists of the University of Sheffield, the British Library, and HR Wallingford.

Follow EnviLOD (through this blog) or on Twitter: @GateAcUk #envilod


Aims of the Project

The overall aim of EnviLOD is to demonstrate the value of using Linked Open Data (LOD) vocabularies in the field of environmental science. Firstly, EnviLOD will tackle the problem of LOD domain vocabulary enrichment and interlinking. Tools for efficient LOD vocabulary lookup and LOD-based term disambiguation will be developed and evaluated, both quantitatively and with users. Secondly, EnviLOD will develop and evaluate intuitive user interface methods that can hide the complexities of the SPARQL semantic search language, while allowing environmental researchers to search successfully, using LOD vocabularies. A new British Library information discovery tool for environmental science, Envia, will be used as a case study to test the use of LOD vocabularies towards enhancing information discovery and management. Environmental consultants at HR Wallingford will collaborate as domain experts, providing feedback on how the semantic work undertaken here supports their work as environmental science practitioners and innovators.

This is a short overview of EnviLOD's progress by mid October 2012.


Planned Outcomes

The key outcomes of this project are:

For further details see this blog post.


Project Partners

The British Library and HR Wallingford are working with us on this project. A complete list of staff involved is available on our blog.


Written Reports and Deliverables

Presentations from the EnviLOD User Workshop (25 January 2013)

Projects Collaborating With/Interested in EnviLOD Results


Useful Links

Our blog posts

Contact us


Project PI: Kalina Bontcheva

This work is supported by JISC