Thursday, 18 October 2012

#EnviLOD: User Requirements Survey Results Now Published

The British Library and HR Wallingford, as part of our work on #EnviLOD, carried out a user survey, which identified the following potential use cases for vocabularies to be tested in the semantic enrichment and search workpackages:

  1. Returning results for geographically specific queries. Beyond keyword recognition, this use case includes proximity and recognition of geographic entities that are implied, but not stated within the query (for example in a query for flooding in SW England, identifying towns such as Exeter within that region, without it being explicitly articulated in the query).
  2. Answering non-open-ended queries. In this case, the user is asking for a specific piece of information, which might pertain to a budget, specific piece of legislation, flood levels in a particular locality, etc. For example: What is the annual flood defence expenditure in The Netherlands? These are questions that can be definitively answered, and to which semantic search algorithms can likely be easily trained.
  3. Answering open-ended queries. In this case, a user is conducting research with an aim of learning more about a particular topic. In this case, there is no definitive ‘answer’ to the query—the question is answered once the user has established that s/he has sufficient information on the topic. For example: What are some examples of community engagement relating to flood risk management? These questions are likely more difficult for a LOD approach to add value—but nevertheless represent an important type of question asked by survey respondents.

In general, users were found to prefer Google-style keyword searches, or searches in which they could pose a question above other types of searches. The amount of subject specific jargon used in their queries depended on the nature of the question that was asked, as well as the job held by the individual who was asking it. As such, the LOD vocabularies used in this work need to be flexible, enabling generalist queries, while also allowing subject-specific queries, where possible.

For further details, please see this public deliverable.

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