<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/AA3FE75D-597C-48A9-8DD1-A839401C97C3" ns1:id="AA3FE75D-597C-48A9-8DD1-A839401C97C3"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/60387437-E604-43A9-94DD-B5C10DD61939" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/055462AB-ED3B-4F26-9C93-CDD5517D62F7" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/9B3048D9-A436-4E4E-BD21-E1ABAAE6CF2F" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/56179042-26E4-4896-8B01-6DBC865C945B" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/055462AB-ED3B-4F26-9C93-CDD5517D62F7" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2016-12-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/70A8C955-2FF7-4520-B675-64CEF55A0BB2" ns1:rel="FUND" ns1:start="2014-08-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">101941</ns2:identifier></ns2:identifiers><ns2:title>Innovative tools to enable exploration of complex and specialised data sets</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>In the age of Big Data, knowledge workers - individuals, companies and organisations whose primary focus is knowledge and information extraction and usage - find it increasingly difficult to search for and identify accurate and relevant information. In the domain of scientific literature and IP search, where the underlying corpora are growing at a huge rate, this is a daunting task and human expertise and involvement remain critical. This project aims to develop a suite of tools that will enable users to search for and identify relevant information within a corpus more efficiently and effectively. The methods developed will deploy new search paradigms together with semantic-based analysis, domain and lexical linguistic ontologies in order to understand the user needs based on the underlying domain of application and subsequently enable accurate information retrieval through enhanced search and cross-reference of information. The project aims to offer tools for sharing of search strategies which will be identified by observing and understanding patterns in users' search behaviours.</ns2:abstractText></ns2:project>