http://hdl.handle.net/10379/384 2017-10-29T23:59:54Z 2017-10-29T23:59:54Z Bordea, Georgeta Buitelaar, Paul http://hdl.handle.net/10379/5862 2016-06-08T08:55:04Z 2016-05-28T00:00:00Z

Semantic representation and enrichment of information retrieval experimental data Bordea, Georgeta; Buitelaar, Paul Experimental evaluation carried out in international large-scale campaigns is a fundamental pillar of the scientific and technological advancement of information retrieval (IR) systems. Such evaluation activities produce a large quantity of scientific and experimental data, which are the foundation for all the subsequent scientific production and development of new systems. In this work, we discuss how to semantically annotate and interlink this data, with the goal of enhancing their interpretation, sharing, and reuse. We discuss the underlying evaluation workflow and propose a resource description framework model for those workflow parts. We use expertise retrieval as a case study to demonstrate the benefits of our semantic representation approach. We employ this model as a means for exposing experimental data as linked open data (LOD) on the Web and as a basis for enriching and automatically connecting this data with expertise topics and expert profiles. In this context, a topic-centric approach for expert search is proposed, addressing the extraction of expertise topics, their semantic grounding with the LOD cloud, and their connection to IR experimental data. Several methods for expert profiling and expert finding are analysed and evaluated. Our results show that it is possible to construct expert profiles starting from automatically extracted expertise topics and that topic-centric approaches outperform state-of-the-art language modelling approaches for expert finding. Journal article

2016-05-28T00:00:00Z Hogan, Aidan Harth, Andreas Polleres, Axel http://hdl.handle.net/10379/4891 2015-10-15T11:42:10Z 2009-01-01T00:00:00Z

Scalable Authoritative OWL Reasoning for the Web Hogan, Aidan; Harth, Andreas; Polleres, Axel

2009-01-01T00:00:00Z Curry, Edward Donnellan, Brian http://hdl.handle.net/10379/4511 2015-10-15T12:50:01Z 2012-01-01T00:00:00Z

Understanding the Maturity of Sustainable ICT Curry, Edward; Donnellan, Brian Sustainable ICT (SICT) can develop solutions that offer benefits both internally in IT and across the extended enterprise. However, because the field is new and evolving, few guidelines and best practices are available. There is a need to improve the SICT behaviours, practices and processes within organizations to deliver greater value from SICT. To address the issue, a consortium of leading organizations from industry, the nonprofits sector, and academia decided to develop a framework for systematically assessing and improving SICT capabilities. The SICT Capability Maturity Framework (SICT-CMF) gives organizations a vital tool to manage their sustainability capability. The framework provides a comprehensive value-based model for organizing, evaluating, planning, and managing SICT capabilities. Using the framework, organizations can assess the maturity of their SICT capability and systematically improve capabilities in a measurable way to meet the sustainability objectives including reducing environmental impacts and increasing profitability. The core of SICT-CMF is a maturity model for SICT which provides a management system with associated improvement roadmaps that guide senior IT and business management in selecting strategies to continuously improve, develop, and manage the sustainable IT capability. This chapter describes the SICT-CMF and the use of it to determine the maturity of sustainable IT capability within a number of leading organisations. The chapter highlights the challenges in managing SICT and motivates the benefit of maturity models. The development process for the SICT-CMF is discussed and the role of Design Science in the development cycle is explored. The application of the resulting model and its use to measure SICT maturity is discussed together with an analysis of the average results for organisations using the model. The chapter concludes with practical insights gained from the assessments. Book chapter

2012-01-01T00:00:00Z Curry, Edward Freitas, Andre O'Ríain, Seán http://hdl.handle.net/10379/4501 2015-10-15T12:50:02Z 2010-01-01T00:00:00Z

The Role of Community-Driven Data Curation for Enterprises Curry, Edward; Freitas, Andre; O'Ríain, Seán With increased utilization of data within their operational and strategic processes, enterprises need to ensure data quality and accuracy. Data curation is a process that can ensure the quality of data and its fitness for use. Traditional approaches to curation are struggling with increased data volumes, and near real-time demands for curated data. In response, curation teams have turned to community crowd-sourcing and semi-automated metadata tools for assistance. This chapter provides an overview of data curation, discusses the business motivations for curating data and investigates the role of community-based data curation, focusing on internal communities and pre-competitive data collaborations. The chapter is supported by case studies from Wikipedia, The New York Times, Thomson Reuters, Protein Data Bank and ChemSpider upon which best practices for both social and technical aspects of community-driven data curation are described. Book chapter

2010-01-01T00:00:00Z