A Framework to Conduct and Report on Empirical User Studies in Semantic Web Contexts

Semantic Web technologies are being applied to increasingly diverse areas where user involvement is crucial. While a number of user interfaces for Semantic Web systems have become available in the past years, their evaluation and reporting often still suffer from weaknesses. Empirical evaluations are essential to compare different approaches, demonstrate their benefits and reveal their drawbacks, and thus to facilitate further adoption of Semantic Web technologies. In this paper, we review empirical user studies of user interfaces, visualizations and interaction techniques recently published at relevant Semantic Web venues, assessing both the user studies themselves and their reporting. We then chart the design space of available methods for user studies in Semantic Web contexts. Finally, we propose a framework for their comprehensive reporting, taking into consideration user expertise, experimental setup, task design, experimental procedures and results analysis.

[1]  Weidong Huang,et al.  Beyond time and error: a cognitive approach to the evaluation of graph drawings , 2008, BELIV '08.

[2]  B MilesMatthew,et al.  Qualitative Data Analysis , 2009, Approaches and Processes of Social Science Research.

[3]  Aniket Kittur,et al.  Crowdsourcing user studies with Mechanical Turk , 2008, CHI.

[4]  Ryen W. White,et al.  Exploratory Search: Beyond the Query-Response Paradigm , 2009, Exploratory Search: Beyond the Query-Response Paradigm.

[5]  W. Buxton Human-Computer Interaction , 1988, Springer Berlin Heidelberg.

[6]  David R. Thomas,et al.  A General Inductive Approach for Analyzing Qualitative Evaluation Data , 2006 .

[7]  Gavriel Salvendy,et al.  Number of people required for usability evaluation , 2010, Commun. ACM.

[8]  Gary Marchionini,et al.  Exploratory search and HCI: designing and evaluating interfaces to support exploratory search interaction , 2007, CHI Extended Abstracts.

[9]  Aba-Sah Dadzie,et al.  Visualisation of Linked Data - Reprise , 2016, Semantic Web.

[10]  Catherine Plaisant,et al.  The challenge of information visualization evaluation , 2004, AVI.

[11]  Erik Frekjmr,et al.  Measuring Usability: Are Effectiveness, Efficiency, and Satisfaction Really Correlated? , 2000 .

[12]  Graham J Hole,et al.  How to Design and Report Experiments , 2002 .

[13]  Natasha Noy,et al.  Crowdsourcing and the Semantic Web: A Research Manifesto , 2015, Hum. Comput..

[14]  Debora Shaw,et al.  Handbook of usability testing: How to plan, design, and conduct effective tests , 1996 .

[15]  Tania Tudorache,et al.  BiOnIC: A Catalog of User Interactions with Biomedical Ontologies , 2017, International Semantic Web Conference.

[16]  Rosa Gil,et al.  Using SWET-QUM to Compare the Quality in Use of Semantic Web Exploration Tools , 2013, J. Univers. Comput. Sci..

[17]  Chaelynne M. Wolak Assessing User Competence: Conceptualization and Measurement , 2000 .

[18]  Jason E. Stewart,et al.  Minimum information about a microarray experiment (MIAME)—toward standards for microarray data , 2001, Nature Genetics.

[19]  Patrick Lambrix,et al.  User Validation in Ontology Alignment , 2016, SEMWEB.

[20]  Harry Hochheiser,et al.  Research Methods for Human-Computer Interaction , 2008 .

[21]  Andrea Giovanni Nuzzolese,et al.  Aemoo: Linked Data exploration based on Knowledge Patterns , 2016, Semantic Web.

[22]  Raimund Dachselt,et al.  IcicleQuery: A Web Search Interface for Fluid Semantic Query Construction , 2017, VOILA@ISWC.

[23]  Sara L. Su,et al.  Understanding Visualization by Understanding Individual Users , 2012, IEEE Computer Graphics and Applications.

[24]  Bo Fu,et al.  Eye tracking the user experience - An evaluation of ontology visualization techniques , 2016, Semantic Web.

[25]  Gary Marchionini,et al.  Exploratory search , 2006, Commun. ACM.

[26]  David R. Karger,et al.  BESDUI: A Benchmark for End-User Structured Data User Interfaces , 2016, International Semantic Web Conference.

[27]  Arild Waaler,et al.  Visual query interfaces for semantic datasets: An evaluation study , 2016, J. Web Semant..

[28]  A. Huberman,et al.  Qualitative Data Analysis: A Methods Sourcebook , 1994 .

[29]  Chris North,et al.  An insight-based methodology for evaluating bioinformatics visualizations , 2005, IEEE Transactions on Visualization and Computer Graphics.

[30]  Valentina Ivanova,et al.  Requirements for and Evaluation of User Support for Large-Scale Ontology Alignment , 2015, ESWC.

[31]  Daniel Schwabe,et al.  Frameworks for Information Exploration - A Case Study , 2015, IESD@ISWC.