Abstract — Visual analytics emphasizes sensemaking of large, complex datasets through interactively exploring visualizations generated by statistical models. For example, dimensionality reduction methods use various similarity metrics to visualize textual document collections in a spatial metaphor

are particularly interested in understanding how data: 1) are transformed from qualitative to quantitative data, 2) capture concepts not well-established in the literature, and 3) can be matched and merged across multiple datasets. We discuss how novice data users make sense of data in these three circumstances

at encouraging scientific discussion by advocating an empirical treatment of communicative conflict, that is one which is grounded in the detailed examination of linguistic data. Through the fine-grained analysis of participants ' sense-making processes in a corpus of real-life intercultural data, we seek

combining text and graphics can help users understand this data. In this paper we describe the results of our research on automatic multimedia presentation generation (including text, graphics, maps, images, etc.) for interactive exploration of behavior datasets. We designed a novel user interface

Making use of the National Travel Survey dataset (NTS) for Great Britain, this paper analyses the influence of various socio-economic and accessibility factors on trip rates, and whether these trip rates are stable over time. The motivation of the research was: i. to examine whether the current

Ordnance Survey, the national mapping agency of Britain is researching the development of topographic ontologies to describe our spatial data, motivated by the business need of improving ease of understanding and reuse of our data, as well as assisting its integration with third party datasets

This paper explores the mis/understandings two young children have of the behaviour ‘crisis ’ besetting our schools. Specifically, this paper examines semi-structured interview talk with boys aged between six and eight years of age who were labelled by medical specialists as exhibiting Attention

In this talk, I present a novel academic search and mining system, AMiner1, the second generation of the ArnetMiner system [9]. Different from traditional academic search systems that focus on document (paper) search, AMiner aims to provide a systematic modeling approach to gain a deep

systematically eval-uate smartphones as a platform for mobile ubiquitous computing by quantifying access to critical resources in the wild. Our analysis of the dataset demonstrates considerable diversity in behaviour between users but also over time. We further demonstrate the value of handset-centric data

Micro-level studies of labour market behaviour have fl ourished in the last three decades thanks to the increasing availability of large datasets covering individuals and households (Angrist & Krueger, 1999). The demand for such research – examining individual labour market outcomes and how