Stefano Padilla

Bio: Stefano Padilla is an academic researcher from Heriot-Watt University. The author has contributed to research in topics: Interactive media & Visual communication. The author has an hindex of 10, co-authored 43 publications receiving 309 citations.

Tactile perceptions of digital textiles: a design research approach

Abstract: Current interactive media presentations of textiles provide an impoverished communication of their 'textile hand', that is their weight, drape, how they feel to touch. These are complex properties experienced through the visual, tactile, auditory and proprioceptive senses and are currently lost when textile materials are presented in interactive video. This paper offers a new perspective from which the production of multi-touch interactive video representations of the tactile qualities of materials is considered. Through an understanding of hand properties of textiles and how people inherently touch and handle them, we are able to develop methods to animate and bring these properties alive using design methods. Observational studies were conducted, noting gestures consumers used to evaluate textile hand. Replicating the appropriate textile deformations for these gestures in interactive video was explored as a design problem. The resulting digital textile swatches and their interactive behavior were then evaluated for their ability to communicate tactile qualities similar to those of the real textiles.

Visualising COVID-19 Research

Abstract: The world has seen in 2020 an unprecedented global outbreak of SARS-CoV-2, a new strain of coronavirus, causing the COVID-19 pandemic, and radically changing our lives and work conditions. Many scientists are working tirelessly to find a treatment and a possible vaccine. Furthermore, governments, scientific institutions and companies are acting quickly to make resources available, including funds and the opening of large-volume data repositories, to accelerate innovation and discovery aimed at solving this pandemic. In this paper, we develop a novel automated theme-based visualisation method, combining advanced data modelling of large corpora, information mapping and trend analysis, to provide a top-down and bottom-up browsing and search interface for quick discovery of topics and research resources. We apply this method on two recently released publications datasets (Dimensions' COVID-19 dataset and the Allen Institute for AI's CORD-19). The results reveal intriguing information including increased efforts in topics such as social distancing; cross-domain initiatives (e.g. mental health and education); evolving research in medical topics; and the unfolding trajectory of the virus in different territories through publications. The results also demonstrate the need to quickly and automatically enable search and browsing of large corpora. We believe our methodology will improve future large volume visualisation and discovery systems but also hope our visualisation interfaces will currently aid scientists, researchers, and the general public to tackle the numerous issues in the fight against the COVID-19 pandemic.

Hot topics in CHI: trend maps for visualising research

Abstract: The aim of this paper is to introduce a novel method of identifying and visualising research trends in an automated, unbiased way. The output of this we call a 'Trend Map', and in this paper we use it to present an at-a-glance overview of the CHI research area, showing which areas are 'hot', 'cold', and 'stable'. This specimen Trend Map was created using the past five years of CHI publications as our only input. We hope that providing this at-a-glance overview of the recent CHI area will encourage introspection and discussion within the community.

Improving User Confidence in Concept Maps: Exploring Data Driven Explanations

Abstract: Automated tools are increasingly being used to generate highly engaging concept maps as an aid to strategic planning and other decision-making tasks. Unless stakeholders can understand the principles of the underlying layout process, however, we have found that they lack confidence and are therefore reluctant to use these maps. In this paper, we present a qualitative study exploring the effect on users' confidence of using data-driven explanation mechanisms, by conducting in-depth scenario-based interviews with ten participants. To provide diversity in stimulus and approach we use two explanation mechanisms based on projection and agglomerative layout methods. The themes exposed in our results indicate that the data-driven explanations improved user confidence in several ways, and that process clarity and layout density also affected users' views of the credibility of the concept maps. We discuss how these factors can increase uptake of automated tools and affect user confidence.

Doing qualitative research: a practical handbook

Abstract: Doing qualitative research: a practical handbook, by David Silverman, Los Angeles, Sage, 2010, 456 pp., AU$65.00, ISBN 978-1-84860-033-1, ISBN 978-1-94960-034-8. Available in Australia and New Zeal...

Mapping the backbone of science.

Abstract: This paper presents a new map representing the structure of all of science, based on journal articles, including both the natural and social sciences. Similar to cartographic maps of our world, the map of science provides a bird's eye view of today's scientific landscape. It can be used to visually identify major areas of science, their size, similarity, and interconnectedness. In order to be useful, the map needs to be accurate on a local and on a global scale. While our recent work has focused on the former aspect, this paper summarizes results on how to achieve structural accuracy. Eight alternative measures of journal similarity were applied to a data set of 7,121 journals covering over 1 million documents in the combined Science Citation and Social Science Citation Indexes. For each journal similarity measure we generated two-dimensional spatial layouts using the force-directed graph layout tool, VxOrd. Next, mutual information values were calculated for each graph at different clustering levels to give a measure of structural accuracy for each map. The best co-citation and inter-citation maps according to local and structural accuracy were selected and are presented and characterized. These two maps are compared to establish robustness. The inter-citation map is more » then used to examine linkages between disciplines. Biochemistry appears as the most interdisciplinary discipline in science. « less

Reliability and Inter-rater Reliability in Qualitative Research: Norms and Guidelines for CSCW and HCI Practice

Abstract: What does reliability mean for building a grounded theory? What about when writing an auto-ethnography? When is it appropriate to use measures like inter-rater reliability (IRR)? Reliability is a familiar concept in traditional scientific practice, but how, and even whether to establish reliability in qualitative research is an oft-debated question. For researchers in highly interdisciplinary fields like computer-supported cooperative work (CSCW) and human-computer interaction (HCI), the question is particularly complex as collaborators bring diverse epistemologies and training to their research. In this article, we use two approaches to understand reliability in qualitative research. We first investigate and describe local norms in the CSCW and HCI literature, then we combine examples from these findings with guidelines from methods literature to help researchers answer questions like: "should I calculate IRR?" Drawing on a meta-analysis of a representative sample of CSCW and HCI papers from 2016-2018, we find that authors use a variety of approaches to communicate reliability; notably, IRR is rare, occurring in around 1/9 of qualitative papers. We reflect on current practices and propose guidelines for reporting on reliability in qualitative research using IRR as a central example of a form of agreement. The guidelines are designed to generate discussion and orient new CSCW and HCI scholars and reviewers to reliability in qualitative research.