Dataset Information

Interdisciplinary collaboration in action: tracking the signal, tracing the noise.

ABSTRACT: Interdisciplinarity is often framed as an unquestioned good within and beyond the academy, one to be encouraged by funders and research institutions alike. And yet there is little research on how interdisciplinary projects actually work-and do not work-in practice, particularly within and across the social sciences and humanities. This article centres on "Hubbub", the first interdisciplinary 2-year research residency of The Hub at Wellcome Collection, which is investigating rest and its opposites in neuroscience, mental health, the arts and the everyday. The article describes how Hubbub is tracing, capturing and reflecting on practices of interdisciplinarity across its large, dispersed team of collaborators, who work across the social sciences, humanities, arts, mind and brain sciences, and public engagement. We first describe the distinctiveness of Hubbub (a project designed for a particular space, and one in which the arts are not positioned as simply illustrating or disseminating the research of the scientists), and then outline three techniques Hubbub has developed to map interdisciplinary collaboration in the making: (1) ethnographic analysis; (2) "In the Diary Room", an aesthetics of collaboration designed to harness and capture affective dynamics within a large, complex project; and (3) the Hubbub Collaboration Questionnaire, which yields quantitative and qualitative data, as well as a social network analysis of collaborators. We conclude by considering some themes that other inter-disciplinary projects might draw on for their own logics of tracking and tracing. This article forms part of an ongoing thematic collection dedicated to interdisciplinary research.

SUBMITTER: Callard F

PROVIDER: S-EPMC4978461 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Interdisciplinary collaboration in action: tracking the signal, tracing the noise.

Callard Felicity F Fitzgerald Des D Woods Angela A

Palgrave communications 20150721

Interdisciplinarity is often framed as an unquestioned good within and beyond the academy, one to be encouraged by funders and research institutions alike. And yet there is little research on how interdisciplinary projects actually work-and do not work-in practice, particularly within and across the social sciences and humanities. This article centres on "Hubbub", the first interdisciplinary 2-year research residency of The Hub at Wellcome Collection, which is investigating rest and its opposite ...[more]

PMID: 27516896

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Project description:Human-robot collaboration could be advanced by facilitating the intuitive, gaze-based control of robots, and enabling robots to recognize human actions, infer human intent, and plan actions that support human goals. Traditionally, gaze tracking approaches to action recognition have relied upon computer vision-based analyses of two-dimensional egocentric camera videos. The objective of this study was to identify useful features that can be extracted from three-dimensional (3D) gaze behavior and used as inputs to machine learning algorithms for human action recognition. We investigated human gaze behavior and gaze-object interactions in 3D during the performance of a bimanual, instrumental activity of daily living: the preparation of a powdered drink. A marker-based motion capture system and binocular eye tracker were used to reconstruct 3D gaze vectors and their intersection with 3D point clouds of objects being manipulated. Statistical analyses of gaze fixation duration and saccade size suggested that some actions (pouring and stirring) may require more visual attention than other actions (reach, pick up, set down, and move). 3D gaze saliency maps, generated with high spatial resolution for six subtasks, appeared to encode action-relevant information. The "gaze object sequence" was used to capture information about the identity of objects in concert with the temporal sequence in which the objects were visually regarded. Dynamic time warping barycentric averaging was used to create a population-based set of characteristic gaze object sequences that accounted for intra- and inter-subject variability. The gaze object sequence was used to demonstrate the feasibility of a simple action recognition algorithm that utilized a dynamic time warping Euclidean distance metric. Averaged over the six subtasks, the action recognition algorithm yielded an accuracy of 96.4%, precision of 89.5%, and recall of 89.2%. This level of performance suggests that the gaze object sequence is a promising feature for action recognition whose impact could be enhanced through the use of sophisticated machine learning classifiers and algorithmic improvements for real-time implementation. Robots capable of robust, real-time recognition of human actions during manipulation tasks could be used to improve quality of life in the home and quality of work in industrial environments.

Project description:Interdisciplinary collaboration, particularly between natural and social sciences, is perceived as crucial to solving the significant challenges facing humanity. However, despite the need for such collaboration being expressed more frequently and intensely, it remains unclear to what degree such collaboration actually takes place, what trends and developments there are and which actors are involved. Previous studies, often based on bibliometric analysis of large bodies of literature, partly observed an increase in interdisciplinary collaboration in general, but in particular, the collaboration among distant fields was less explored. Other more qualitative studies found that interdisciplinary collaboration, particularly between natural and social scientists was not well developed, and obstacles abounded. To shed some light on the actual status and developments of this collaboration, we performed an analysis based on a sample of articles on groundwater research. We first identified journals and articles therein that potentially combined natural and social science aspects of groundwater research. Next, we analysed the disciplinary composition of their authors' teams, cited references, titles and keywords, making use of our detailed personal expertise in groundwater research and its interdisciplinary aspects. We combined several indicators developed from this analysis into a final classification of the degree of multidisciplinarity of each article. Covering the period between 1990 and 2014, we found that the overall percentage of multidisciplinary articles was in the low single-digit range, with only slight increases over the past decades. The interdisciplinarity of individuals plays a major role compared to interdisciplinarity involving two or more researchers. If collaboration with natural sciences takes place, social science is represented most often by economists. As a side result, we found that journals publishing multidisciplinary research had lower impact factors on average, and multidisciplinary papers were cited much less than mono-disciplinary ones.

Dataset Information

Interdisciplinary collaboration in action: tracking the signal, tracing the noise.

Publications

Interdisciplinary collaboration in action: tracking the signal, tracing the noise.

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