IDC Seminar: Fast and frugal decision-making – Professor Mandeep K. Dhami

Tuesday, 3rd December, 2013

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Professor Mandeep Dharmi, professor of decision psychology, Middlesex University, gave a talk at the IDC Seminar, entitled “Fast and frugal decision making”. Her research suggests that people when faced with decisions with many attributes, are often likely to make that decision based on one key attribute or cue. This is known as ‘frugal’ decision making, and her studies in different domains such as medicine, crime, policing and law, seem to provide evidence for this. She is now extending her work in this area into other domains such as intelligence analysis.

IDC Seminar: An Extensible Framework for Provenance in Human Terrain Visual Analytics – Dr. Rick Walker

Tuesday, 26th November, 2013

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We describe and demonstrate an extensible framework that supports data exploration and provenance in the context of Human Terrain Analysis (HTA). Working closely with defence analysts we extract requirements and a list of features that characterise data analysed at the end of the HTA chain. From these, we select an appropriate non-classified data source with analogous features, and model it as a set of facets. We develop ProveML, an XML-based extension of the Open Provenance Model, using these facets and augment it with the structures necessary to record the provenance of data, analytical process and interpretations. Through an iterative process, we develop and refine a prototype system for Human Terrain Visual Analytics (HTVA), and demonstrate means of storing, browsing and recalling analytical provenance and process through analytic bookmarks in ProveML. We show how these bookmarks can be combined to form narratives that link back to the live data. Throughout the process, we demonstrate that through structured workshops, rapid prototyping and structured communication with intelligence analysts we are able to establish requirements, and design schema, techniques and tools that meet the requirements of the intelligence community. We use the needs and reactions of defence analysts in defining and steering the methods to validate the framework. 

IDC Seminar: Visualising the Smart Home – Sarah Goodwin and Graham Dove

Tuesday, 19th November, 2013

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We enhance a user-centred design process with techniques that deliberately promote creativity to identify opportunities for the visualisation of data generated by a major energy supplier. Visualisation prototypes developed in this way prove effective in a situation whereby data sets are largely unknown and requirements open – enabling successful exploration of possibilities for visualization in Smart Home data analysis. It suggests: that the deliberate use of creativity techniques with data stakeholders is likely to contribute to successful, novel and effective solutions; that being explicit about creativity may contribute to designers developing creative solutions; that using creativity techniques early in the design process may result in a creative approach persisting throughout the process. The work constitutes the first systematic visualisation design for a data rich source that will be increasingly important to energy suppliers and consumers as Smart Meter technology is widely deployed. 

Data seem set to play an increasingly prominent role in the design of new products or services. Here we will outline on-going research exploring how information visualization can be used to make these data more accessible and engaging to key stakeholder representatives during design workshops. The objective of these workshops being to identify ideas for design requirements that are both novel and appropriate, and therefore considered creative. We illustrate this research with details of a workshop held with customers and staff of E.ON Energy in which the objective was to design new services that utilise the data generated by smart energy meters.

IDC Students attend TUTOREM 2013

Monday, 18th November, 2013

20131106_213358Phong Nguyen, Ashley Wheat and Marianne Markowski recently attended the TwinTide AUtumn Training SchOol 2013: REsearch Methods for Human-Computer Interaction (TUTOREM 2013). The overarching goal of TUTOREM is to improve participants’ understanding of significant research methods commonly or increasingly used in the field of HCI. Such an enhanced understanding will enable them to select and combine appropriate research methods for their specific HCI projects and to contextualise them without unintended impacts on validity. While we recognise the importance of theories that inform the development of research methods, due to the time constraint no session is dedicated to HCI theories. Nevertheless, relevant theoretical frameworks will be addressed in individual sessions of TUTOREM, which consist of lectures, workshops and discussions. In addition, student participants will collaboratively work in small groups on a mini-project with the topic identified by the School’s lecturers. More information can be found at http://www2.le.ac.uk/departments/computer-science/people/elaw/tutorem.

IDC Seminar: Geovisual data mining of space-time trajectories – Dr. Tony Moore

Tuesday, 12th November, 2013

image Through GPS and tracking technologies, there now exists an abundance of space-time trajectory data, and this resource is exponentially increasing in size. The lion’s share of this dataset comes from humans and mobile devices such as smartphones, but a significant mass of data relates to animal movement, collected through portable devices attached to the animal. The problem to be addressed ins this: Taking into account a dataset relating to even a single animal, conventional mapping techniques would render all but the simplest dataset as an uninterpretable ‘scribble’. To address this, an adaption of the REMO method (which transforms a set of space-time trajectories into a grid of directions travelled, or velocities, with listed trajectories discretised into regular time intervals) will be outlined. The modified version reorders trajectory lines according to proximity through simulated annealing, an optimizing method. Featured space-time data will be selected from an assembled dataset collected from sealions, feral cats, hedgehogs, dolphins and buff weka.