Ruben Riestra

Data Science Professional Uncovered: How the EDISON Project will Contribute to a Widely Accepted Profile for Data Scientists

The digital revolution made available vast amounts of data both in industry and in the research landscape. The ability to manipulate and extract knowledge and value from this data represents a new profession called the Data Scientist: expected to be the most visible job in future years. The EDISON project has been established in order to support universities, research centers, industry and research infrastructure organisations to cope with the potential shortfall of Data Scientists, to define the framework of competences as well as the body of knowledge for this profession. In this paper the EDISON team describes how it intends to nurture the profession of Data Scientist to cope with the expected increase in demand. The strategy proposed is based on both the analysis of the demand side (industries, research centers and research infrastructure organisations) and the supply side (Universities and training centers) bridging between the providers and employers by cooperating on the establishment of a Competence Framework and a Body of Knowledge for the Data Scientist Professional. The project will exploit piloting initiatives in cooperation with pioneer universities and also involve external experts as evangelists.

IVIS4BigData: A Reference Model for Advanced Visual Interfaces Supporting Big Data Analysis in Virtual Research Environments

This paper introduces an approach to develop an up-to-date reference model that can support advanced visual user interfaces for distributed Big Data Analysis in virtual labs to be used in e-Science, industrial research, and Data Science education. The paper introduces and motivates the current situation in this application area as a basis for a corresponding problem statement that is utilized to derive goals and objectives of the approach. Furthermore, the relevant state-of-the-art is revisited and remaining challenges are identified. An exemplar set of use cases, corresponding user stereotypes as well as a conceptual design model to address these challenges are introduced. A corresponding architectural system model is suggested as a conceptual reference architecture to support proof-of-concept implementations as well as to support interoperability in distributed infrastructures. Conclusions and an outlook on future work complete the paper.

SenseCare: Using Affective Computing to Manage and Care for the Emotional Wellbeing of Older People

This paper discusses an opportunity for using affective computing modalities to support the monitoring of emotional wellbeing of older people. The ageing population is escalating and is associated with an increase in the number of persons with dementia. It is also reported that older people can suffer from social isolation and that people with dementia can experience a range of negative emotions such as anxiety and depression. We present a model to care for a person’s emotional wellbeing in the home using multiple-modalities such as video, audio, electrodermal activity and photoplethysmography.

Participatory design-based requirements elicitation involving people living with dementia towards a home-based platform to monitor emotional wellbeing

We are living in an ageing population with an escalation in chronic illnesses including dementia and other age related diseases. People living with dementia often continue to live at home and are supported by caregivers and next of kin. It is often important to monitor the wellbeing of people living with dementia in order to measure their level of independence and to provide proper support at the time of need as well as supporting their quality of life. Some researchers have focused on monitoring physical wellbeing and activities of daily living (ADL). However, there has been a paucity of research focussed on monitoring mood, affect and the emotional wellbeing of people living with dementia, despite these people experiencing frustration, agitation, depression and social isolation to name but a few known effects. As a result, the SenseCare project aims to build an affective computing platform that uses sensors placed in the home environment to monitor moods, affect and the emotional wellbeing of people living with dementia. This platform is being iteratively designed and will likely use plug-n-play sensors such as passive infrared, wearables and camera technologies to infer emotions from facial expressions, voice intonations and physical behaviour and other modalities. However, it is important to interact iteratively with people living with dementia and their caregivers in order to understand their profound needs. In this study, we report on two focus groups that were conducted to elicit user stories and eventual requirements for the SenseCare platform. Since participatory design involving people living with dementia could bring about unique challenges, we adopted a dyad approach where a caregiver and the person living with dementia participate together in the focus group. This ensures that their needs are fully represented and that consent is fully transparent. In this paper, we report the personal stories elicited during these discussions which will ultimately inform the implementation of the SenseCare platform.