Big Data Science has undoubtedly gained relevance in various sectors of society, and efforts to harness its potential have become a priority for the industry, government, and academia alike. The recent, Scottish Government driven Smart Cities Alliance initiative is a prime example of an imminent shift towards future data-driven societies, whereby big data empowers: a) city governments, including through e-governance and open data platforms; b) journalists, for example, through the adoption of web metrics to develop news agenda, Big data/content management systems and embryonic forms of artificial intelligence for newsrooms; and c) citizens, including through their active engagement in compiling, disseminating and interpreting Big Data, subsequently leading to the development of smart applications with the potential to enhance civic society.
Last year’s announcement by the Scottish Infrastructure and Cities Secretary, Keith Brown, that a 15 million euro (£11.1 million) fund would be allocated to help make Scotland's cities "smarter" through the use of new cutting-edge technological infrastructure, has made it clear that the development and management of big data analytic systems is to be a priority within the strategic planning of seven Scottish cities forming the Scottish Cities Alliance. Within this ecosystem, it is of paramount importance that academia becomes a complementary actor assisting in the design, evolution, explanation and evaluation of the technological infrastructures mediating public life.
This first of its kind, one-day SICSA funded Conference seeks to create networking space where data scientists, technologists and scholars involved with journalism, governance, and civic life can deliberate on best ways to boost the development and exploitation of big data analytics, particularly in Scotland. The goal is to impart an understanding of the strengths and limitations of some of the key data science technologies as they impact the future development of smart cities, open governance and data journalism. In particular, we will explore implications of current approaches to data analysis within city government, local news, academic public research and civic engagement, and ask whether they are compatible with a healthy, democratic and self-sustainable agenda of innovation.
We invite multi-disciplinary academics, PhD research students, technologists, policy makers, media practitioners, community developers and think tanks interested in Big Data Science. The conference is intended to stimulate discussions on the following key themes:
* The current state-of-the-art within the emerging Scottish (and global) socio-technical ecosystem in smart cities, open governance, data journalism and civic innovation.
* The potential risks and benefits to this ecosystem emerging from current trends in data science and artificial intelligence
The Conference will be held in the Court Room, Cottrell Building, Division of Computing Science and Maths, School of Natural Sciences, at the University of Stirling. Travel directions and maps can be found at: http://www.stir.ac.uk/about/getting-here/
Cognitive Big Data Informatics (CogBID) Lab,
Division of Computing Science & Maths,
University of Stirling, UK
(E-mail: email@example.com ; http://cs.stir.ac.uk/~ahu )
Communications, Media & Culture,
Faculty of Arts & Humanities
University of Stirling, UK
Institute of Language, Cognition and Computation
University of Edinburgh
SICSA, as part of its sponsorship of this Conference, is covering the full registration fee for ALL (SICSA and non-SICSA funded) PhD students in computer science departments of SICSA member Scottish universities (for a full list of SICSA Universities, see: http://www.sicsa.ac.uk/about-us/our-members/). The number of SICSA students is limited and a decision on ranking may be taken if necessary. Note that SICSA sponsored PhD students will be responsible for their own travel arrangements and expenses to get to Stirling – they should be able to access local support from their own Schools/Departments to support such travel. All SICSA PhD students are required to include a short statement on their research interests and achievements (no more than 200 words - including career stage and publication details if any) - at the time of submitting their Abstract.