Data-Driven Innovation Workshop 2016

Workshop Goals

This session is intended to be a half-day workshop covering a number of studies related to the utilization of data within an innovation context, and the ability for the Web to facilitate these processes. This can be from, but is not limited to, an organizational, individual, social and/or psychological perspective. Merging theory and practice from multiple disciplines is wholly welcomed due to the interdisciplinary nature of the topic and of the wider Web Sci 16 conference.

The following are the preliminary goals of the workshop:

  •      Uncover best practices on building and managing innovation ecosystems on the Web
  •      Provide case examples of data-driven innovation ecosystems/network
  •      Provide models and strategies for managing and implementing a data-driven innovation scenario
  •      Present challenges associated with utilising data in this context
  •      Determine skills requirements in data-driven innovation
  •      Determine characteristics of data appropriate for innovation

Organising Committee

Mr. Gareth Beeston, PhD Researcher and EDSA Project, University of Southampton

Dr. Xin Wang, VOICE Project, University of Southampton

Dr. Christopher Phethean, EDSA Project, University of Southampton

Chairs

Dr. Thanassis Tiropanis, Associate Professor, WAIS Group, University of Southampton

Dr. Massimo Mecella, Associate Professor, SAPIENZA, Università di Roma

Programme Committee

Rafaela Kunz, London South Bank University, UK

Dr. Sofoklis Kyriazakos, Associate Professor, CTIF, Aalborg University

Dr. Thomas Wainwright, Royal Holloway University of London, UK

Dr. Antonio Bob Santos, Instituto Universitario De Lisboa, Portugal

Background

The Web provides a platform through which data can be collected, harvested and stored, with many organisations and individuals leveraging such datasets for innovation practice, process and creation. The Web also provides a platform through which data can be leveraged more effectively, and personnel residing outside the boundaries of an organisation can offer ideas for innovation through Web-based platforms. In light of this, it is revered that innovative practices cannot be performed as efficiently without access to data, or networks that can facilitate these innovation processes. However, through this assumption a number of questions arise regarding the usefulness of data in the innovation context, the data skills of the innovator, and the capabilities of the innovation network on the Web. In order to understand how individuals and organisations utilize data for innovative intent, studies are required to provide unique perspectives on this increasingly important research topic.

Motivation

This workshop is proposed in order to align objectives of academic research with those detailed in the Horizon2020 European Commission funding which looks to develop new models of innovation, utilize data in an innovation context for economic effect, and utilize technologies, such as the Web, to co-create and co-innovate. With this alignment, it is proposed by the workshop organizing committee that the Web Science perspective enables research in this field to break new ground, combining research techniques from different academic disciplines and theoretical perspectives in order to better understand and formulate data-driven innovation processes, and encourage optimized innovation outputs.

Schedule of Sessions (Half-Day Workshop)

Welcome and Introduction

  •     Welcome and Introduction by Dr. Thanassis Tiropanis (10 minutes)
  •     Keynote – Professor David De Roure (30 minutes)

Bio: David De Roure is Professor of e-Science, Director of the Oxford e-Research Centre, and a Senior Fellow at the Oxford Martin School. He has strategic responsibility for Digital Humanities at Oxford. His personal research is in Web Science and Internet of Things, and he has held the roles of director of the national Digital Social Research programme, and Strategic Adviser for new and emerging forms of data, for the UK Economic and Social Research Council.  He is a frequent speaker and writer on digital scholarship and the future of scholarly communications.

Abstract: Co-creation flourishes in the Web ecosystem, where the affordances of the digital bring a new scale of citizen participation and a new empowerment of the ingenious human. As we enter the era of the Internet of Things we anticipate new opportunities to realise the economic value of data. But what will happen when data supply massively outstrips demand, and as innovative data use is inevitably coupled with increasing automation? This talk will take a long view of co-creation, Web Science, and data driven innovation (roughly from 1600 to 2050).

Paper Session 1 – Session Chair: Mr. Gareth Beeston

  •     Paper 1: Ideas Matchmaking for Supporting Innovators and Entrepreneurs (Francesco Leotta, Massimo Mecella and Stavros Vassos)
  •     Paper 2: Facilitating Data-Driven Innovation using VOICE Observatory Infrastructure (Eugene Siow, Xin Wang and Thanassis Tiropanis)

Coffee break (15 minutes)

Paper Session 2 – Session Chair: TBC

  •     Paper 3: Ethical and legal support for innovation on Web Observatories (Caroline Wilson, Thanassis Tiropanis, Anni Rowland-Campbell and Leanne Fry)
  •     Paper 4: Recommendations beyond the Ratings Matrix (Eirini Ntoutsi and Kostas Stefanidis)
  •     Paper 5: On the Quest for Changing Knowledge (Marco Brambilla, Stefano Ceri, Florian Daniel and Emanuele Della Valle)

Panel Session (30-45 minutes) – The Future of Data-Driven Innovation

Conclusion and Wrap up (10 minutes)

Selection Criteria

The deadline for submissions is Friday 1st of April at 11:59pm (Hawaii Standard Time), with acceptances and rejections planned for Friday 8th of April 2016, or before. Camera-ready submissions, accepted to the workshops, will be required by 18th April 2016 at 11:59pm (Hawaii Standard Time). 

Possible topics for submissions include, but are not limited to, the following:

  •    Uncover best practices on building and managing innovation ecosystems on the Web
  •      Provide case examples of data-driven innovation ecosystems/network
  •      Provide models and strategies for managing and implementing a data-driven innovation scenario
  •      Present challenges associated with utilising data in this context
  •      Determine skills requirements in data-driven innovation
  •      Determine characteristics of data appropriate for innovation

Papers will be submitted via Easychair utilizing the ACM SIG proceedings format. We welcome short papers (2-5 pages) aimed at answering any questions related to data usage in an innovation context, and/or innovation occurrences on the Web. These can include case examples, experimental studies, or studies of Web-based innovation platforms. Each accepted paper will be published on the workshop website before the workshop so that delegates of this workshop can prepare for questions at each of the paper sessions.

Papers will be assessed based upon the following criteria:

  •      Alignment with the workshop objectives
  •      Novel approaches and examples of data-driven innovation
  •      Contribution to the field of data-driven innovation
  •      May have an industry-focused or practitioner orientated element
  •      Clear structure and presentation
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