Event description
New forms of data, data science and data analytics have reshaped social science research over the past years. Rapid growth has been spurred on by the proliferation of complex and rich data in science, industry and government, which are potentially available for research. As a result, (big) data analytics are no longer the preserve of engineering and computer science students, but as big datasets are increasingly becoming common in most domains, analytical skills have become essential to most fields of study and practice, and certainly to social science and Business School students. These trends have set new expectations about research questions, data collection and analysis methods as well as the general skills of doctoral students in social science research. Social science doctoral programmes have responded to the challenge of integrating new methods at the intersection of the computational and social sciences with new programmes and communities. Beyond these specialised programmes, the vast majority of doctoral courses have not caught up methodologically with advances in the area or are not able to harness the potential fully.
Doctoral students and early career researchers in management studies will need to acquire some familiarity with big data techniques alongside their traditional training over the course of their academic careers. If doctoral programmes do not include data science aspects (beyond the ones typically covered in quantitative methods) they risk limiting the scope of tackling objectives that are topical and relevant to theory and practice. For example, it limits the potential of projects to applying mixed methods approaches where qualitative insight can be combined with sources such as social media data or crowdsourcing . This is especially true when it comes to interdisciplinary projects that require novel ways of methodological synthesis. Introducing data science into doctoral programmes is not to say that such training would result in cross-functional, cross-discipline, all-knowing candidates who can tackle any research objective that can deliver valuable analytical insights. Instead, such curriculum and training interventions can complement the business/domain knowledge and the soft skills that graduates have with:
- framing complex data-driven research questions and data capturing skills
- data validation, manipulation and storage, using widely supported tools
- application of statistics, machine learning and predictive analytics
- data visualisation in appropriate forms
To this end our doctoral consortium puts a strong emphasis on increasing awareness of data related opportunities and challenges.
For more information, please visit the event webpage here
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Provisional Programme
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12th of September |
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08.30 – 09.00 |
Arrival and registration |
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9.00 – 09.15 |
Welcome note by the workshop organisers |
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09.15 – 10.30 |
Barry Hodgson, Strategy Director, National Innovation Centre for Data: "Supporting innovation, increased productivity, and data skills development - the National Innovation Centre for Data engagement model"
Barry leads on strategy and operations for the National Innovation Centre for Data. He has deep experience of entrepreneurship and innovation in the software industry and portfolio management of large-scale research projects in academia. Having started with a university tech spin-out, he was involved in multi-million-dollar acquisitions where he was the Director responsible for due diligence, finance and investor relations. Returning to academia he has focussed on data and played a major role in attracting over £100m in funding to the region including his work to establish the National Innovation Centre for Data at Newcastle University. |
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10.30 – 10.45 |
Coffee Break |
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10.45 – 12.00 |
Dr Matthew Forshaw, Senior Advisor for Skills to The Alan Turing Institute / Senior Lecturer in Data Science at Newcastle University: Data Skills for a Developing Workforce: observations from the UK’s national skills landscape
Dr Matthew Forshaw is Senior Advisor for Skills to The Alan Turing Institute, and a Senior Lecturer in Data Science at Newcastle University. His work in data and AI skills includes working with the Government on the skills pillar of the National Data Strategy, leadership of skills policy initiatives through the Data Skills Taskforce, and as Expert Advisor to the Department for Digital, Culture, Media and Sport (DCMS). His work on professionalisation of the data science occupation with the Alliance of Data Science Professionals is having a major impact on public and professional policy and practice, setting professional values and ethical standards for the use of data science and AI for the UK’s accreditation and certification processes across several major professional bodies. He is passionate about democratising access to, and widening participation into, data and AI skills training at all levels. |
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12.00 – 12.45 |
Lunch |
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12.45 – 14.00 |
Prof Rachel Franklin, Centre for Urban and Regional Development Studies, Newcastle University: The Business Case for Data Rachel Franklin is a Professor of Geographical Analysis in the Centre for Urban and Regional Development Studies (CURDS) and the School of Geography, Politics and Sociology at Newcastle University, theme lead for Spatial Analytics at Newcastle Data, Co-I for the EPSRC-funded Centre for Doctoral Training (CDT) in Geospatial Systems, and the University Lead for Newcastle for the Alan Turing Institute, where she is also a Fellow. Her primary research focus is in spatial demography and the interplay between spatial analytics and demographic change, in particular quantifying patterns, sources and impacts of spatial inequality. She also maintain an ongoing interest in pedagogy, especially the teaching of methods. She has taught spatial analysis, GIS, and quantitative methods for well over a decade, with a pedagogic orientation towards policy applications and the social sciences and humanities, and is the co-author of a recent textbook aimed at teaching GIS for the social sciences. She is the current editor of the journal, Geographical Analysis, and sit on the Board of the Regional Studies Association, as Chair for Diversity and Inclusion.
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14.00 – 14.15 |
Coffee Break |
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14.15 – 15.30 |
Tackling data science problems in research |
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14.15 – 15.30 |
Prof Thanos Papadopoulos (Associate Editor of British Journal of Management): "Publishing in top journals: A data perspective" |
Networking: Drinks Receptions
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Provider Information
Supported by SAMS, BAM Ebusiness & Egovernment SIG, Newcastle University Business School, Coventry University, Queen Mary University of London
