Socialising Big Data

Date:

24/06/2014

Organised by:

Goldsmiths, University of London

Presenter:

Dr Evelyn Ruppert,
Department of Sociology, Goldsmiths
PI ESRC Socialising Big Data Project

Prof Penny Harvey,
Anthropology and Director of CRESC,
University of Manchester

Prof Celia Lury,
Sociology and Director, Centre for Interdisciplinary Methodologies,
University of Warwick

Dr Ruth McNally,
Principal Lecturer, Innovation, Technology and Management,
Lord Ashcroft International Business School,
Anglia Ruskin University

Level:

Advanced (specialised prior knowledge)

Contact:

Dr Stephanie Alice Baker

(t): +44 (0)20 7919 7016
(e): sa.baker@gold.ac.uk

Map:

View in Google Maps  (SE14 6NW)

Venue:

Richard Hoggart Building
Room 342a
Goldsmiths, University of London,
New Cross,
London, UK

Description:

This advanced interdisciplinary PhD workshop will involve ‘socialising’ Big Data in two ways. First it will comprise training in the concept and conduct of ‘collaboratories’ as a social science method of working with practitioners not as informants or users but as co-producers of concepts and knowledge. The workshop will do this through illustrations and discussions of collaboratories that have been conducted with practitioners who work with Big Data in three different contexts: bioscience, national statistics and waste management. In addition to attending to how these collaboratories worked methodologically, the workshop will explore their substantive discussions and findings concerning the range of meanings and the problems, risks and potentials of Big Data across the different practical settings. In this way the workshop will involve both training in how to ask critical questions about Big Data that can be taken up in relation to other substantive and practical contexts as well as the collaboratory as a social science method.

Cost:

UK Doctoral Students = free
International Doctoral Students = £30

Website and registration:

Region:

Greater London

Keywords:

Epistemology, Case Study, Participatory Research, Analysis of official statistics, Analysis of administrative data, Survey and Questionnaire Design, Data Collection (other), Data Quality and Data Management , Data archiving, Data Quality and Data Management (other), Data linkage, Confidentiality and Anonymity, Research Ethics, Big Data , Digital Data , Raw data , Data mining , Data practitioners , Genomics data , Official Statistics data , Waste Management data , Ontology , Governmentality , Performativity of method

Related publications and presentations:

Epistemology
Case Study
Participatory Research
Analysis of official statistics
Analysis of administrative data
Survey and Questionnaire Design
Data Collection (other)
Data Quality and Data Management
Data archiving
Data Quality and Data Management (other)
Data linkage
Confidentiality and Anonymity
Research Ethics

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