Co-Predicting Weather in a Big Data Society
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Co-Predicting Weather in a Big Data Society

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This is a poster presentation at the 2014 IACAP conference in Thessaloniki, Greece, 2-4 July 2014.

This is a poster presentation at the 2014 IACAP conference in Thessaloniki, Greece, 2-4 July 2014.

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Co-Predicting Weather in a Big Data Society Co-Predicting Weather in a Big Data Society Presentation Transcript

  • Relevance This paper investigates contemporary practices associated with the 'citizen scientific' culture, and how crowd-sourced user-generated data (may they be qualitative or quantitative, a single piece or aggregated information) collected and collated through these practices shape today's data- saturated society. Contemporary 'big data' infrastructures are difficult to study because the vastness of data generated, processed and used by different means and from different sources, blurs the boundaries between individuals, groups, communities, organisations. Whilst citizen scientific projects that solicit crowd- sourced data and information are becoming popular, how are these crowd-sourced data and information being integrated into 'big data' infrastructures? Aims and Objectives To understand the shifting boundaries and complexity in the networks of networks of actors and objects, which are fluid and mobile, this paper employs a framework that traces the 'social life of a weather datum', from its advent, into different contexts of re-use including the Met Office, international climate science and weather derivatives markets. Following the trajectory of the weather datum allows the researchers to map the colliding social worlds involved in the production, consumption, distribution of big data. Methods Based on studies of the UK Met Office's WOW project, and the Zooniverse's Old Weather Data project, this project examines how 'citizen science' projects in relation to weather data are done. We are interested in how crowd-sourced weather data and information are created, shared, tried, governed, averaged, leveraged, integrated and re- used in a big weather data infrastructure. Based on narratives on the internet (found on relevant mailing lists or online forums), published articles in printed media or on the Internet, and interviews with key stakeholders, the ethnographic fieldwork will help unpack how weather is co- predicted in a big data era. Initial results We identify and visualise the trajectories a crowd- sourced user-generated weather datum may travel through infographics as shown below. In this tube- map-like concept image, different stations indicate different organisations or individuals who are involved in data management or manipulation. This map pictures key stakeholders in an infrastructural context (Star 1999, 2002; Star and Bowker 2010) where data (artefacts), services, human knowledge and experiences, and actions are aligned and assembled to shape scientific agenda and cultures. Conclusions Each segment in our map mirrors a socio- technical assemblage found during a value- creating or value- translating process. We found that some concerns such as measurement, accuracy, completeness, and abilities to prediction (in relation to vastness, speed, immediacy) have been favoured and prioritised during data collection, cleaning, processing and analysis. These practices are socio- technical afforded by the advancement and popularisation of computing technologies. This work is part of the UK AHRC-funded 'The Secret Life of a Weather Datum' project. For more information see http://secretlifeofdata.wordpress.com/ References Star, S. L. (1999). 'The Ethnography of Infrastructure'. American Behavioral Scientist, 43(3): 377-391. Star, S. L. (2002). "Infrastructure and ethnographic practice: Working on the fringes,"Scandinavian Journal of Information Systems: Vol. 14: Iss. 2, Article 6. http://aisel.aisnet.org/sjis/vol14/iss2/6 Star, S. L. and Bowker, G. C. (2010). 'How to infrastructure'. In L. A. Lievrouw and S. Livingstone (eds). Handbook of New Media: Social Shaping and Social Consequences of ICTs. Sage.
  • This is an in progress working document of the interactive visualisation map