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Data assemblage is the framework which influences data collection and theoretical development beyond the technical elements. This can refer to the political, social, and economic factors which contribute to the production of data.[1] This is a subsection of assemblage theory, which looks specifically at which diverse arrangement of external factors which can contribute in how data is created, collected, utilized and understood.[2] Data assemblage looks specifically at the intersection of system and context factors, and how these intersections interact with one another in a socio-technical sense.
Overview
editThe concepts related the assemblage theory, as laid out by DeLanda, perceives that the interconenctive nature of all processes leads to unique and conflicting space.[2] Data assemblage is a core concept of critical data studies in which the relationships and amalgamation of data develops over its lifetime. These processes can be linked to the institutions which data exists in, but are capable of being altered as it transitions through time and space.
Concepts
editIn relation to twenty-first century data collection strategies and the development of Big data collection,[3] there are several factors of influence on how data is created and its intended purpose as a definitive rationalization of known facts. Data assemblage is a philosophy which questions how truth and content are managed. This is a cyclical field, in which one is acting and being acted upon.[4] Datum points are acted upon and causing action within networks. The process of data assemblage is dependent on the social factors and technology in use. The importance of circumstances means that in critical data studies each collection is under its own realm of influence, and is capable of influencing other spaces.
Technology
editThis factor relates to the ecosystem which data exists within in terms of how data is perceived through a realist view, such as the regulatory factors, user interface or operating system. The way in which measurements exists and how data is constructed are also related to technology. This is a diverse area in which many elements can be considered a technological source of influence.
Social
editSocial influence comes from the contextual spaces which influence how data is understood. This largely relates to the framing of systems, or which factors can contribute to how data is interpreted. These lenses by which data is understood are seen to be space in which the social norms influence how data behaves over its lifetime.[1] This can be institutions and stakeholders who created or are looking to utilize the data.
Application
editIn developing analysis through critical data studies, the application of data assemblage looks at how a system and the context which frames a system exert influence over the data processes.[5] In this critical analysis, data is examined in a way which allows for a reflection on existing assemblages which affect data. In critical analysis, these connections or networks are which construct the assemblage.[1] Examples of this can be seen in studies for data collection in smart cities, the production of constant data streams via big data,[6] and in the development of a family tree.[7]
As data develops as an industry and moves further within critical fields of thought, data assemblage allows for the assembly and disassembly of institutional influence, such as in the examination of data colonialism. It is not possible to remove data from its assemblage process because the web of relations is present from data's inception. An example of this is a government purchasing data from a data broker. Although the collection process may attempt to avoid biases, the construction of data, the collection process, and the ability to purchase it in bulk all come to be results of data capitalism.[8]
See Also
editReferences
edit- ^ a b c Kitchin, Rob (2022). The data revolution : a critical analysis of big data, open data & data infrastructures (Second edition ed.). Los Angeles, CA. ISBN 978-1-5297-3375-4. OCLC 1285687714.
{{cite book}}:|edition=has extra text (help)CS1 maint: location missing publisher (link) - ^ a b De Landa, Manuel (2016). Assemblage theory. Edinburgh. pp. 127–133. ISBN 978-1-4744-1364-0. OCLC 964447319.
{{cite book}}: CS1 maint: location missing publisher (link) - ^ P., Kitchin, Rob Lauriault, Tracey (2014-07-27). Towards critical data studies: Charting and unpacking data assemblages and their work. The Programmable City Working Paper 2. Programmable City. OCLC 1291151213.
{{cite book}}: CS1 maint: multiple names: authors list (link) - ^ Paasonen, Susanna (2015-12). "As Networks Fail: Affect, Technology, and the Notion of the User". Television & New Media. 16 (8): 701–716. doi:10.1177/1527476414552906. ISSN 1527-4764.
{{cite journal}}: Check date values in:|date=(help) - ^ Williamson, Ben (2017-08). "Learning in the 'platform society': Disassembling an educational data assemblage". Research in Education. 98 (1): 59–82. doi:10.1177/0034523717723389. ISSN 0034-5237.
{{cite journal}}: Check date values in:|date=(help) - ^ Desjardins, Jeff. "How much data is generated each day?". World Economic Forum. Retrieved 2022-12-09.
- ^ Nordstrom, Susan Naomi (2015). "A Data Assemblage". International Review of Qualitative Research. 8 (2): 166–193 – via SAGE.
- ^ World Economic Forum (2011). Personal Data: The Emergence of a New Asset Class. World Economic Forum. pp. 13–26.