Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
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1Fonseca, F. ; Marcinkowski, M. ; Davis, C.: Cyber-human systems of thought and understanding.
In: Journal of the Association for Information Science and Technology. 70(2019) no.4, S.402-411.
Abstract: The present challenge faced by scientists working with Big Data comes in the overwhelming volume and level of detail provided by current data sets. Exceeding traditional empirical approaches, Big Data opens a new perspective on scientific work in which data comes to play a role in the development of the scientific problematic to be developed. Addressing this reconfiguration of our relationship with data through readings of Wittgenstein, Macherey, and Popper, we propose a picture of science that encourages scientists to engage with the data in a direct way, using the data itself as an instrument for scientific investigation. Using GIS as a theme, we develop the concept of cyber-human systems of thought and understanding to bridge the divide between representative (theoretical) thinking and (non-theoretical) data-driven science. At the foundation of these systems, we invoke the concept of the "semantic pixel" to establish a logical and virtual space linking data and the work of scientists. It is with this discussion of the relationship between analysts in their pursuit of knowledge and the rise of Big Data that this present discussion of the philosophical foundations of Big Data addresses the central questions raised by social informatics research.
Inhalt: Vgl.: https://onlinelibrary.wiley.com/doi/10.1002/asi.24132.
Anmerkung: Beitrag eines Special issue on social informatics of knowledge
Themenfeld: Data Mining
Wissenschaftsfach: Informatik ; Philosophie
2Marcinkowski, M.: Data, ideology, and the developing critical program of social informatics.
In: Journal of the Association for Information Science and Technology. 67(2016) no.5, S.1266-1275.
Abstract: The rapidly shifting ideological terrain of computing has a profound impact on Social Informatics's critical and empirical analysis of computerization movements. As these movements incorporate many of the past critiques concerning social fit and situational context leveled against them by Social Informatics research, more subtle and more deeply ingrained modes of ideological practice have risen to support movements of computerization. Among these, the current emphasis on the promises of data and data analytics presents the most obvious ideological challenge. In order to reorient Social Informatics in relation to these new ideological challenges, Louis Althusser's theory of ideology is discussed, with its implications for Social Informatics considered. Among these implications, a changed relationship between Social Informatics's critical stance and its reliance on empirical methods is advanced. Addressed at a fundamental level, the practice of Social Informatics comes to be reoriented in a more distinctly reflective and ethical direction.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23483/abstract.
3Marcinkowski, M. ; Fonseca, F.: ¬The conditions of peak empiricism in big data and interaction design.
In: Journal of the Association for Information Science and Technology. 67(2016) no.6, S.1279-1288.
Abstract: An influx of mechanisms for the collection of large sets of data has prompted widespread consideration of the impact that data analytic methods can have on a number of disciplines. Having an established record of the use of a unique mixture of empirical methods, the work of understanding and designing for user behavior is well situated to take advantage of the advances claimed by "big data" methods. Beyond any straightforward benefit of the use of large sets of data, such an increase in the scale of empirical evidence has far-reaching implications for the work of empirically guided design. We develop the concept of "peak empiricism" to explain the new role that large-scale data comes to play in design, one in which data become more than a simple empirical tool. In providing such an expansive empirical setting for design, big data weakens the subjective conditions necessary for empirical insight, pointing to a more performative approach to the relationship between a designer and his or her work. In this, the work of design is characterized as "thinking with" the data in a partnership that weakens not only any sense of empiricism but also the agentive foundations of a classical view of design work.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23497/abstract.