Abstract
We present the methodological principles underlying the scientific activities of the DHST Commission on the History and Philosophy of Computing. This volume collects refereed selected papers from the First International Conference organized by the Commission.
Notes
Lakatos, I. (1970), History of science and its rational reconstructions, Proceedings of the Biennial Meeting of the Philosophy of Science Association, pp. 91–136.
DHST is the Division for the History of Science and Technology of the International Union for the history and philosophy of science.
See www.hapoc.org for more details.
See M. Vogelsberger et al (2014), Properties of galaxies reproduced by hydrodynamic simulation, Nature, vol. 509, pp. 177–182.
This strong assumption drives the research areas of data mining and big data analytics, although not necessarily taken with its full methodological implications: “[D]ata mining is the process of discovering interesting knowledge from large amounts of data stored in databases, data warehouses or other information repositories. […] By performing data mining, interesting knowledge, regularities, or high-level information can be extracted from databases and viewed or browsed from different angles. […]. [D]ata mining is considered one of the most important frontiers in database and information systems and one of the most promising interdisciplinary developments in the information technology.” [Han, J. and Kamber, M., Data mining—concepts and techniques, Elsevier, 2006.]
M. Heidegger (1954), Die Frage nach der Technik, in: M. Heidegger, Vorträge und Aufsätze, Verlag Günther Neske.
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De Mol, L., Primiero, G. Facing Computing as Technique: Towards a History and Philosophy of Computing. Philos. Technol. 27, 321–326 (2014). https://doi.org/10.1007/s13347-014-0169-4
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DOI: https://doi.org/10.1007/s13347-014-0169-4