License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.6.7.42
URN: urn:nbn:de:0030-drops-67644
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2016/6764/
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Abiteboul, Serge ; Miklau, Gerome ; Stoyanovich, Julia ; Weikum, Gerhard
Weitere Beteiligte (Hrsg. etc.): Serge Abiteboul and Gerome Miklau and Julia Stoyanovich and Gerhard Weikum

Data, Responsibly (Dagstuhl Seminar 16291)

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dagrep_v006_i007_p042_s16291.pdf (0.9 MB)

Abstract

Big data technology promises to improve people's lives, accelerate
scientific discovery and innovation, and bring about positive societal
change. Yet, if not used responsibly, large-scale data analysis and
data-driven algorithmic decision-making can increase economic
inequality, affirm systemic bias, and even destabilize global markets.

While the potential benefits of data analysis techniques are well
accepted, the importance of using them responsibly - that is, in
accordance with ethical and moral norms, and with legal and policy
considerations - is not yet part of the mainstream research agenda
in computer science.

Dagstuhl Seminar "Data, Responsibly" brought together academic and
industry researchers from several areas of computer science, including
a broad representation of data management, but also data mining,
security/privacy, and computer networks, as well as social sciences
researchers, data journalists, and those active in government
think-tanks and policy initiatives. The goals of the seminar were to
assess the state of data analysis in terms of fairness, transparency
and diversity, identify new research challenges, and derive an agenda
for computer science research and education efforts in responsible
data analysis and use. While the topic of the seminar is
transdisciplinary in nature, an important goal of the seminar was to
identify opportunities for high-impact contributions to this important
emergent area specifically from the data management community.

BibTeX - Entry

@Article{abiteboul_et_al:DR:2016:6764,
  author =	{Serge Abiteboul and Gerome Miklau and Julia Stoyanovich and Gerhard Weikum},
  title =	{{Data, Responsibly (Dagstuhl Seminar 16291)}},
  pages =	{42--71},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{7},
  editor =	{Serge Abiteboul and Gerome Miklau and Julia Stoyanovich and Gerhard Weikum},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2016/6764},
  URN =		{urn:nbn:de:0030-drops-67644},
  doi =		{10.4230/DagRep.6.7.42},
  annote =	{Keywords: Data responsibly, Big data, Machine bias, Data analysis, Data management, Data mining, Fairness, Diversity, Accountability, Transparency, Personal}
}

Keywords: Data responsibly, Big data, Machine bias, Data analysis, Data management, Data mining, Fairness, Diversity, Accountability, Transparency, Personal
Freie Schlagwörter (englisch): information management, Ethics, Responsible research, Responsible innovation, Data science education
Collection: Dagstuhl Reports, Volume 6, Issue 7
Issue Date: 2016
Date of publication: 28.11.2016

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