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Ethnomethodological architectures: Information systems driven by cultural and community visions

Authors: Colin Meek; Roger B. Dannenberg; George Tzanetakis; Bryan Pardo; Ning Hu; William P. Birmingham;

Ethnomethodological architectures: Information systems driven by cultural and community visions

Abstract

AbstractAs networked digital systems are rapidly created and deployed, social, cultural, and community‐focused issues are often neglected. Indeed much research has focused on the “effects” these systems hold rather than viewing systems as tools to be designed given an understanding of sociocultural context. Acknowledging the cultural practices and belief systems of a set of users may allow systems to be more effectively created and deployed into particular contexts. Emerging research in community information systems and archives has highlighted possible interactions between system design and ethnographic research. These bridges include understanding how communities can begin (1) to create content for their own information systems, (2) to design the database architectures, and (3) to integrate systems within community infrastructures. In this article, I allude to several cultural criticisms that accompany the global proliferation of information technologies. These criticisms can be answered by research that focuses on developing systems based on ethnographic insights. Specifically, I present the research example of Tribal Peace, a cultural information system designed for and by community members of the 19 Native American reservations of San Diego County (California, United States). This case has demonstrated the potential for a community to create an information system that satisfies its own priorities. This precedent points to the need for further research that investigates this convergence.

Countries
Australia, Belgium, Italy
Keywords

FOS: Computer and information sciences, 020, Dogpile, 303, 004, stemming; hidden markov models; evaluation, Web Search, Meta Search Engines, 89999 Information and Computing Sciences not elsewhere classified, Web Search Engines, Information Systems

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    421
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
421
Top 1%
Top 1%
Top 1%
Green
hybrid