Interviewing data - the art of interpretation in analytics

Washington, Anne L.

Permalink

https://hdl.handle.net/2142/89433 Copy

Description

Title

Interviewing data - the art of interpretation in analytics

Author(s)

Washington, Anne L.

Issue Date

2016-03-15

Keyword(s)

• data analytics
• naturalistic inquiry
• big data
• ethics
• flu prediction
• validity

Abstract

"Interviewing Data: The art of interpretation in analytics -- Algorithms and statistical models produce consistent results with confidence yet they do so with data that are subject to change. Furthermore, the underlying digital traces created within specifically designed platforms are rarely transparent. The emerging field which incorporates analytics, predictive behavior, big data, and data science, is still contesting its methodological boundaries. How can we use existing research tools to validate the reliability of the data? This paper explores alternatives to statistical validity by situating analytics as a form of naturalistic inquiry. A naturalistic research model, which has no assumption of an objective truth, places greater emphasis on logical reasoning and researcher reflectivity. ""Interviewing data"", based on journalistic practices, is introduced as a tool to convey the reliability of the data. The misleading 2013 flu prediction illustrates this approach and is discussed within the context of ethics and accountability in data science."

Publisher

iSchools

Series/Report Name or Number

IConference 2016 Proceedings

Type of Resource

text

Language

eng

Permalink

http://hdl.handle.net/2142/89433

DOI

https://doi.org/10.9776/16256

Copyright and License Information

Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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