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Elizabeth Muthoni Warrick

dblp:192/2370 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Collaborative and social computing · 100%
Network and information security
1 paper
Privacy and data protection · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Collaborative and social computing › crowdsourcing
citizen science
0.312017
Accounting for Privacy in Citizen Science: Ethical Research in a Context of Openness · CSCW 2017
Collaborative and social computing › information sharing
data sharing
0.312017
Accounting for Privacy in Citizen Science: Ethical Research in a Context of Openness · CSCW 2017
Privacy and data protection › privacy analysis › privacy models
contextual integrity
0.312017
Accounting for Privacy in Citizen Science: Ethical Research in a Context of Openness · CSCW 2017
Privacy and data protection › differential privacy
privacy accounting
0.312017
Accounting for Privacy in Citizen Science: Ethical Research in a Context of Openness · CSCW 2017

Methods — techniques the papers use, named apart from their topics

contextual integrity framework · 0.6
YearPublicationVenuePosition
2017 Accounting for Privacy in Citizen Science: Ethical Research in a Context of Openness
abstract
In citizen science, volunteers collect and share data with researchers, other volunteers, and the public at large. Data shared in citizen science includes information on volunteer location or other sensitive personal information; yet, volunteers do not typically express privacy concerns. This study uses the framework of contextual integrity to understand privacy accounting in the context of citizen science, by analyzing contextual variables including roles; information types; data flows and transmission principles; and, uses, norms, and values. Findings show that uses, norms, and values-including core values shared by researchers and public volunteers, and the motivations of individual volunteers' have a significant impact on privacy accounting. Overall, citizen science volunteers and practitioners share and promote openness and data sharing over protecting privacy. Studying the context of citizen science offers an example of contextually-appropriate data sharing that can inform broader questions about research ethics in an age of pervasive data. Based on these findings, this paper offers implications for designing data and information flows and supporting technologies in public and voluntary data sharing projects.
Anne Bowser, Katie Shilton, Jennifer Preece, Elizabeth Muthoni Warrick
CSCW4