Data Ecology: Understanding and Designing Data Ecosystems

Data profoundly shapes our economic, political, and social ecosystems, yet we have limited control over its influence. Unchecked dataflows among agents can distort or undermine these ecosystems. Analyzing dataflows helps us understand their use and misuse, revealing opportunities to harness their value. Beneficial dataflows, such as hospitals sharing patient data, enhance healthcare outcomes, while harmful dataflows, such as personal data sold to self-interested brokers, cause substantial damage. Equally critical are absent dataflows-such as banks or governments withholding data due to competition or mistrust-that lead to unrealized value. Despite their substantial impact, unified methods to manage dataflows effectively are lacking. Current legal (regulations), economic (incentives), and technical (privacy technologies) interventions are developed independently without a clear evaluation of their collective effectiveness.

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Publication Details

Journal
ACM SIGMOD Record
Published
2026-01-19
DOI
https://doi.org/10.1145/3793217.3793225
Primary Topic
Information Systems Theories and Implementation
Type
article
Field-Weighted Citation Impact
0.00
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article

Data Ecology: Understanding and Designing Data Ecosystems

Ronield Fernandez
ACM SIGMOD Record
Information Systems Theories and Implementation
article

Data Ecology: Understanding and Designing Data Ecosystems

Ronield Fernandez
article en

Abstract

Data profoundly shapes our economic, political, and social ecosystems, yet we have limited control over its influence. Unchecked dataflows among agents can distort or undermine these ecosystems. Analyzing dataflows helps us understand their use and misuse, revealing opportunities to harness their value. Beneficial dataflows, such as hospitals sharing patient data, enhance healthcare outcomes, while harmful dataflows, such as personal data sold to self-interested brokers, cause substantial damage. Equally critical are absent dataflows-such as banks or governments withholding data due to competition or mistrust-that lead to unrealized value. Despite their substantial impact, unified methods to manage dataflows effectively are lacking. Current legal (regulations), economic (incentives), and technical (privacy technologies) interventions are developed independently without a clear evaluation of their collective effectiveness.

ACM SIGMOD RecordVol. 54(4)
University of Chicago (US)
Life in Land
Openalex Percentile: Top 84%
Information Systems Theories and Implementation
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