Responsible Data Science

Summary: Responsible data science: blending algorithmic/statistical methods with social theories to address socio-technical issues in systems, highlighting relational learning. Survey of challenges, methods, and ethics for DB/ML integration in data systems. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 5665
Venue: SIGMOD
Year: 2019
Pagerank: 6.1034311e-05
Overall Rank: 4,531 | 68.52%
DOI: 10.1145/3299869.3314117

Incoming Non-self Citations Over Time

Authors

1. Lise Getoor

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,746	Do the Rich Get Richer? Fairness Analysis for Blockchain Incentives	2021	SIGMOD	6.7885138e-05
6,462	Tailoring Data Source Distributions for Fairness-aware Data Integration	2021	VLDB	5.0479645e-05
6,895	Identifying Insufficient Data Coverage for Ordinal Continuous-Valued Attributes	2021	SIGMOD	4.8879337e-05

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank

Semantically Similar Papers

Overall Rank	Paper	Year	Venue	Pagerank
6,614	Building Machine Learning Systems that Understand	2016	SIGMOD	4.988814e-05
13,257	Deep Data Integration	2021	SIGMOD	-
7,254	Panel: A Debate on Data and Algorithmic Ethics	2018	VLDB	4.7825086e-05
5,982	Responsible Data Integration: Next-generation Challenges	2022	SIGMOD	5.2409386e-05
13,157	Bridging Disciplines in Data Management Research to Solve Complex Data Problems	2025	VLDB	-
8,340	Deep Learning: Systems and Responsibility	2021	SIGMOD	4.5381546e-05
1,406	Responsible Data Management	2020	VLDB	0.0001216385
13,333	Special Session: A Technical Research Agenda in Data Ethics and Responsible Data Management	2018	SIGMOD	-
13,162	The Limitations of Data, Machine Learning and Us	2024	SIGMOD	-
13,305	The Responsibility Challenge for Data	2019	SIGMOD	-