Publications

Jump to full list, reports, blogs and popular press.

Highlights

A Nutritional Label for Rankings

A Web-based application that generates a “nutritional label” for rankings. Ranking Facts is made up of a collection of visual widgets that implement our latest research results on fairness, stability, and transparency for rankings, and that communicate details of the ranking methodology, or of the output, to the end user.

Ke Yang, Julia Stoyanovich, Abolfazl Asudeh, Bill Howe, HV Jagadish and Gerome Miklau

Proceedings of ACM SIGMOD (demo), 2018

Online Set Selection with Fairness and Diversity Constraints

Selection algorithms usually score individual items in isolation, and then select the top scoring items. However, often there is an additional diversity objective. Since diversity is a group property, it does not easily jibe with individual item scoring.

Julia Stoyanovich, Ke Yang and HV Jagadish

Proceedings of EDBT, 2018

DataSynthesizer: Privacy-preserving synthetic datasets

To facilitate collaboration over sensitive data, we present DataSynthesizer, a tool that takes a sensitive dataset as input and generates a structurally and statistically similar synthetic dataset with strong privacy guarantees.

Haoyue Ping, Julia Stoyanovich and Bill Howe

Proceedings of SSDBM, 2017

Fides: A platform for responsible data science

We see a need for a data sharing and collaborative analytics platform with features to encourage (and in some cases, enforce) best practices at all stages of the data science lifecycle. We propose Fides, in the context of urban analytics, outlining a systems research agenda in responsible data science.

Bill Howe, Julia Stoyanovichi, Serge Abiteboul, Gerome Miklau, Arnaud Sahuguet and Gerhard Weikum

Proceedings of SSDBM, 2017

 

Full List

On Obtaining Stable Rankings
Abolfazl Asudeh, H. V. Jagadish, Gerome Miklau, and Julia Stoyanovich
CoRR abs/1804.10990 (2018)

Panel: A Debate on Data and Algorithmic Ethics
Julia Stoyanovich, Bill Howe, H. V. Jagadish, Gerome Miklau
PVLDB 11(12): 2165-2167 (2018)

Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151)
Serge Abiteboul, Marcelo Arenas, Pablo Barceló, Meghyn Bienvenu, Diego Calvanese, Claire David, Richard Hull, Eyke Hüllermeier, Benny Kimelfeld, Leonid Libkin, Wim Martens, Tova Milo, Filip Murlak, Frank Neven, Magdalena Ortiz, Thomas Schwentick, Julia Stoyanovich, Jianwen Su, Dan Suciu, Victor Vianu, Ke Yi
Dagstuhl Manifestos 7(1): 1-29 (2018)

A Technical Research Agenda in Data Ethics and Responsible Data Management
Julia Stoyanovich, Bill Howe, and HV Jagadish
Proceedings of ACM SIGMOD, 2018

RC-Index: Diversifying Answers to Range Queries
Yue Wang, Alexandra Meliou, and Gerome Miklau
PVLDB 11(7), 2018

A Nutritional Label for Rankings
Ke Yang, Julia Stoyanovich, Abolfazl Asudeh, Bill Howe, HV Jagadish and Gerome Miklau
Proceedings of ACM SIGMOD (demo), 2018

Online Set Selection with Fairness and Diversity Constraints
Julia Stoyanovich, Ke Yang and HV Jagadish
Proceedings of EDBT, 2018

MobilityMirror: Bias-Adjusted Synthetic Transportation Datasets
Luke Rodriguez, Babak Salimi, Haoyue Ping, Julia Stoyanovich and Bill Howe
BiDU, 2018

Diversity in Big Data: A Review
Marina Drosou, HV Jagadish, Evaggelia Pitoura and Julia Stoyanovich
Big Data Special Issue on Social and Technical Trade-Offs, June 2017

Measuring fairness in ranked outputs
Ke Yang and Julia Stoyanovich
Proceedings of SSDBM, 2017

DataSynthesizer: Privacy-preserving synthetic datasets
Haoyue Ping, Julia Stoyanovich and Bill Howe
Proceedings of SSDBM, 2017

Fides: A platform for responsible data science
Bill Howe, Julia Stoyanovichi, Serge Abiteboul, Gerome Miklau, Arnaud Sahuguet and Gerhard Weikum
Proceedings of SSDBM, 2017

Data, responsibly: fairness, neutrality and transparency in data analysis
Julia Stoyanovich, Serge Abiteboul and Gerome Miklau
Proceedings of EDBT, 2016

Collaborative Access Control in WebdamLog
Vera Zaychik Moffitt, Julia Stoyanovich, Serge Abiteboul, Gerome Miklau
Proceedings of ACM SIGMOD, 2015

Rule-Based Application Development using Webdamlog
Serge Abiteboul, Emilien Antoine, Gerome Miklau, Julia Stoyanovich, and Jules Testard
Proceedings of SIGMOD, 2013

Making Interval-Based Clustering Rank-Aware
Julia Stoyanovich, Sihem Amer-Yahia and Tova Milo
Proceedings of EDBT, 2011

On Provenance and Privacy
Susan Davidson, Sanjeev Khanna, Sudeepa Roy, Julia Stoyanovich, Val Tannen, Yi Chen
Proceedings of ICDT, 2011

Reports

Data, Responsibly (Dagstuhl Seminar 16291)
Serge Abiteboul, Gerome Miklau, Julia Stoyanovich and Gerhard Weikum

Schloss Dagstuhl Seminar Report 2016

Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151)
Serge Abiteboul, Marcelo Arenas, Pablo Barceló, Meghyn Bienvenu, Diego Calvanese, Claire David, Richard Hull, Eyke Hüllermeier, Benny Kimelfeld, Leonid Libkin, Wim Martens, Tova Milo, Filip Murlak, Frank Neven, Magdalena Ortiz, Thomas Schwentick, Julia Stoyanovich, Jianwen Su, Dan Suciu, Victor Vianu, Ke Yi

Schloss Dagstuhl Seminar Report 2016 (full), SIGMOD Record (abridged)

An Algorithmic Approach to Correct Bias in Urban Transportation Datasets
October 30, 2018

Testimony of Julia Stoyanovich before the New York City Council Committee on Technology regarding Automated Processing of Data (Int. 1696-2017)
October 16, 2018

NYC Has An Algorithm Ethics Task Force, And Drexel Prof Julia Stoyanovich Is Involved
May 30, 2018

Refining the Concept of a Nutritional Label for Data and Models
Julia Stoyanovich and Bill Howe Freedom to tinker blog

University Researchers Use ‘Fake’ Data for Social Good
Bill Howe November 7, 2017

Julia Stoyanovich on the importance of many perspectives at the Data for Good Exchange
Tech at Bloomberg, July 7, 2017

Plaidoyer pour une analyse responsable des données
Serge Abiteboul and Julia Stoyanovich Le Monde, October 12, 2015

Revealing Algorithmic Rankers
Julia Stoyanovich and Ellen P. Goodman Freedom to tinker blog

The Data, Responsibly Manifesto
Serge Abiteboul and Julia Stoyanovich ACM SIGMOD blog