[Colloquium] [CS] Re: TODAY: Avigdor Gal (Technion)-Loch Data and Other Monsters: on Creating Data Ecosystems, the Intelligent Way

[Rob Mitchum]

If you would like to join today's talk by Zoom, it will be available here:

https://uchicagogroup.zoom.us/j/99678447393?pwd=cU5SM1R2MEh3QlVkazF6YXdkd0ttQT09

Meeting ID: 996 7844 7393
Passcode: 837872

On Mon, Apr 25, 2022 at 9:10 AM Holly Santos <hsantos at uchicago.edu> wrote:

> *Data Science Institute/Computer Science Seminar*
>
> *Avigdor Gal*
> *Benjamin and Florence Free Chaired Professor of Data Science*
>
> *Technion – Israel Institute of Technology *
>
> *TODAY Monday, April 25th*
> *3:00 p.m. - 4:00 p.m.*
> *In Person: John Crerar Library, Room 390*
>
>
> *Loch Data and Other Monsters: on Creating Data Ecosystems, the
> Intelligent Way *
>
> A data ecosystem offers an alliance-driven infrastructure that enables the
> interaction of different stakeholders and the resolution of
> interoperability issues among shared data. Despite years of research in
> data governance and management, trustability is still affected by the
> absence of transparent and traceable data-driven pipelines. Data
> integration is the main facilitator of such data-driven pipelines and
> matching is a task at the heart of any data integration process, aimed at
> identifying correspondences among data elements. Matching problems were
> traditionally performed in a semi-automatic manner, with correspondences
> being generated by matching algorithms and outcomes subsequently validated
> by human experts. Human-in-the-loop data integration has been recently
> challenged by the introduction of big data and recent studies have analyzed
> obstacles to effective human matching and validation. In this talk, we
> focus on the tension between human and machine matching. We propose a novel
> data ecosystem architecture that relies on both human knowledge and machine
> learning and offer a concrete algorithmic solution for effective data
> integration within this architecture. In particular, we shall present the
> limitations of human matching and offer a method for learning to
> characterize reliable and valuable matching experts.
>
> *Bio*: Avigdor Gal
> <https://urldefense.com/v3/__https://agp.iem.technion.ac.il/avigal/__;!!BpyFHLRN4TMTrA!rissONFs9OVtnNuiDLHSXCZOKBQKMda3T_TK_2IlbcGXJT1F-cm3ZzmJgwj1bJ1gGA$> is
> The Benjamin and Florence Free Chaired Professor of data science at the
> Technion – Israel Institute of Technology, where he heads the Big Data
> Integration laboratory. He specializes in various aspects of data
> management and mining with about 150 publications in leading journals,
> books, and conference proceedings. In the current age of big data, his
> research is focused on developing novel models and algorithms for data
> integration. In the past he gave keynotes and tutorials in leading
> conferences in the areas of data and process management. Avigdor Gal is a
> recipient of the prestigious Yannai award for excellence in academic
> education, and multiple best paper and test-of-time awards.
>
> *Host: *Michael Franklin
> ---
> Holly Santos
> Executive Assistant to Michael J. Franklin, Chairman
> Department of Computer Science
> The University of Chicago
> 5730 S Ellis Ave-217   Chicago, IL 60637
> P: 773-834-8977
> hsantos at uchicago.edu
>
>
>
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-- 
*Rob Mitchum*

*Associate Director of Communications for Data Science and Computing*
*University of Chicago*
*rmitchum at uchicago.edu <rmitchum at ci.uchicago.edu>*
*773-484-9890*
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