Responsible Data Science for Search Engines & Statistics (Event 09)

Date: Thursday 15 June

Time: 16:00-17:30

Location: VU Amsterdam Main Building (1st Floor): HG-01A33

16:00-16:05 Introduction & Overview on Responsible Data Science by Frank van Harmelen, Professor in Knowledge Representation & Reasoning, Department of Computer Science, VU

16:05-16:30 Speaker 1: Maarten de Rijke, Professor in Information Retrieval, Informatics Institute (UvA) on Explainable Search Engines

16:30-16:55 Speaker 2: Piet J.H. Daas, Senior methodologist, Research coordinator Big Data & lead Data Scientist at the Center for Big Data Statistics on Responsible Data Science at Statistics Netherlands: implications for big data research?

The mission of Statistics Netherlands (in Dutch: “Centraal Bureau voor de Statistiek”) is to publish reliable and consistent statistical information. At the office  we are used to working with privacy sensitive data, have to be transparent and want to produce the best estimates possible. In that sense, this should also apply to big data based statistics.  In the presentation the standard way of working, the implications for the big data research performed and examples of our work will be discussed.

16:55-17:00 Wrap-up

17:00 – Networking and drinks

17:30 – Close

***

On 15 June, we will hold our monthly seminar series on Responsible Data Science (RDS), a joint collaboration of expert researchers from 11 knowledge institutions across the Netherlands:  Academisch Medisch Centrum (AMC), Centrum Wiskunde en Informatica (CWI), Delft University of Technology (TUD), Eindhoven University of Technology (TU/e), Leiden University (LU), Leiden University Medical Center (LUMC), Radboud University Nijmegen (RU), Tilburg University (UvT), University of Amsterdam (UvA), VU Medical Center Amsterdam (VUmc), VU University Amsterdam.

The RDS initiative is driven by the omnipresence of data making society increasingly dependent on data science. Despite its great potential, there are also many concerns on irresponsible data use. Unfair or biased conclusions, disclosure of private information, and non-transparent data use, may inhibit future data science applications.

***

The RDS programme aims at generating scientific breakthroughs by making data science responsible by design. In RDS researchers from multiple disciplines connect to develop techniques, tools, and approaches to ensure fairness, accuracy, confidentiality, and transparency.

Big data is changing the way we do business, socialize, conduct research, and govern society. Data are collected on anything, at any time, and in any place. Organizations are investing heavily in Big data technologies and data science has emerged as a new scientific discipline providing techniques, methods, and tools to gain value and insights from new and existing data sets. Data abundance combined with powerful data science techniques has the potential to dramatically improve our lives by enabling new services and products, while improving their efficiency and quality. Many of today’s scientific discoveries (e.g., in health) are fuelled by developments in statistics, data mining, machine learning, databases, and visualization.

For more information see the Responsible Data Science website HERE

Please note all our Meet-up events are open to all to attend, just register on our Meet-up page and RSVP to the specific event you would like to attend.