CIVICA
Data Science Seminar Series



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About The Series

The Data Science Seminar series is a multi-disciplinary series focused on applications and methodologies of data science for the social, political, and economic world. Its aim is to allow researchers to share original, new work or work in progress in order to get methodological or technical comments and suggestions.

Shared among the partner institutions of the CIVICA network, this series directly addresses the data science research stream of the CIVICA initiative.

Where

During COVID19 travel restrictions, the series will take place online (e.g. using MS Teams or Zoom).

When

The seminar series will start with regular bi-weekly slots (Wednesdays every other week at 16.00 Central European Time) across regular academic year. The number of meetings can be expanded with the increase of partner institutions.

Seminar Schedule

Here is our tentative seminar series schedule in 2021

  • All
  • Spring 2021
  • Fall 2021

Launch Event

Wednesday, 24 February, 2021

Session 1

Wednesday, 17 March 2021

Session 2

Wednesday, 24 March 2021

Session 3

Wednesday, 07 April, 2021

Session 4

Wednesday, 21 April 2021

Session 5

Wednesday, 05 May 2021

Session 6

Wednesday, 19 May, 2021

Session 7

Wednesday, 02 June 2021

Session 8

Wednesday, 08 September 2021

Session 9

Wednesday, 22 September, 2021

Session 10

Wednesday, 06 October 2021

Session 11

Wednesday, 20 October 2021

Session 12

Wednesday, 3 November 2021

Session 13

Wednesday, 1 December 2021

Partner Institutions

Partner institutions' information and gallery

Hertie School Data Science Lab

The Hertie School Data Science Lab is a research and training hub that tackles societal challenges with computational and data-intensive methods. The Lab's mission is to foster, advance and promote excellence in data science research, education and application to enable better decision-making for the common good. Situated at the Hertie School, a private university at the heart of Berlin, the Data Science Lab prepares exceptional students for leadership positions in government, business and civil society, where they can leverage breakthroughs in data science and artificial intelligence to solve complex challenges of our world today.

LSE Data Science Institute

The Data Science Institute (DSI) forms the institutional cornerstone of the LSE's involvement in data science. Working alongside the academic departments across the School, the DSI's mission is to foster the study of data science and new forms of data with a focus on their social, economic and political aspects. The DSI aims to host, facilitate and promote research in social and economic data science through an annual programme of seminars, workshops and research projects delivered by a range of academic experts and research students.

CEU Department of Network and Data Science

The Department of Network and Data Science at the Central European University carries out research in network science, with a special focus on the foundations and applications of network science to practical data-driven problems. The Department offers a PhD Program and an Advanced Certificate Program in Network Science. Data science tools and the network science approach offer a unique perspective to tackle complex problems, impenetrable to linear-proportional thinking. A key element of the mission of the Department is to work across disciplines to bring network and data science tools to many fields of the social sciences, and related areas.

Bocconi Institute for Data Science and Analytics

The Bocconi Institute for Data Science and Analytics (BIDSA) was established in 2016 to promote and facilitate data-driven research at Bocconi University. BIDSA's aim is to promote and conduct theoretical and applied research that addresses challenging issues arising from the analysis of large-scale datasets and the modeling of the underlying complex phenomena while building a community of high-profile scholars to bridge the gap across Data Science disciplines and support the training of the new generation of data scientists by providing them with advanced statistical, mathematical and computational skills.

Sciences Po médialab

The Sciences Po médialab is an interdisciplinary research laboratory comprised of sociologists, engineers and designers, conducting thematic and methodological research to investigate the role of digital technology in our societies. These research approaches are developed jointly around four main themes: the digital public space, the environmental turn, technological futures and quantitative cultural studies. The médialab is a diverse research team, comprised of men and women with complementary skills. As members or partners of the laboratory, these social sciences, digital methods and design experts join forces and work together to develop research that draws on this diversity.

European University Institute Tech Cluster

The EUI Tech Research Cluster investigates the challenges of profound technological changes with the aim to assist policy makers. The Cluster adopt a global perspective but will focus on the EU’s ability to play a leading role, while preserving its fundamental values. The Cluster's events will engage engineers and computer scientists, academics in social sciences and leaders from industry, government and civil society to discuss which current issues would benefit most from interdisciplinary investigation.

F.A.Q

  • The Data Science Seminar series is a multi-disciplinary series in applications and methodologies of data science focused on applications to the social, political, and economic world. Its aim is to allow researchers to share original, new work or work in progress in order to get methodological or technical comments and suggestions. The focus on the early stage work can potentially lead to collaborations both across partner institutions and with the institutions of invited speakers (if different). This will also differentiate the series from regular research seminars in partner institutions.

    Shared among the partner institutions of the CIVICA network, this series directly addresses the data science research stream of the CIVICA initiative.

  • We recognise that methodological and technical skills are heterogeneous, and that many disciplinary traditions are represented across partner institutions. Our focus will be on recruiting speakers working in data science within a particular field, but focusing on problems that are general enough to be of board interest across other fields. We expect that there will be considerable overlap between those presenting and those commenting on work in this series.

    We also understand that talking about work in progress is more sensitive than presenting a completed work in a seminar, so one possibility is to make this more appealing is to ensure the meeting is 'closed' in some way, for example, in terms of the information participants may talk about freely outside the meeting.

    Culturally, we aim to make these methodological discussions in a collegiate, non-threatening environment. Hence, privacy and gentility in commentary are important. The series will publish a code of conduct and ask all participants to agree to that code prior to participating.

  • Initially the series will start with a regular monthly slot (e.g. first Wednesday of the month at 16.00 Central European Time) across regular academic year, i.e. approximately 10 meetings in a year. The number of meetings can be expanded with the increase of partner institutions.

    During COVID19 travel restrictions, the series will take place online (e.g. using MS Teams or Zoom). The series can subsequently be moved to in-person meetings rotating across partner institutions or a hybrid system (in-person with online streaming). The cost of the meeting in this setting will be covered by CIVICA or the partner institution.

    Schedule of speakers will be done in discussion between partner institutions, with each partner nominating equal number of speakers in proportion to the number of scheduled seminar slots for the year. Nomination of next year’s speakers and scheduling should be complete before the end of the current year’s seminar series.

  • The seminar series may follow two formats.

    In the first, the presentation is structured as a discussion of work circulated and read prior to the meeting taking place. In this “reading seminar” format, authors circulate a brief note or their draft paper beforehand, as well as possible discussion points on which they are seeking feedback, such as how to measure a key concept, find data on a particular topic, or identify the strengths and weaknesses of a particular method, tool, or research design. The authors are welcome to present this during the meeting to start the discussion and the group then jointly discusses this aspect of the problem. When circulating the materials, the authors also mention what they would like to get out of the discussion, which helps to streamline the conversation on the day.

    The second format would be more of a classical seminar where new work is presented, and is followed by a Q&A session.

    The series would alternative between the two formats, making adjustments based on feedback from the first term of experience with the two formats.

  • The intended advantages for the author are a) to discuss their work with an audience outside their immediate subfield, and b) to get focussed comments and suggestions on a part of their work that, while important, would normally be secondary to and in the background of their normal research process. The intended advantage for the audience is a) to be exposed to more of the research happening across partner institutions and beyond, b) to identify new and interesting methodological and technical challenges in perhaps unfamiliar substantive areas, and c) create opportunities for research collaborations.

  • If you are a researcher at one of the institutions within the CIVICA network, information should be made available by the coordinator at your institution. Alternatively, you can sign up for the newsletter below to keep up-to-date about the seminar series.

Newsletter

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