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Swiss Data Science Center

From EverybodyWiki Bios & Wiki





Swiss Data Science Center
File:Swiss Data Science Center (SDSC).png
AbbreviationSDSC
TypeNot for profit research center
PurposeAccelerate and promote the use of data science and machine learning techniques within academic disciplines of the ETH Domain, the Swiss academic community, and the industrial sector.
HeadquartersEPFL Campus, Ecublens
Location
  • 1015 Lausanne, Switzerland
  • 8006 Zurich, Switzerland
Executive director
Olivier Verscheure
Key people
Andreas Krause, Edouard Bugnion
Parent organization
ETH Board
Websitewww.datascience.ch

The Swiss Data Science Center (SDSC) is a joint venture between the Swiss Federal Institute of Technology (ETH) in Zurich (German: Eidgenössische Technische Hochschule Zürich) and the Swiss Federal Institute of Technology (EPFL) in Lausanne (French: École Polytechnique Fédérale de Lausanne), Switzerland.

Its self-proclaimed goal is to accelerate the use of data science, artificial intelligence and machine learning techniques within academic disciplines of the ETH Domain, the Swiss academic community, the Federal research institutes and the industrial and public sectors, and to support Swiss researchers and the industry with the help of Data Science and AI.

History

To ensure that the ETH Domain and Switzerland possess the necessary expertise to remain globally competitive in digitalization and data-driven research, the ETH Board defined Data & Information[1] as one of its 4 strategic action areas for the years 2017 to 2024.[2] As a result, EPFL and ETH Zurich established the SDSC in January 2017.[3][4]

Organization

The SDSC has offices in three locations: at EPFL in Lausanne, at ETH in Zurich, and at the Paul Scherrer Institute (PSI) in Villigen, dedicated to Data Science for large-scale scientific infrastructures.[5] The center is led by an executive director, Olivier Verscheure,[6] and two academic co-directors. The SDSC collaborates with SWITCH and the CSCS for the data infrastructure (e.g. servers, network, authentication).

Main activities

AI for science through collaborative research projects

Many approaches, including machine learning and deep learning techniques, are often challenging to exploit in real-world applications, given their complexity and fast-paced progress.[7] For researchers working on methodological aspects of data science, applying their newly developed techniques to concrete problems requires setting up sizable collaborative projects, which are challenging to undertake and sustain alone.[8]

The SDSC Collaborative Data Science Projects seeks to help researchers and domain experts leverage new techniques in Data Science, to develop models and perform analyses to support their research.

AI for innovation through collaborative industry projects

The competitiveness of Swiss businesses increasingly depends on integrating Data Science and AI in their processes.[9]

The SDSC positions itself as an education and training platform to foster the adoption of AI and Data Science in the private sector, looking to help data scientists solve business challenges, and increasing data literacy within companies. Launched in 2019, the SDSC Industry Unit has set up partnerships with Swiss companies, covering a range of business areas.

The SDSC Industry Unit organizes a yearly event called SDSC Connect[10] for the public (held online in 2020 and 2021 due to sanitary restrictions).

Industry partners include Roche, Bühler Group,[11] Merck Group, Richemont, Firmenich, Romande Energie, PSA Group, etc.

Open-research data (ORD) platforms for AI

Renku[12] is an open-source software platform designed to facilitate data and knowledge exchange between all the actors involved in data science collaborations. Data analysis projects can be discussed, repeated and verified, and split up into components that can be individually shared, reused, and recombined. It provides traceability and transparency in provenance information, allowing (data) scientists to validate the results' quality and integrity. Provenance enables users to replicate the science and confidently reuse the results in their derivative work with all the proper accreditation and attribution. The platform is designed to encourage best practices in line with the Findable, Accessible, Interoperable, Reusable (FAIR data) principles,[13] and in line with the Swiss National Open Research Data Strategy as commissioned by the State Secretariat for Education, Research and Innovation (SERI) in January 2020.[14]

Renku's ability to share an identical work environment fosters its usage beyond the initial research scope. It is being used to teach classes in various fields, from Bioinformatics to Data Science, at EPFL, ETH Zurich, University of Fribourg, UC Louvain, and Harvard University. Using this platform, teachers and students can avoid manually setting up a common environment and share the same datasets and tools within minutes instead.

The name Renku derives from the Japanese Renku (連句, "linked verses") which is a type of collaborative poetry made of linked verses.

PSI hub for large scale infrastructure

A collaboration between the PSI and the SDSC, launched in 2021, addresses the challenge of the large amount of data produced by large-scale research facilities of the Paul Scherrer Institute (PSI).[15] The SDSC Hub at PSI promotes and accelerates the use of supercomputer services as provided by the Swiss National Supercomputing Centre (CSCS) for the analysis of high-volume scientific data.

Teaching and training

SDSC members teach several courses in Data Science and Machine Learning at EPFL and ETH Zurich for Bachelor and Master students in Data Science, Computer Science, Electrical Engineering, and Mathematics,[16] as well as a Diploma of Advanced Studies (DAS) in Data Science from ETH Zurich[17] and the Certificate of Advanced Studies (CAS) in Data Science & Management,[18] a joint Executive Program from EPFL and the business school at the University of Lausanne.

Collaboration with the Swiss federal administration

The SDSC is assisting Swiss federal offices in their digitalization journey and open data policy,[19] particularly the Federal Office of Public Health (FOPH), the Federal Office of Energy (SFOE), and the Federal Statistical Office (FSO). In 2021, the FSO and the SDSC entered a strategic partnership,[20][21][22] to support the creation of a competence center aimed at delivering data science "as-a-service" to the Swiss federal offices - the Data Science Competence Center (DSCC).[23]

COVID-19 forecasting tool

In 2021, Antoine Flahault,[24][circular reference] researcher and epidemiologist at the Institute of Global Health of the Faculty of Medicine of the University of Geneva[25] and the SDSC entered into a collaboration to help disseminate COVID-19 data and scientific results to key scientists and stakeholders while ensuring the integrity of the underlying sensitive data.[26] The center also powers the a COVID-19 Daily Epidemic Forecasting dashboard[27] and a Daily Risk Map,[28] becoming a worldwide reference to predict the evolution of the coronavirus in 209 countries.[29][30]

See also

References

  1. ↑ "Data and information". 31 August 2023.
  2. ↑ "Strategic action areas". ethz.ch.
  3. ↑ "«Big Data» in der Forschung - Neues Zentrum für Datenwissenschaften". Schweizer Radio und Fernsehen (SRF). February 6, 2017.
  4. ↑ "L'EPFL et l'EPFZ lancent un centre de science des données". Tribune de Genève – via www.tdg.ch.
  5. ↑ "Les EPF auront un troisième hub pour la data science". 30 April 2021.
  6. ↑ "Wie Unternehmen die Datenwissenschaften für sich nutzen können". 30 June 2021.
  7. ↑ Alzubaidi, Laith; Zhang, Jinglan; Humaidi, Amjad J.; Al-Dujaili, Ayad; Duan, Ye; Al-Shamma, Omran; Santamaría, J.; Fadhel, Mohammed A.; Al-Amidie, Muthana; Farhan, Laith (2021). "Review of deep learning: Concepts, CNN architectures, challenges, applications, future directions". Journal of Big Data. 8 (1): 53. doi:10.1186/s40537-021-00444-8. PMC 8010506 Check |pmc= value (help). PMID 33816053 Check |pmid= value (help).
  8. ↑ "Data Science Methodology Program". July 2015.
  9. ↑ https://www.satw.ch/fileadmin/user_upload/documents/02_Themen/08_Kuenstliche-Intelligenz/SATW-Swiss_AI_Strategy.pdf [bare URL PDF]
  10. ↑ "SDSC-Connect | Overcoming key challenges in the digital transformation". sdsc-connect.ch.
  11. ↑ "Bühler s'appuie sur le Machine Learning pour trier le bon grain de l'ivraie". 2 February 2018.
  12. ↑ "Renku". renkulab.io.
  13. ↑ "FAIR Principles". GO FAIR.
  14. ↑ "National Strategy and Action Plan - swissuniversities".
  15. ↑ "Growth in the data sciences | Our Research | Paul Scherrer Institut (PSI)". www.psi.ch. April 28, 2021.
  16. ↑ "Data scientist, le métier du siècle".
  17. ↑ "DAS in Data Science". inf.ethz.ch.
  18. ↑ "Open program in Data science & management (CAS) | HEC Lausanne". Executive Education HEC Lausanne.
  19. ↑ "Data science and artificial intelligence for the public good". ethz.ch. 25 March 2021.
  20. ↑ "The federal institutes of technology and the FSO join forces in data science and artificial intelligence for the public good - Competence centre for data science: New cooperation | Press release". 25 March 2021.
  21. ↑ "Bund stärkt KI-Kompetenzen mit Hilfe der ETHs".
  22. ↑ "L'OFS s'appuie sur le Swiss Data Science Center pour ses services en sciences des données". 25 March 2021.
  23. ↑ Office, Federal Statistical. "Data Science Competence Center (DSCC)". www.bfs.admin.ch.
  24. ↑ "Antoine Flahault".
  25. ↑ "SANTÉ PUBLIQUE". www.unige.ch. July 16, 2015.
  26. ↑ Petropoulos, Fotios; Makridakis, Spyros; Stylianou, Neophytos (2022). "COVID-19: Forecasting confirmed cases and deaths with a simple time series model". International Journal of Forecasting. 38 (2): 439–452. doi:10.1016/j.ijforecast.2020.11.010. ISSN 0169-2070. PMC 7717777 Check |pmc= value (help). PMID 33311822 Check |pmid= value (help).
  27. ↑ https://renkulab.shinyapps.io/COVID-19-Epidemic-Forecasting/_w_5e1a0663/_w_5a357a15/?tab=about
  28. ↑ "COVID-19 Forecasting". renkulab.shinyapps.io.
  29. ↑ "La success-story d'un site qui prédit l'avenir du Covid". 7 January 2021.
  30. ↑ "Big data en temps de pandémie – le site web qui fait la météo du Covid". 5 May 2021.
  31. ↑ "Swissuniversities - swissuniversities".


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