606 zoekresultaten voor “data science research programme” in de Medewerkerswebsite
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Data Science Research Programme
Universities, companies, organisations and societies are increasingly facing enormous quantities of data. It is a great challenge to transform these Big Data into knowledge, which is why Leiden University has launched a University-wide Data Science Research Programme.
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Leiden University launches Data Science research programme
Leiden University is investing 4 million euros in a new Data Science research programme. This is a joint initiative of all the faculties, headed by Dean Geert de Snoo at the Faculty of Science. The programme will focus on Leiden scientific data.
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Wessel Kraaij
Wiskunde en Natuurwetenschappen
w.kraaij@liacs.leidenuniv.nl | +31 71 527 5778
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Symposium Data Science Research Programme
Congres/symposium
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Migrating research data
Do you need help migrating your research data?
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Archaeology thanks to computer-based research
A mix of data research, artificial intelligence and archaeology led to lively discussions on 31 January. On that day the unique event 'AI & Data Science @ Archaeology' took place in which the Data Science Research Programme (DSRP), SAILS and the Faculty of Archaeology joined forces.
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A digital eye for archaeologists
Wouter Verschoof-van der Vaart is refining an artificial intelligence system that can detect and classify archaeological objects on digital images. Such a system is desperately needed because human archaeologists around the world are being flooded with data.
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Personal data
As a university employee, you probably work with personal data. That is not just names and telephone numbers – it can also include things like cookies. How can you make sure you are working in a privacy-proof way?
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Personal data
Leiden University has access to personal data of both employees and students. This information is processed and stored in a number of ways. The University deals with personal data responsibly and in accordance with the Personal Data Protection Act.
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Data management
Data management can be defined as the creation, storage, maintenance, disclosure, archiving and sustainable preservation of research data.
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Data storage
Research data must be securely preserved, during but also after your research. Read about data management, data retention and open science.
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Workshop 'Privacy for researchers:data protection in a changing world'
ICT, Onderzoek
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Responsible and transparent data science
Data science is used in almost every academic discipline. This presents plenty of new opportunities, but new dilemmas too. Reason enough for the symposium on 5 March: ‘Fairness and Transparency, towards responsible data science.’ Keynote speaker Ricardo Baeza-Yates gives a sneak preview.
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Privacy and data breaches
Any loss of control over stored personal data constitutes a potential data leak. In most cases this concerns stolen (or lost) digital files, but a stolen (or mislaid) printed list containing personal data also represents a data leak. It is important that you report any data leak.
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Data processing agreement
If you bring in a (new) person who will be processing personal data for you, this person is not allowed to use this information for his or her own purposes. You need to formalise this in a data processing agreement. The university will usually have an agreement in place.
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Data processing register
A data processing register is a record of which personal data you process and who you share this data with. If you collect personal data for your research, you must record this in the data processing register.
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Deleting personal data
In certain cases, people have the right to require the university to delete their personal data, for example if the university no longer needs the information or if someone withdraws their permission to use the information.
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Storage and data recovery
As a standard, your workplace comes equipped with a limited amount of disk space. We offer a number of options for extending your disk space. In addition, ISSC can help you recover lost files.
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Data analysis software
Data analysis is the process of converting raw data into information that can be used to answer research questions. To help you interpret your raw data SOLO Research and Lab Support supports different types of data analysis software.
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Physiological data acquisition
How does a human subject respond physiologically during an experiment? Measuring these responses offers valuable data. Heart rate, brain activity, skin response and eye moment can al be measured using various types of equipment.
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Collecting physiological data
How does a human subject respond physiologically during and experiment? Measuring these responses offers valuable data.
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Long-term data retention
Once the research has been completed, the research data must be retained securely for the long term. This means that the integrity, availability and – if required – confidentiality of the data must be guaranteed.
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One-off data processing
Are you handling personal data just once, for instance when taking the minutes of a meeting or organising an employee outing? You do not need to include this use in the data processing register if you stick to the following conditions.
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General Data Protection Regulation (GDPR)
The General Data Protection Regulation (GDPR) has been in force since 25 May 2018. Whenever you work with personal data, you have to record what happens to this data. The university will support you in working in a privacy-proof way.
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Matthijs van Leeuwen
Wiskunde en Natuurwetenschappen
m.van.leeuwen@liacs.leidenuniv.nl | +31 71 527 7048
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'Data science enables us to develop new tools'
PhD students Alex Brandsen and Wouter Verschoof-van der Vaart are both doing a project within the university’s Data Science research programme. The are introducing terms like ‘text mining’ and ‘advanced machine learning’ into archaeology. ‘These techniques will make archaeology more efficient and ch…
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Science
During an evacuation, employees and students of the Science Faculty gather at the following assembly points:
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Gineke Wiggers
Faculteit Rechtsgeleerdheid
g.wiggers@law.leidenuniv.nl | +31 71 527 8838
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Workshop: How to write a Data Management Plan (DMP)
Cursus
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Workshop: How to write a Data Management Plan (DMP)
Cursus
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Workshop: How to write a Data Management Plan (DMP)
Cursus
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Workshop: How to write a Data Management Plan (DMP)
Cursus
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Marta Fiocco
Wiskunde en Natuurwetenschappen
m.fiocco@math.leidenuniv.nl | +31 71 527 7119
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Rianne de Heide
Wiskunde en Natuurwetenschappen
r.de.heide@math.leidenuniv.nl | +31 71 527 4844
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Botond Szabo
Wiskunde en Natuurwetenschappen
b.t.szabo@math.leidenuniv.nl | +31 71 527 2727
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Laura Zwep
Wiskunde en Natuurwetenschappen
l.b.zwep@lacdr.leidenuniv.nl | +31 71 527 3529
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Amine Hadji
Wiskunde en Natuurwetenschappen
m.a.hadji@math.leidenuniv.nl | +31 71 527 5863
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Peter Grünwald
Wiskunde en Natuurwetenschappen
pdg@math.leidenuniv.nl | +31 71 527 7047
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Gino Bertrand Kpogbezan
Wiskunde en Natuurwetenschappen
g.b.kpogbezan@math.leidenuniv.nl | +31 71 527 7109
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Magnus Münch
Wiskunde en Natuurwetenschappen
m.m.munch@math.leidenuniv.nl | +31 71 527 2727
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Jelle Goeman
Faculteit Geneeskunde
j.j.goeman@lumc.nl | +31 71 526 9700
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Kevin Duisters
Wiskunde en Natuurwetenschappen
k.l.w.duisters@math.leidenuniv.nl | +31 71 527 2727
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Gregory Chen
Wiskunde en Natuurwetenschappen
x.chen@math.leidenuniv.nl | +31 71 527 2727
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Thijs Bos
Wiskunde en Natuurwetenschappen
j.m.bos@math.leidenuniv.nl | +31 71 527 7047
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Stéphanie van der Pas
Wiskunde en Natuurwetenschappen
svdpas@math.leidenuniv.nl | +31 71 527 7134
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Johannes Schmidt-Hieber
Wiskunde en Natuurwetenschappen
schmidthieberaj@math.leidenuniv.nl | +31 71 527 2727
- Data management & open access
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Open Science
Open Science is an umbrella term for an approach that aims to make scientific research accessible, reproducible, and freely available to people within and outside of academics.
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Wouter van Loon
Faculteit der Sociale Wetenschappen
w.s.van.loon@fsw.leidenuniv.nl | +31 71 527 7330
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More powerful data centre will accelerate research
Language evolution, targeted drugs or archaeological interpretation. Researchers are making increasing use of supercomputers that can rapidly process large quantities of data. This is one reason why the University data centre will be extended and updated. ‘Datamining means we can get a better picture…