1,275 search results for “fair data” in the Public website
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FAIR data
Open Science means not only sharing final research results but also the underlying data. A main way to do that is by making research data FAIR: Findable, Accessible, Interoperable and Reusable.
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Leiden: Silicon Valley of FAIR data
If researchers make their data FAIR, computers can link large quantities of data and identify patterns, thus greatly accelerating the process of arriving at new insights. In Leiden, the birthplace of ‘FAIR data’, Professor Barend Mons explains the meaning of this term.
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FAIR Surveys Project
This project aims to contribute to the improvement of documentation and archiving standards (conform the FAIR principles) for systematic Mediterranean archaeological field survey.
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Metabolomics Implementation Network launched for fair data
On 10 March 2017, Professor Karel Luyben (TU Delft) welcomed the ‘Metabolomics GO FAIR Implementation Network’ as community initiative to start the European Open Science Cloud. The network aims to implement the FAIR data principles in the field of metabolomics in Europe.
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Barend Mons
Faculteit Geneeskunde
b.mons@lumc.nl |
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VODAN Africa – FAIR Covid-19 Data across Africa and Asia
VODAN Africa started as a platform to enable access to critical data needed from Africa to fight the novel COVID-19. The initiative was inspired by the experience from the Liberia Ebola Virus outbreak in 2014: early detection requires contact tracing. Inclusion of the most vulnerable is critical to…
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GO FAIR Implementation Network Africa launched in Leiden
On 22 August, the GO-FAIR IN Africa was launched: an implementation network under the GO FAIR efforts to train, build and change the next generation of the Internet of FAIR Data and Services (IFDS).
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Impact Fair
Leiden University will participate in the second edition of the Impact Fair, for everyone who wants to contribute positively to the world of tomorrow and is looking for inspiration.
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Jaap-Willem Mink
Faculteit der Sociale Wetenschappen
j.a.b.mink@fsw.leidenuniv.nl | +31 71 527 6801
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Feel at Home Fair
If you've only just come to live in the Netherlands, life can at times be both exciting and difficult. To help you feel at home more quickly, a Feel at Home Fair is being organised in city hall, The Hague on 3 February. Leiden University will be present at the fair. It's a good opportunity to attend…
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Data science and visualisation by the government
On 20 February 2019, a special meeting on data science took place in the House of Representatives. The aim of the meeting was to start a dialogue with government organisations about data developments within the government.
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The FAIR Principles herald more open, transparent, and reusable scientific data
Today, March 15 2016, the FAIR Guiding Principles for scientific data management and stewardship were formally published in the Nature Publishing Group journal Scientific Data.
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Master's students Data Science present solutions to central government and the House of Representatives
On 1 November 2019, international Master's students Data Science from Leiden University presented the elaboration of their data concepts to senior officials of the House of Representatives and Rijks I-Ecosysteem. With the presentation, they successfully completed this part of the Data Science master…
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Data Science
The ability to collect and interpret huge quantities of data has become indispensable to society and academia. Leiden University is a knowledge and expertise centre for data science that places the emphasis on interdisciplinary collaboration and innovation.
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Data Science Seminar for Fairness and Transparency
Data Science seminar at the Faculty of Governance and Global Affairs
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Promoting Fair Vetting in Kenya and Beyond
How do laws and procedures for police vetting unfold in practice?
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Brenda Miranda Xicotencatl
Science
b.miranda.xicotencatl@cml.leidenuniv.nl | +31 71 527 2727
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Reliable and Fair Machine Learning for Risk Assessment
The focus of this thesis is on the technical methods which help promote the movement towards Trustworthy AI, specifically within the Inspectorate of the Netherlands.
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Ethical standards for data science
Computers are becoming so smart that in the future they will perhaps take over the role of judges. In the meantime, experts at Leiden University are examining the question of which standards responsible data science should meet.
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Symposium 'Fairness and Transparency, towards responsible data science'
On March 5, CWTS and the Leiden University Data Science Research Programme will organize the symposium ‘Fairness and Transparency, towards responsible data science’.
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FAIRDOM – FAIR Sharing for Systems and Synthetic Biology
FAIRDOM consortium is an open initiative of various partners including funding programmes, large-consortia, institutes, small groups as well as individuals.
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Katy Wolstencroft
Science
k.j.wolstencroft@liacs.leidenuniv.nl | 071 5278926
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Uncontrollable: Data subject rights and the data- driven economy
On 7 February 2019, Helena Ursic-Vrabec defended her thesis 'Uncontrollable: Data subject rights and the data- driven economy'. The doctoral research was supervised by Prof. dr. S. van der Hof.
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Data Analytics and Management
Our group is part of the Metabolomics and Analytics Centre where we accompany the data from its acquisition all the way to the publication of identified associations and biomarkers for a range of human diseases. The generated data of the metabolic measurements are assessed using an in-house quality…
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Governance and Data Science Group
The extensive use of electronic communication channels and other devices has opened new possibilities for collecting data on human behavior. This information is sometimes openly accessible, but largely part of administrative registration systems that are not open to the broader public. The data provides…
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Tax and Society: Building a Sustainable and Fair Tax System
Tax scandals, like the Panama Papers, the Paradise Papers, and the Pandora Papers, have made taxation a major topic of public debate. Learn more about this in the new minor Tax and Society: Building a Sustainable and Fair Tax System.
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‘For good measure’: data gaps in a big data world
Sarah Giest and Annemarie Samuels, both Assistant Professors at Leiden University, researched the quality and coverage of the data being collected for policiymakers to be used, specifically pertaining to minority groups.
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Joining hands to advance Dutch microscopy
Advanced microscopy to understand life and fight disease: that’s the goal of the new NL-BioImaging network that will develop and integrate state-of-the-art microscopy technologies and services. Researchers from all Dutch universities, including Leiden University and the Leiden University Medical Centre,…
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Fairness matters when responding to disasters: An experimental study of government legitimacy
This article by Honorata Mazepus and Florian van Leeuwen in the journal Governance: An International Journal of Policy, Administration and Institutions looks at how evaluations of authorities were influenced by four aspects of a governmental response to a hypothetical disaster.
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LIFES: From Reusable Data to New Treatments and Faster Diagnoses
Early diagnosis, new treatments, and personalised care: all of these are possible if we can better unlock the wealth of information hidden in health data. Unfortunately, this data is often poorly organised, difficult to access, and not interoperable. The new international Leiden Institute for FAIR and…
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Mariëlle Linting
Faculteit der Sociale Wetenschappen
linting@fsw.leidenuniv.nl | +31 71 527 4098
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The BIAS Project at the Webinar on Intersectional Fairness in AI
Carlotta Rigotti, Postdoc researcher at eLaw, participated in the ‘Intersectional Fairness in AI: Legal Frameworks, Tools, and Learning Opportunities’ webinar on 10 December 2024.
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Publication Helena Ursic en Bart Custers about data reuse
Data reuse and big data: a taxonomy for personal data reuse.
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Inaugural lecture: Data of Value
By comparing individual health data with population data, doctors can provide personalized health advice and patients can learn from each other's experiences. Wessel Kraaij, professor of Applied Data Analytics shows how personal data can have predictive value.
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Akrati Saxena
Science
a.saxena@liacs.leidenuniv.nl | +31 71 527 2727
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DAMIOSO - data mining on high volume simulation output
Modern computer-aided simulation tools used by various industries produce gigabytes of data. But currently, they take days and even up to weeks of computation effort. To make the best use of all these data, the DAMIOSO project focuses on developing algorithms and tools for managing, mining, and optimizing…
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Data
Data Sets Department of Economics
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Enhancing Democracy and Citizens’ Trust in Governance: Adopting a Fair Treatment Approach in Indonesia’s Ombudsman Offices
How can the Indonesian National Ombudsman make the transition from autonomous to responsive justice in view of the day-to-day challenges it is faced with?
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ZonMw – Optimizing the responsible researcher: towards fair and constructive academic advancement
Researchers are pulled in various, sometimes contradictory directions by the multiplication of performance metrics and new incentives to align with societal needs. Management structures, funding systems, and publication practices are increasingly influenced by pressures to promote only the highest quality…
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SAPPAO - Optimizing the flight times of airplanes using data science
The SAPPAO project aims to optimise the accuracy and reliability of predicting scheduled flight times. The full name of the project is 'A Systems Approach towards Data Mining and Prediction in Airlines Operations'.
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Making everything we know computer-readable
Data and information should be stored in a way that computers can understand, says Barend Mons, professor of Biosemantics at the Leiden University Medical Center and Chair of the High Level Expert Group for the European Open Science Cloud. We speak with him about FAIR data, knowlets and nanopublicat…
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Data-Driven Drug Discovery Network (D4N)
The Data-Driven Drug Discovery Network (D4N) is an initiative by researchers from Leiden University and collaborators to join efforts in applying and developing novel techniques from data science to drug discovery and related topics from bioinformatics.
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Exploratory Data Mining in Multimodal data
The change from a closed institution to an open living environment for patients with late stages of dementia will give the patients more freedom in their day-to-day life. The effect of this change on the patients’ mobility, activity and interaction with others will be assessed with sensor technology…
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Inaugural lecture: Data science and Ebola
Today, everybody and everything produces data. People produce large amounts of data in social networks and in commercial transactions. Medical, corporate, and government databases continue to grow. Sensors continue to get cheaper and are increasingly connected, creating an Internet of Things, and generating…
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Mining Sensor Data from Complex Systems
Promotor: J.N. Kok, Co-Promotor: A.J. Knobbe
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Enriching official economic statistics using data-driven modelling techniques
Netherlands Statistics (CBS), Leiden University and the University of Amsterdam have started a collaboration in the form of a research project titled 'Enriching official economic statistics using data-driven modelling techniques'.
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Data Management
LACDR adheres to strict data management rules, with the aim to make our data findable, accessible, interoperable and re-usable. For this reason all LACDR PhD candidates are required to prepare a data management plan and to implement data management rules accordingly. All PhD candidates follow a data…
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Data science
The majority of scientists, from archaeologists through to zoologists, collect enormous volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics and computer science, we can develop algorithms for analyzing…
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Data Science
The majority of scientists, from archaeologists through to zoologists, collect huge volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics, we can develop algorithms for analysing and identifying patterns…
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Data based decision making processes in secondary education
How can teachers be motivated by their students’ data in making stepwise changes to their teaching practices?