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HBO/WO

MBO

10 oktober 2023

Personal Data under the GDPR

This video explains when (research) data can be considered personal data. It is part of Utrecht University's online module Privacy Basics for Researchers (https://zenodo.org/doi/10.5281/zenodo.7930571).

Video

Universiteitsbibliotheek Utrecht

10 augustus 2023

Research Data Management: Personal data and anonymization

Personal data Many researchers process (collect/study/store/share) personal data when conducting their research. Anonymisation and pseudonymisation Applying anonymizing and pseudonymizing techniques is a measure you must take to protect the privacy of research respondents. Definitions Informing participants Another very important measure is to be transparent with your research participants about which personal data you plan to process (collect/study/store/share) for which reason and at what point you will anonymize the data. Related. Suggested.

Website

Erasmus University Library

23 augustus 2023

Lecture: Governance and Stewardship, Key Stakeholders and Personal data Management

Understand the concept of Governance and Stewardship, Key Stakeholders and Personal data Management Understanding of related techniques and approaches

Website

HCAIM Consortium

31 mei 2023

Data Privacy Handbook

The Data Privacy Handbook is a practical guide on handling personal data in scientific research, primarily written for Utrecht University researchers and research support staff in the Netherlands. It is an initiative of Research Data Management Support, in collaboration with privacy and data experts at Utrecht University. The Data Privacy Handbook consists of: A knowledge base which explains how the EU General Data Protection Regulation (GDPR, Dutch: Algemene Verordening Gegevensbescherming) applies to scientific research, including guidelines and good practices in carrying out GDPR-compliant scientific research; An overview of privacy-enhancing techniques & tools and practical guidance on their implementation; Use Cases in the form of research projects with privacy-related issues, for which a reusable solution (e.g., tool, workflow) is shared.

Website

Universiteitsbibliotheek Utrecht

2 maart 2024

Data management

Introductie op research data management, met onder meer aandacht voor Open Science, FAIR data management, een aantal praktische tips en persoonlijke data. De slides zijn voorzien van het UvA-logo, en een aantal slides hebben betrekking op de lokale situatie van de UvA.

Presentatie

Casper Fermin, Joost Oosterhuis, Ira Lenters

4 januari 2021

Sharing information on genetic makeup for big data analysis

Imagine working at a lab that runs diagnostics on the genetic makeup of individual persons in combination with other individual information, e.g., personal habits and living conditions etc. The amount of data you collect on individuals over time is extensive, and it can be used for general big data analyses as well as for individual risk assessments. How should access to this data and to respective analyses be handled?

Document

Michael Kühler, Lavinia Marin

10 augustus 2023

Research Data Management: Data classification

Data classification While writing your dissertation you may (re)use existing data or create new data. These data sets may contain sensitive data. Sensitive data is frequently classified as: public, internal, confidential or secret. The data classification is important as it determines how you store, share and publish your data. Example of classification of sensitive data. Sharing data Sensitive data identifies individuals, species, objects or locations, and carries a risk of causing discrimination, harm or unwanted attention. Related.

Website

Erasmus University Library

10 augustus 2023

Research Data Management: Research data management

Research data management Research data management (RDM) is an important topic with increasing relevance for academics. Due to recent examples of researchers committing fraud by falsifying or manipulating research data, this topic has attracted a lot of attention. These examples of fraud resulted in a Taskforce Scientific Integrity at the EUR, which recommended the introduction of research data management for researchers. For students, it has led to stricter supervision and attention to plagiarism. Benefits Basic elements of data management In each stage of the research life cycle different requirements are identified. Related. Suggested.

Website

Erasmus University Library

10 augustus 2023

Research Data Management: Citing data

Citing data In this module we'll explain why and how to cite datasets. Once you've establised a link between your publication and the underlying data anyone reading the publication will be able to find the dataset. Also, anyone looking at your data is able to find your publication. How to cite data So which elements are essential for other people to identify and retrieve your data? Sometimes additional elements may be requested, but be sure to include at least the following items. Digital Object Identifier (DOI) A DOI is a digital identifier of an object. It enables an object to be identified and found on the Internet. The metadata of the object are stored together with the DOI and includes information about where the object is located on the Internet. If the object is moved to a new location, the metadata can be updated with the new URL of the object. A DOI therefore provides a more long-lasting and reliable reference for finding an online publication than a URL. Related.

Website

Erasmus University Library

10 augustus 2023

Research Data Management: Open Data

What is Open Data? Open Data is data that anyone can access, use and share. Open Data challenges intelligent and creative minds to provide societal value. Open Data applications allow us to make better use of existing resources and create new products and services. Open Data is also one of the cornerstones of Open Science, a concept central to science practitioners and policy makers of today, promoting (re)use of research data and results amongst scientists, the business community and society as a whole. Open Data and academic research In academia, Open Data are used in humanities and cultural heritage research communities (e.g. Journal of Open Humanities Data (JOHD), Europeana); Open Data are also common in the life sciences (e.g. Elixer) and in economics (e.g. World Bank). Some open datasets can be useful to explore societally relevant questions relevant to current policy debates and topics of interest to specific demographics. Open Data is also important for educational purposes (e.g., see Bishop & Kuula-Luumi, 2017). Open Data applications Open Data helps to create (new) value for societies, citizens and businesses. There are now several examples of successful startups with innovative applications of Open Data. Appealing examples are available in health, transport, energy and the environmental sector (see ODINE for examples). I want to work with Open Data. Where to start, who to contact? A good starting point for information and inspiration on “all things” Open Data is the Open Data Handbook. This online handbook provides case studies, learning resources and networked information on Open Data. Related. Support.

Website

Erasmus University Library