Admission requrements
Not applicable.
Description
This course explores the use, reuse and reproducibility of data in biomedical science. Biomedical data exists in large and ever-growing distributed data repositories. It is generally produced to answer a specific research question, but it can be reused and integrated to find new insights.
As the volume and variety of biological data grows, we face new challenges in recording, publishing and sharing scientific results in a way that will allow further integration and exploitation. Consequently, data integration, management and reuse are central concerns in bioinformatics.
The FAIR data principles, which state that data should be Findable, Accessible, Interoperable and Reusable, provide a conceptual framework for enabling easier discovery and reuse of biomedical data.
The course will cover:
1) the principles and applications of FAIR data (i.e. that data should be Findable, Accessible, Interoperable and Reusable),
2) the use of semantic web tools and technologies which facilitate making data FAIR (i.e. standards, ontologies and knowledgebases),
3) the importance of provenance in FAIR data collection, analysis and aggregation
4) computational methods to improve reuse and also reusability in science
Learning Objectives
Make use of global public bioinformatics data resources, identifying and linking data to answer biomedical research questions
Explain the FAIR data principles (i.e. that data should be Findable, Accessible, Interoperable and Reusable) and the role FAIR plays in data reuse in bioinformatics
Explain the role of ontologies and the semantic web in FAIR data integration
Explain the role of workflows in reproducible and FAIR analyses
Discriminate between different data collection and management approaches
Timetable
The most recent timetable can be found on the student website:
Mode of Instruction
Lectures
Practical classes
Presentation
Assessment Method
Two practical assignments Assignment 1: Assessing the FAIRness of published data (30%) Assignment 2: Reanalysing enrichment analysis results (40%)
Practical classe participation (10%)
Presentation (20%)
Students need to obtain a grade of 5.5 or higher on each assignment and the presentation to pass the course. During the exam resit period, there will be an opportunity to retake assignments, but the retake assignments must be completed and submitted within 1 week. The teacher will inform the students how to register for retake assignments during the lectures.
Literature
- Scientific papers from conferences, workshops and journals.
Registration
Aanmelding voor vakken verloopt via uSis. Hiervoor is de uSis-code van het vak nodig, die te vinden zijn in de Studiegids. Meer info over het inschrijven voor vakken of tentamens is hier te vinden.
MyTimetable
In MyTimetable kun je alle vak- en opleidingsroosters vinden, waarmee jij je persoonlijke rooster kunt samenstellen. Onderwijsactiviteiten waarvoor je in uSis staat ingeschreven, worden automatisch in je rooster getoond. Daarnaast kun je My Timetable gemakkelijk koppelen aan een agenda-app op je telefoon en worden roosterwijzigingen automatisch in je agenda doorgevoerd; bovendien ontvang je desgewenst per e-mail een notificatie van de wijziging.
Vragen? Bekijk de video-instructie, lees de instructie of neem contact op met de ISSC helpdesk.
Brightspace
Inschrijving voor vakken verloopt via uSis. Wanneer je je hier inschrijft voor een bepaald vak krijg je automatisch ook toegang tot de omgeving van dit vak via Brightspace.
Voor meer informatie over Brightspace kun je op deze link klikken om de handleidingen van de universiteit te bekijken. Bij overige vragen of problemen kan contact opgenomen worden met de helpdesk van de universiteit Leiden.
Contact
Onderwijscoordinator Riet Derogee