The course will be organised in 2020. The exact date will be announced soon. You can pre-register for the course via the pre-registration form.
Marco Roos (LUMC) and Katy Wolstencroft (Leiden University)
Credits and grading
The total study load of the course is 3 EC.
With endorsements for FAIR* data stewardship ranging from Nature Genetics to the G7, and increasing pressure from funders for much stricter data management, FAIR data stewardship skills will be among the most wanted for the next decade. By following this course, you add these skills to your CV and learn cutting-edge semantic techniques to search and integrate health and life science data for efficient, reproducible data science.
* FAIR: Findable, Accessible, Interoperable and Reusable for humans and computers
The amount of Life Science data available in the public domain is a vast and growing resource for bioinformatics research. There are over 20 million papers in PubMed and over 1600 biological databases. In many cases finding and applying the information from these resources is far from trivial. Following this course will show you techniques for working with these distributed resources, which includes using the web of Linked data and scientific workflows. It will also focus on methods for using or linking your own data into this large distributed Semantic Web of resources, in order to ensure that your data is FAIR (Findable, Accessible, Interoperable and Reusable).
This course is for bioinformaticians who would like to learn about leading-edge data and knowledge integration solutions. You will learn (1) powerful and flexible approaches to data and information management for your bioinformatics application (Semantic Web and Linked Data), (2) how to work with data across remote locations, for instance by applying Web Services and workflows, (3) how to publish your own data to make it available and reusable for the rest of the community. We assume a basic understanding of bioinformatics programming for the hands on sessions. It would suit previous user participants of BYOD meetings who would like more hands-on experience of data integration. It would also suit data providers who would like to explore new ways of serving their data or integrating it with other resources.
This course introduces modern techniques for the management of life science data and knowledge for bioinformatics applications. After following this course students should be able to start creating their first applications based on these technologies or make more informed design decisions for their current application.
In this course you will learn about:
- Linked Data and the Semantic Web technologies that underpin it
- How you can use Linked Data for data and knowledge integration in the Life Sciences
- Available Linked Data resources in the public domain and large-scale projects that use these resources
- How you can integrate your own data with Linked Data resources
- How you can combine data integration and analysis over distributed resources, using Web Services and workflows