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 new techniques for working with these distributed resources, including using the Semantic Web, Linked data and scientific workflows. It will also focus on methods for using or linking your own data into this large distributed web of resources.
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 get the most credit and make it available and reusable for the rest of the community.
Date: 30 November – 4 December 2015
Target audience: This course is for bioinformaticians who would like to learn about leading-edge data and knowledge integration solutions.
Program: 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:
- how the ‘Linked Data’ principle works and how it can be applied for ‘meaningful’ data integration.
- how to expose your local data with rich metadata for use in other systems.
- how Web Services and workflows can be used to analyse distributed data.
- how to make publishable artefacts from your data for which you can get scientific credit.
Keywords: Knowledge-based information management, Database workhorses, Web services for collaboration and data integration, Semantic data integration