San Francisco, California
London, United Kingdom
SORRY, THIS EVENT HAS BEEN CANCELLED.
For further information and to find out about other training opportunities, please visit www.eudat.eu/training.
Fundamentals of Data Infrastructures
An EUDAT Training Session co-located with ISC Big Data 2014
The EUDAT vision is to support a Collaborative Data Infrastructure which will allow researchers to share data within and between communities and enable them to carry out their research effectively. EUDAT aims to provide a solution that will be affordable, trustworthy, robust, persistent and easy to use.
In this course we describe what EUDAT is working on described in the context of the three Vs of Big Data (volume, velocity and variety). You can find out what our services have to offer you and how they can help you to do research in new ways. We'll recap what we consider to be the problems and opportunities of big data, and we'll talk about some of the aspects of EUDAT's data infrastructure that can be useful in dealing with large amounts of research data including persistent identifiers, metadata, moving data, data access and integration and what you need to know both to make your data reusable and to reuse other people’s data.
We’ve also added a session which is specifically related to legal aspects of data sharing, something which becomes more and more important as we share more of our data, and make use of data that others have produced and collected. The course will be presented by four members of the EUDAT project who together have a broad knowledge about Big Data, Data Science and Research Data Infrastructures.
Training attendees need not register for ISC Big Data, but training
attendees may qualify for a reduced rate for the conference registration.
Please contact the course organiser if you are interested in this offer.
13:00 Welcome & Introduction
13:05 EUDAT and Big Data
14:00 EUDAT’s services from the point of view of Big Data
15:05 Scientific use cases for a Big Data Infrastructure
16:00 Legal aspects relevant to data sharing and big data infrastructures