Motivation

A study from EMC in 2014 predicts the doubling of the available data in the “Digital Universe” every two years between now and 2020. This rapid growth is a challenge for society – how to put the available data to use effectively? This is a challenge in many areas including Medicine and Life Sciences as well as areas in Engineering and Science, which depend on data such as Energy and Materials research. Advanced technologies and the emerging Open Data phenomenon produce an ever-increasing amount of data, which needs to be interpreted and examined. To turn data into knowledge, data scientists need to effectively process, filter, interpret cluster and learn from the available data. This process currently is largely unsupported – data scientists are spending time and money on processing data, configuring infrastructure, writing code etc., which is a large loss of productivity and unexploited opportunities, if data scientists with the necessarily skills are available at all.

To meet these challenges technologies from different areas need to be combined which help to execute computationally demanding tasks.

Linked Data and Semantic Web technologies, coming from a different direction, help to bring heterogeneous data sources together to exploit and make sense of different datasets and making it easier to process semantically heterogeneous data.

This workshop aims to accept papers that present the anatomy of large scale linked data infrastructure, which covers: the distributed infrastructure to consume, store and query large volumes of heterogeneous linked data; using indexes and graph aggregation to better understand large linked data graphs, query federation to mix internal and external data-sources, and linked data visualisation tools for health care and life sciences. It will further cover topics around data integration, data profiling, data curation, querying, knowledge discovery, ontology mapping / matching / reconciliation and data / ontology visualisation, applications / tools / technologies / techniques for life sciences and biomedical domain. Workshop aims to provide researchers in biomedical and life science, an insight and awareness about large scale data technologies for linked data, which are becoming increasingly important for knowledge discovery in the life sciences domain.

Key Aims and Learning Objectives

• Provide basic knowledge regarding the fundamentals of Large Scale Data in Life Sciences and related technologies.
• Elaborate how semantic web technologies are useful for managing Large Scale Data.
• Elaborate how to access and benefit from semantic data on the Web.
• Elaborate how to make use of Large Scale Data and introduce some of the current applications based on Semantic Web technologies