Exploiting Diverse Sources of Scientific Data

The wealth and diversity of data collected and stored is growing rapidly as automation increases and technological costs diminish. Collecting and curating data is a crucial mechanism in collaborative scientific research. Many researchers share the effort and pool their data and knowledge in each database - where we understand the word database to denote any organised and structured collection irrespective of whether it is managed by a Database Management System. This provides a rapid mechanism for distributed communication. In many cases, the database is then published: within an organisation, within a community or publically. The Digital Curation Centre is concerned with all stages in that creation, curation and publishing process.

Today's researchers have to make best use of this wealth of data resources in combination with the data their own research provides. There is huge potential for discovery by combining information from these multiple, diverse and distributed data resources. But their sheer number, complexity and diversity makes this a daunting task. The challenge for this theme is to understand how best to enable researchers' exploitation of this potential. What strategies and methods would we advise them to use? What tools will best support their work? What cooperative plans can we make for developing the strategies and tools and for sharing the resources that they require?

There are two principal strategies supported by tools today: scientific workflows and data federation. Will these remain separate lines of development and independent tools that researchers may use? Or can we see synergies that should be supported? Within each approach, what are the methods that best work today? What are the tools currently available? How do they compare from the researcher's point of view? What are their deficiencies and how should they be addressed?

The research communities adopt different strategies for their community. For example, the BIRN, SEEK and GEON projects develop an managed integration for each of their communities. Are there fundamentally different requirements for each discipline? Is it appropriate to organise by discipline in order to reduce data exploitation costs within that discipline? Or will that generate discipline silos that inhibit interdisciplinary investigations?

The theme will lead to a series of workshops and reports addressing the kind of issues that are illustrated above. Early workshops will also help in the formulation of the theme. They may also propose future themes to address major parts of this large topic in more depth.