Empowering e-Science, eMpowering libraries – Xiaolin Zhang – VALA 2012

Xiaolin Zhan is the head of the National Science Library of Chinese Academy of Sciences

Lots of information challenges to e-science:

  1. eScience is built on a lot of data – it is smart data, not just because you can play with it using computers, but because of forthcoming technologies like semantic publishing, and computable. It not only comes as numbers, but intelligent, computable, with metadata.

  2. eScience is more than a lot of data – it covers the entire research and development chain, enables integrated resource development and analysis and envisions an integrative infrastructure. Its computable knowledge – can have visualised searches, intelligent tracking, tech trends analysis. Its knowledge driven scientific discovery, workflow and problem solving. The whole discovery process then becomes knowledge driven.

  3. eScience is a different information world? Its strategic innovation, interdisciplinary and translational research, its cooperative research, its data intensive knowledge discovery. Now serving R & I decision-makers, lab & project leaders, front-line researchers and engineers. Now scientists go from data to information to intelligence to a solution is happening on the go. They need scholarly publications, research data, applied and market data, applied market and social information and more.

  4. A new approach is required. Library solution is no longer the user solution. Library can only build its contribution on users solutions. Users solutions are not data or collections, but R& problem solving solutions. Library should aim for high impact services.

Libraries as smart power for e-Science:

  1. Re-purpose the research library: trends tracking, potential testing and priority selection. Not just data, but visualisation and presentation. If we miss these opportunities, we miss this trust and miss the future. Focus on R&D’s new and hurting knowledge bottlenecks – help them to do research better, but with added value. Knowledge as a service – science as service, take steps to make the knowledge into a live tool – smart data.

  2. Smart reading for R&D. First look at how people consumer information. No longer linear, static and lonely or reactive. Now weak vs strong information – weak is information you don’t know and don’t know its relevance. Power browsing – key messages rather than linear reading. Strategic reading – fast scanning to extract and accumulate for building context, frameworks and direction. Looked at who is reading what – the higher the position, the more strategic, innovation, interdisciplinary and translational research. Need to provide a lot of information analysis and tools to do this.

  3. Integrative knowledge support for R&D> need discovery, customised, embedded, analysis and preservation provenance. Which matches the R&D workflow.

  4. Knowledge based collaborative R&D; networked-based knowledge experiments,not just resources, but tools, experts and specialists. Need the facilities, the rights, ability to experiment.

  5. Capitalising on complexity of meta-knowledge – we help by building knowledge as a service. Provide knowledge on knowledge, on collaborating, on processes, structures and interactions. Its now a verb as well as a noun. It is live. To do so, need to be strong, have special expertise and organisation. Libraries can do this, but are not ready to do so quite yet. Vendors are already offering this type of service.

Because most researchers and students live over 1000kms away from the National Science Library, they have built a system where the information is pushed out to the users (who are all connected online). They are shifting to a R&D support service, which incorporates an integrated discovery service. They are experimenting with clustering,GIS and visualisation technologies to gather and explore diverse data resources from many institutions and websites. Put much more emphasis on building user environments.RH

Planning a China IR alliance, with other research institutions and also with European partners. They are supporting OA publishing and are a member of arXiv.org. They plan to be a central force in OA resources and policies.

Have fourteen teams working on Research Intelligence Services. Do regular R&D tracking, R &D structure and evolution analysis – using purchased tools and others they have developed themselves, Mapping of sciences and R&D roadmapping, Tech trends analysis – now a big part of what they do. They are developing computer-assisted integrated analysis generation, including automatic profiles, customised analysis, etc.

Also have embedded research support – they liase with their institutes, but not library or documente based. They are user centred. They are doing integrated resource development, helping their institutes to determine what information they need and how it should be organised.

Developing Knowledge platforms as an Academy wide initiative. By end of 2012, it will be live in 15 institutes, by 2012 in all 100 CASS institutes. This will include improved knowledge literacy, so that they not only know how to find the data.

Library will become an open innovation centre. From a library, to a knowledge co-laboratory? They are using the under-utilised library space for consultation, video conferencing, lectures, exhibitions, experiments, seminars and classes.

Challenges:

  • technologies – types and integration

  • staff – need a knowledge of R&D and tech, not just subject areas

  • organisation – reversing pyramid structure – embedded knowledge specialists first