e-Science and LIS Realities and Considerations Dr Melissa Terras Lecturer in Electronic Communication School of Library, Archive and Information Studies UCL

Overview/ recap of Grid Computing Grid computing: how developed is it? Grid and the Arts and Humanities Grid and the LIS Challenges and Futures

Grid/ e-Science/ Cyberinfrastructure

Common characteristics Co-ordinated problem solving  Distributed computing Resource sharing  Computers, data, networks, processing power Virtual Organisations  Multi-institutional  Large or small, static or dynamic Transparency  User doesn’t know (or care) how their task is processed Pervasive, dependable, cost effective, efficient

Types of Grid (1) Computational Grids  CPU resources from different platforms are utilised to address a single problem parallel workloads distribution of serial workloads across a pool of systems  Two main types server grids desktop scavenging  Example: SETI Data Grids  Sharing of Data across multiple platforms Distributed filesystems Federated databases (DBMS) Data replication  Example: e-Diamond

Types of Grid (2) Connecting people “access grid” ensemble of resources including multimedia large- format displays, presentation and interactive environments, and interfaces to Grid middleware and to visualization environments. Used to support group-to- group interactions across the Grid.  large-scale distributed meetings  collaborative work sessions  seminars, lectures, tutorials, and training

Technology Hype Cycle Devised by Jackie Fenn, analyst, © Gartner Group

Grid Computing General Commercial Home use Commercial High Performance Computing University Research Source: John Easton, IBM Grid Computing, December 2005, Lecture to UCL Research Computing Group

Where are we now? Source: Mike Miniter, Training Team, National e-Science centre, “Overview of e-infrastructure”, Lecture at UCL, February 2006

What has this to do with LIS? Grid computing provides way to analyse, process, and share data LIS sector traditionally deals with information Shouldn’t we be getting involved? Maybe it will lead to knowledge… understanding… wisdom…

LIS and the Grid How will we use such technologies?  Access  Physically  Theoretically What type of data do we want analysed, processed, or delivered?  Is this a solution in search of an application? Are these technologies suited to us at all? What IT solutions are we missing at the moment, that can be addressed by e-Science technologies?  Data mining? Processing large volumes of information?  Visualisations?  Automatic generation of Ontologies? How do we join in the party at this stage? Where will the money come from? Where will staff who understand both sides come from?

Related Projects so far Use of IT and resources  (such as the eSSS…)  Entangled Data- Knowledge and Community Making in E- Social Science  University of Essex  Looking at how users use IT and may use grid systems and services to undertake research  Cyberinfrastructure for Humanities and Social Sciences American Council of Learned Societies Integration of cultural heritage through networked environment – what do people need?

Related Projects (2) Demonstrators – searching databases BIODIVERSITYWORLD: A Problem Solving Environment for Global Biodiversity  University of Reading  Using e-Science tools to search heterogeneous datasets  The user is presented with an easy to use interface which interacts with various databases seamlessly  Sorts through data to make complex visualisations

Related Projects (3) Pioneers Setting standards and experimenting with the technologies in order to build an infrastructure, and implement the type of software projects will use GROWL- VRE Programming and Toolkit GEODISE - Geodise: Grid enabled optimisation and design search system

Projects and the Arts and Humanities eSSS is stage one – identifying what can be done for the arts and humanities We need to embrace development of software and articulate our needs to the wider community to ensure that standards and protocols developed suit us too  But how to talk the same language?  How can we articulate something we don’t know about?  Small amount of projects funded by AHRC and EPSRC

Challenges to LIS What is the really innovative use of this technology?  How do we push the boundaries of what is possible? Access to technologies Funding Liaison with Computer and Engineering Science What does it mean to share IT infrastructures?  How do I get a “fair share” of the grid? procurement metrics What will be the effect of  turning around responses to users faster  sharing data seamlessly across institutions will it reveal other holes elsewhere?

Challenges and the way ahead Disavow ourselves of the notion that e-science is a “solution” to our research problems Main problem – amount and quality of data  Promoting digitization standards in order to enable processing and reuse of digital media between projects and organizations  Liaising with Computer Science in the development of protocols to search through massive datasets intuitively and efficiently Only at the start of the journey  a long term fundamental change in computing infrastructure and utilisation, efficiency and opportunity Remind ourselves that Grid computing generally involves large amounts of data  Most projects have a poor idea of how to store or manage their data effectively  LIS professionals can offer expertise to Grid computing!  Massive role in aiding in the archiving and accessing of digital information in the future

And also… Validation of digital scholarship in the humanities as proper academic research Engagement with Computing and Engineering Science  Training of interdisciplinary scholars who understand technical infrastructure and design issues Engaging in the debate on copyright and access to digital data – intellectual property and privacy rights Considering theoretical implications of the grid – engaging in what the grid means from an “information studies” standpoint. Thinking big

In Conclusion e-Science technologies are emergent  Lots of research, development and implementation required before they will become useful or usable The Arts and Humanities are relatively late to the table  e-Science is no longer flavour of the month LIS has things to benefit e-Science, and should also be part of the dialogue regarding protocols and futures There are considerable barriers to becoming part of that dialogue We have to engage with e-Science on a theoretical as well as practical level, to develop understanding of the technologies involved – and make ourselves indispensable We have to encourage a dialogue to understand what we need from future technologies We should not adopt e-Science technologies just because they are there – they should fit our goals and purpose as humanities scholars