My work spans fundamental, applied and, increasingly, interdisciplinary research. I think that's typical at the LKL because many of us have come with expertise in specific disciplines, and what LKL aims to do is to foster research into problems which simply can't be solved with the perspective and expertise of just one discipline.

Personally, what drew me to computing was the creative aspect of software analysis, design and development, and the interaction with its prospective users during this process. These are interests that remain true today, and resonate I think with the multi- and inter-disciplinary research aims of the LKL.

My long-running fundamental research is in data manipulation and data integration.

Data manipulation involves the design, implementation and evaluation of languages for querying and updating data. Data manipulation languages may be targeted towards end-users or towards application developers.

Traditionally what has happened is that the data manipulation part of an application is embedded within the programming language, e.g. SQL in C. In the 1980s and 90s a particular area of research was database programming languages. Some of my early work was in that area, where we tried to design languages that seamlessly handle data and computation within one language.

Currently, our work with Peter Wood, George Papamarkos, Sandeep Mittal and Carlos Hurtado, is focussing on languages for manipulating RDF data, and this has application in areas such as e-science and e-learning.

My other strand of fundamental research is in data integration. There are applications that need to integrate data from a variety of different sources. We want to make the task of the end-user of such an application, or the developer, easier by providing mechanisms to carry out that integration and to allow access the new integrated resources. Ideally the aim is to be able to access an integrated resource as if it had been created like that in the first place. The integrated resource may be a stored resource, or it may be a "virtual" and we provide middleware that sits over actual data sources to give that illusion to the end-user.

Our major project in this area is the AutoMed project, which is a long-running collaboration with Imperial College. Currently Lucas Zamboulis, Sandeep Mittal and Dean Williams here are doing their PhDs in the context of that project. The tools we are developing are being used for integrating different biological databases in the ongoing ISPDER project. AutoMed is also being used in another project at Imperial, called RoDex, which is developing protocols for the exchange of data between autonomous vehicles.

Data integration techniques are also useful in a learning context. Some of the other projects here at the LKL - for example, the MyPlan project - in the longer term may need to integrate information from a variety of repositories relating to learning objects, learners and other learning-related material.

Another side to AutoMed is that we teach it as part of the course on Advances in Data Management on the MSc in Advanced Information Systems at Birkbeck. It's a toolkit that students can use - we have designed coursework based on it. Students can also do their projects with us, and extend its code base and functionality. This has worked well as part of Birkbeck's mission of research-led teaching.

Moving to applied research, I've mentioned already two applied projects I'm involved in, ISPIDER and MyPlan.

ISPIDER supports biological data integration within a Grid environment. The aim of Grid technologies is to be able to share data and computing resources which may be geographically quite disparate and autonomous. In the ISPIDER project, we are focussing on a variety of proteomics data resources working with Manchester, EBI (European Bioinformatics Institute) and UCL. Nigel Martin is the PI of the project and Lucas Zamboulis is working on combining AutoMed with Grid services for data access and distributed querying. Performance is an issue in such environments and some of our work is focussing on that.

Also in Grids, we're part of the Learning Grid Special Interest Group of the Kaleidoscope network, with other groups from Italy and Spain. This SIG aims to explore the relationships between Grid technologies and the needs of applications in the learning area.

The aim of the MyPlan project (which George Magoulas and I lead) is to use techniques from semantic web, personalisation and adaptation to support life-long learners in identifying appropriate educational opportunities. Currently, this is focused in the London region and the Linking London Lifelong Learning network; in principle it could scale up beyond that. Nicolas van Labeke and Hassan Baajour are working on this project. Also part of the MyPlan team are Diana Laurillard, Martin Oliver, Sara de Freitas and Ian Harrison.

My main interdisciplinary work is in the new TEL project we've recently had funded from the ESRC/EPSRC, MiGen - intelligent support for mathematics generalisation. I think this project will truly allow us at LKL to cross barriers and work together across disciplines. The idea is to use computational intelligence and information management techniques, and develop them collaboratively with education experts to provide more effective learning experiences.

An ideal learning environment I could envision would be one in which the users are in control of the way the environment presents itself to them, and adapts to them. It's empowering the user, facilitating functionality for them, and trying to make the system the servant of the teacher and the learner, rather than the other way round. That's one dimension; the other is facilitating collaboration between learners - technology as an active medium that fosters collaboration.

More broadly, I see my role as helping to shape the research strategy of the LKL and to facilitate the emergence and development of multi- and interdisciplinary research collaborations at the lab. Birkbeck's School of Computer Science and Information Systems has a long tradition of applied research and collaboration with the users of computing research, so the LKL is a natural next step for us.