In 2001, David De Roure, Nick Jennings and Nigel Shadbolt introduced the notion of the Semantic Grid, which advocated “the application of Semantic Web technologies both on and in the Grid.” From the requirements derived from the diverse set of U.K. e-Science applications, De Roure, Jennings and Shadbolt identified a need for maximum reuse of software, services, information and knowledge. Although the basic Grid middleware originally was conceived for hiding the heterogeneity of distributed computing, the authors contended that users now required “interoperability across time as well as space” to cope with both anticipated and unanticipated reuse of services, information and knowledge.
In a new paper, the same authors have revisited the projects of the U.K. e-Science program three years out from their original analysis to examine if their expectations have been realized. They now see the e-Science requirements as a spectrum, with one end characterized by automation, virtual organizations of services and the digital world, and the other end characterized by interaction, virtual organizations of people and the physical world.
From experience with projects such as myGrid and CombeChem, they have abstracted 12 key requirements for the Semantic Grid:
- Resource description, discovery and use.
- Process description and enactment.
- Autonomic behavior.
- Security and trust.
- Information integration.
- Synchronous information streams and fusion.
- Context-aware decision support.
- Support for communities.
- Smart environments.
- Ease of configuration and deployment.
- Integration with legacy IT systems.
They also identify five key technologies that are being used to address these requirements in some of the U.K. e-Science projects:
- Web services.
- Software agents.
- Ontologies and reasoning.
- Semantic Web services.
Let us look at what have these two projects achieved so far.
The myGrid e-Science project (www.mygrid.org.uk) is researching high-level middleware to support personalized in silico experiments in biology. These in silico experiments use databases and computational analysis rather than laboratory investigations to test hypotheses. In myGrid, the emphasis is on data intensive experiments that combine the use of applications and database queries. The biologist user is helped to create complex workflows with which they can interact and that can also interact with workflows of other researchers. Intermediate workflows and data are kept, notes and thoughts recorded, and different experiments linked together to form a network of evidence as is currently done in bench laboratory notebooks.
The computer scientists and biologists in the project have together developed a detailed set of scenarios for investigation of the genetics of Graves' disease, an immune disorder causing hyperthyroidism, and of Williams-Beuren syndrome, a gene deletion disorder that affects multiple human systems and also causes mental retardation. To implement its ideas, the project has built a prototype electronic workbench based on Web Services. They have identified four categories of service:
- External third party services such as databases, computational analyses and simulations, wrapped as Web services.
- Services for forming and executing experiments such as workflows, information management and distributed database query processing.
- Services for supporting the e-Science methodology such as provenance and notification.
- Semantic services, such as service registries, ontologies and ontology management, that enable the user to discover services and workflows and to manage several different types of metadata.
Some, or all, of these services are then used to support applications and build application services.
The project has developed a suite of ontologies (roughly speaking, agreed vocabularies of terms or concepts) to represent metadata associated with the different middleware services. Semantic Web technologies such as DAML+OIL and standards body W3C's Web ontology language, OWL, then allow the prototype myGrid workbench to operate, interoperate and reason over these services intelligently. The project has demonstrated the potential of such an approach to in silico bioinformatics experiments and is now attempting to produce more robust semantic components that will allow users to personalize their own research environment.
The CombeChem project (www.CombeChem.org) has the ambitious goal of creating a “Smart Laboratory” for Chemistry using technologies for automation, semantics and Grid computing. A key driver for the project is the fact that large volumes of new chemical data are being created by new high throughput technologies such as combinatorial chemistry, in which large numbers of new chemical compounds are synthesized simultaneously. The need for assistance in organizing, annotating and searching this data is becoming acute. The multidisciplinary CombeChem team has, therefore, developed a prototype Smart Laboratory test-bed that integrates chemical structure-property data resources with a Grid-based computing environment.
The project has explored automated procedures for finding similarities in solid-state crystal structures across families of compounds and evaluated new statistical design concepts to improve the efficiency of combinatorial experiments in the search for new enzymes and pharmaceutical salts for improved drug delivery. One of the key concepts of the CombeChem project is “[email protected]” by which there is a complete end-to-end connection between the results obtained at the laboratory bench and the final published analyses. In a sister project called eBank, raw crystallographic data is annotated with metadata and “published” by archiving in the U.K. National Data Store as a “Crystallographic e-Print.” Publications can then be linked back to the raw data for other researchers to access.
In another strand, computer scientists in the SmartTea project have worked with the Combechem team to develop an innovative human-centered system that captures the process of a chemistry experiment from plan to execution. They have used an analysis of the process of making tea in a laboratory to develop an electronic lab book replacement.
Using tablet PCs, the system has been successfully tested in a synthetic organic chemistry laboratory and linked to a flexible back-end storage system. A key finding was that users needed to feel in control, and this necessitated a high degree of flexibility in the lab book user interface. The computer scientists on the team investigated the representation and storage of human-scale experiment metadata and introduced an ontology to describe the record of an experiment and a novel storage system for the data from the electronic lab book.
In the same way that the interfaces needed to be flexible to cope with whatever chemists wished to record, the back end solutions also needed to be similarly flexible to store any metadata that might be created. Their storage system was based on Semantic Web technologies such as RDF (Resource Description Framework) and Web services. This system was found to give a much higher degree of flexibility to the type of metadata that can be stored compared to traditional relational databases.
Although much of the focus of the Grid community is currently on low level middleware, it is important not to lose sight of the significant research challenges for computer scientists to develop high level, intelligent middleware services. These services must genuinely support the needs of scientists and allow them to routinely construct secure Virtual Organizations and to automate the management of the many Petabytes of scientific data that will be generated in the next few years in many areas of science. The Semantic Grid is not yet a reality, but the U.K. e-Science projects are providing a valuable test-bed for Semantic Web technologies.
© Tony Hey 2005