The potential of collaborative work can be further harnessed if the implicit knowledge in the collaboration documents can be exploited. Together with the Experimental High-Energy Physics (EHEP) community, we are investigating the use of ontologies for scientific collaboration. The EHEP collaborative work revolves around experimental analyses. We propose an intuitive way to establish augmented collaborative experimental analysis documents. The collaboration documents are annotated with appropriate semantic descriptors, linked to ontologies published on the web. Our initiative will necessarily lead the EHEP community to produce and share information innovatively. This development is an epitome of large-scale scientific collaborations and will provide the impetus for a more rapid scientific advance.
3. EXPLICATING THE EXPERIMENTAL ANALYSES It is not difficult to see that the problem in the scenario described above could be traced to lack of structure and semantics in the published analysis description documents. Debugging an experimental analysis described by authors who profess somewhat different ontological commitment about the domain is indeed a daunting task. We believe this misinterpretation problem can be safely resolved if an analysis process is described explicitly in definite terms to peer researchers.
To begin, we propose the creation of a formal scientific document, called analyses report, which describes the completed experimental analyses according to EHEP ontologies in an orderly manner. A systematic elaboration of the analyses would allow for a clear and detailed description of the content. Publishing the analyses with annotations that further enrich its description can ensure optimal exchange of information between researchers within a collaboration.
Moreover, these machine-readable ontologies can also be utilised to describe analysis jobs. The formal specification of description can be interpreted runtime by analyser agents to perform the required data analyses.
The EHEP ontologies can also be used to mark-up the essential parts of the publications in open archives, allowing semantic searches on the collection. Alternately, a publication can now straightaway point to the relevant experimental analysis reports in the analysis archive. Accessing relevant publications or discovering similar experimental analyses will require far less time and effort.
This opportunity to embark upon an innovative way of handling
scientific information generated within an EHEP collaboration is
illustrated in Fig. 1. It affirms the belief that the next generation
web can indeed change the way scientific knowledge is produced
and shared, as envisaged by Berners-Lee and Hendler [
Next, each of these ‘hook’ concepts is expanded systematically, as sub-models of the EHEP domain. These models are in essence, taxonomies of defined concepts with their roles (properties) restricted. The knowledge models are elaborated from interviews with EHEP researchers, scientific documents, such as pre-prints and journal articles, and existing standard HEP terminology, such as the terms maintained by the Particle Data Group.
We are developing these models using a Frame-based tool, called
Protégé-2000 [
A parallel activity undertaken during this time is the formulation of a set of competency questions that outline the competence of the EHEP ontologies. The regularly updated competency questions effectually guide the acquisition of the correct domain knowledge for the models.
In short, the development of the knowledge models follows an evolutionary development cycle, which also encompasses the model validation, verification and refinement. This is part of our ongoing work.
Finally, the completed models will be formalised as EHEP
ontologies. We intend to implement the ontologies in
DAML+OIL [
Analyser
Analysis Job semantic links
EHEP Ontologies completed analyses review existing analysis
Analysis Report
Publication produces hyperlinks Analysis Archive
Publication Archive Fig. 1. Handling EHEP collaboration documents. Researchers prepare and deliver the semantically marked up analysis reports and publications, which can be archived and referred during subsequent experimental analysis. The content of the archives can also be searched more productively using precisely defined queries. Jobs described using the ontological terms can be processed directly by the agent analyser