The ESP2Net project is developing technologies that enable effective collaborative scientific data sharing to support collaboration among scientists, accelerate production of scientific data products, and improve understanding of the science. We have defined a Scientific Experiment Markup Language (SEML) to capture scientific experiments in hypermedia documents as a basic unit of information sharing. A collection of SEML documents can be viewed as an online electronic experiment logbook that captures the entire experiment experience by including the process and interrelationships between experiments to allow an experiment to be re-created. Complementary means of sharing the experiences from scientific experiments (browsing, searching, dissemination, and mining) are provided by integrating OASIS transparent distributed scientific object access, Conquest dynamic distributed query processing services, and active information dissemination services introduced in semantic multicast.

The main concept behind our approach to scientific information sharing is to capture scientific experiments in hypermedia documents as the basic unit of information exchange. We defined SEML (Scientific Experiment Markup Language), based on the XML standard that introduces definitions of tags and links for specific and common information describing scientific experiments. A collection of SEML documents can be viewed as an online electronic experiment logbook that captures the entire experiment. The process and inter-relationships between experiments are modeled to allow an experiment to be re-created, perhaps when input data sets change. We have prototyped ASSISS (Active Semi-Structured Information Sharing System), supporting the browsing, searching and dissemination of XML documents. ASSISS extends scalable active data dissemination technologies developed in the Semantic Multicast Project to provide support for collaborative scientific information dissemination. Within the framework, users' information requests are adaptively clustered. The aggregated information processing and dissemination needs of user groups are then satisfied by a network of dynamic content agents that filters and transforms information in the appropriate manner. SEML is used as the vocabulary against which user profiles are specified, and SEML documents capturing an experiment can be proactively multicasted to groups of users who are interested in some aspect of the activity as the experiments are being conducted.

Consider a database that represents the location of moving objects, such as taxi-cabs (typical query: "retrieve the cabs that are currently within 1 mile of 33 Michigan Ave., Chicago"), or objects in a battle-field. Existing database management systems (DBMSs) are not well equipped to handle continuously changing data, such as the position of moving objects, since data is assumed to be constant unless it is explicitly modified. In this paper, we address position-update policies and imprecision. Assuming that the actual position of a moving object m deviates from the position computed by the DBMS, when should m update its position in the database in order to eliminate the deviation? Furthermore, how can the DBMS provide a bound on the error (i.e. the deviation) when it replies to a query, such as: "what is the current position of m?" We propose a cost-based approach to update policies that answers both questions. We develop several update policies and analyze them theoretically and experimentally.

We propose a data model for representing moving objects in database systems. It is called the Moving Objects Spatio-Temporal (MOST) data model. We also propose Future Temporal Logic (FTL) as the query language for the MOST model, and devise an algorithm for processing FTL queries in MOST.

Future large and complex information systems create new challenges and opportunities for research and advanced development in data management. A brief description of Hughes research and prototype efforts to meet these challenges is summarized.>

Fuzzy databases have been introduced to deal with uncertain or incomplete information in many applications. The efficiency of processing fuzzy queries in fuzzy databases is a major concern. We provide techniques to unnest nested fuzzy queries of two blocks in fuzzy databases. We show both theoretically and experimentally that unnesting improves the performance of nested queries significantly. The results obtained in the paper form the basis for unnesting fuzzy queries of arbitrary blocks in fuzzy databases.>

Proposes a formal approach for translating OODB queries to equivalent relational queries. The translation is accomplished through the use of relational predicate graphs and OODB predicate graphs. One advantage of using such a graph-based approach is that we can achieve bidirectional translation between relational queries and OODB queries.>

A new hybrid algorithm is proposed for well-formed path problems including the transitive closure problem. The CPU time for computation is O(ne), and blocking technique is incorporated to reduce the disk I/O cost in disk-resident environment. The new features of the new algorithm are that only parents sets instead of descendant sets are loaded in from disk, and the computation can be parallelized efficiently. Simulation results show that our algorithm is superior to other existing algorithms in sequential computation, and that linear speedup is achieved in parallel computation.>

Proposes a solution for the construction of a relational front-end for object-oriented database systems (OODBs). Rules are provided to transform the structural part of an OODB scheme to an equivalent relational scheme to provide relational users with a relational view of the OODB scheme. A mechanism based on a relational predicate graph and an OODB predicate graph is provided to translate relational queries to OODB queries to allow relational users access to data stored in an OODB database system.>