Tore Risch

EDUTELLA: a P2P networking infrastructure based on RDF

Metadata for the World Wide Web is important, but metadata for Peer-to-Peer (P2P) networks is absolutely crucial. In this paper we discuss the open source project Edutella which builds upon metadata standards defined for the WWW and aims to provide an RDF-based metadata infrastructure for P2P applications, building on the recently announced JXTA Framework. We describe the goals and main services this infrastructure will provide and the architecture to connect Edutella Peers based on exchange of RDF metadata. As the query service is one of the core services of Edutella, upon which other services are built, we specify in detail the Edutella Common Data Model (ECDM) as basis for the Edutella query exchange language (RDF-QEL-i) and format implementing distributed queries over the Edutella network. Finally, we shortly discuss registration and mediation services, and introduce the prototype and application scenario for our current Edutella aware peers.

Main memory orientated optimization of OO queries using typed Datalog with foreign predicates

Object-oriented database systems (OODBs) have created a demand for relationally complete, extensible, and declarative object-oriented query languages. Until now, the runtime performance of such languages was far behind that of procedural OO interfaces. One reason is the internal use of a relational engine with magnetic disk resident databases. The authors address the processing of the declarative OO language WS-OSQL, provided by the fully operational prototype OODB called WS-IRIS. A WS-IRIS database is main memory (MM) resident. The system architecture, data structures, and optimization techniques are designed accordingly. WS-OSQL queries are compiled into an OO extension of Datalog called ObjectLog, providing for objects, typing, overloading, and foreign predicates for extensibility. Cost-based optimizations in WS-IRIS using ObjectLog are presented. Performance tests show that WS-IRIS is about as fast as current OODBs with procedural interfaces only and is much faster than known relationally complete systems. These results would not be possible for a traditional disk-based implementation. However, MM residency of a database appears to be only a necessary condition for better performance. An efficient optimization is of crucial importance as well. >

Query processing over object views of relational data

Abstract. This paper presents an approach to object view management for relational databases. Such a view mechanism makes it possible for users to transparently work with data in a relational database as if it was stored in an object-oriented (OO) database. A query against the object view is translated to one or several queries against the relational database. The results of these queries are then processed to form an answer to the initial query. The approach is not restricted to a ‘pure’ object view mechanism for the relational data, since the object view can also store its own data and methods. Therefore it must be possible to process queries that combine local data residing in the object view with data retrieved from the relational database. We discuss the key issues when object views of relational databases are developed, namely: how to map relational structures to sub-type/supertype hierarchies in the view, how to represent relational database access in OO query plans, how to provide the concept of object identity in the view, how to handle the fact that the extension of types in the view depends on the state of the relational database, and how to process and optimize queries against the object view. The results are based on experiences from a running prototype implementation.

Functional Data Integration in a Distributed Mediator System

Amos II (Active Mediator Object System) is a distributed mediator system that uses a functional data model and has a relationally complete functional query language, AmosQL. Through its distributed multi-database facilities many autonomous and distributed Amos II peers can intemperate. Functional multi-database queries and views can be defined where external data sources of different kinds are translated through Amos II and reconciled through its functional mediation primitives. Each mediator peer provides a number of transparent functional views of data reconciled from other mediator peers, wrapped data sources, and data stored in Amos II itself. The composition of mediator peers in terms of other peers provides a way to scale the data integration process by composing mediation modules. The Amos II data manager and query processor are extensible so that new application oriented data types and operators can be added to AmosQL, implemented in some external programming language (Java, C, or Lisp). The extensibility allows wrapping data representations specialized for different application areas in mediator peers. The functional data model provides very powerful query and data integration primitives which require advanced query optimization.

Distributed Data Integration by Object-Oriented Mediator Servers

Integration of data from autonomous, distributed and heterogeneous data sources poses several technical challenges. This paper overviews the data integration system AMOS II based on the wrapper‐mediator approach. AMOS II consists of: (i) a mediator database engine that can process and execute queries over data stored locally and in several external data sources, and (ii) object‐oriented (OO) multi‐database views for reconciliation of data and schema heterogeneities among sources with various capabilities. The data stored in different types of data sources is translated and integrated using OO mediation primitives, providing the user with a consistent view of the data in all the sources. Through its multi‐database facilities many distributed AMOS II systems can interoperate in a federation. Since most data reside in the data sources, and to achieve high performance, the core of the system is a main‐memory DBMS having a storage manager, query optimizer, transactions, client–server interface, disk backup, etc. The AMOS II data manager is optimized for main‐memory access and is extensible so that new data types and query operators can be added or implemented in some external programming language. The extensibility is essential for providing seamlessaccess to a variety of data sources. Copyright

A database generator for human brain imaging

Sharing scientific data containing complex information requires new concepts and new technology. NEUROGENERATOR is a database generator for the neuroimaging community. A database generator is a database that generates new databases. The scientists submit raw PET and fMRI data to NEUROGENERATOR, which then processes the data in a uniform way to create databases of homogeneous data suitable for data sharing, met-analysis and modelling the human brain at the systems level. These databases are then distributed to the scientists.

A functional approach to integrating database and expert systems

A new system architecture shares certain characteristics with database systems, expert systems, functional programming languages, and spreadsheet systems, but is very different from any of these.

Query Decomposition for a Distributed Object-Oriented Mediator System

The mediator-wrapper approach to integrate data from heterogeneous data sources has usually been centralized in the sense that a single mediator system is placed between a number of data sources and applications. As the number of data sources increases, the centralized mediator architecture becomes an administrative and performance bottleneck. This paper presents a query decomposition algorithm for a distributed mediation architecture where the communication among the mediators is on a higher level than the communication between a mediator and a data source. Some of the salient features of the proposed approach are: (i) exploring query execution schedules that contain data flow to the sources, necessary when integrating object-oriented sources that provide services (programs) and not only data; (ii) handling of functions with multiple implementations at more than one mediator or source; (iii) multi-phase query decomposition using a combination of heuristics and cost-based strategies; (iv) query plan tree rebalancing by distributed query recompilation.

Using partial differencing for efficient monitoring of deferred complex rule conditions

Presents a difference calculus for determining changes to rule conditions in an active DBMS. The calculus has been used for implementing an algorithm to efficiently monitor rules with complex conditions. The calculus is based on partial differencing of queries derived from rule conditions. For each rule condition, several partially differentiated queries are generated that each considers changes to a single base relation or view that the condition depends on. The calculus considers both insertions and deletions. The algorithm is optimized for deferred rule condition monitoring in transactions with few updates. The calculus allows us to optimize both space and time. Space optimization is achieved since the calculus and the algorithm does not presuppose materialization of monitored conditions to find its previous state. This is achieved by using a breadth-first, bottom-up propagation algorithm and by calculating previous states by doing a logical rollback. Time optimization is achieved through incremental evaluation techniques. The algorithm has been implemented and a performance study is presented at the end of the paper.

Syntel Using a Functional Language for Financial Risk Assessment

This article describes Syntel, a knowledge representation language used in building large-scale expert systems for financial risk assessment. Syntel is an outgrowth of rule-based systems such as MYCIN and network-based systems such as Prospector. Unlike typical rule- or frame-based expert system shells, however, Syntel is a data-driven, purely functional language providing probabilistic inference plus many kinds of functionality associated with spreadsheets and database systems.