Querying business processes with BP-QL

We present in this paper BP-QL, a novel query language for querying business processes. The BP-QL language is based on an intuitive model of business processes, an abstraction of the emerging BPEL (business process execution language) standard. It allows users to query business processes visually, in a manner very analogous to how such processes are typically specified, and can be employed in a distributed setting, where process components may be provided by distinct providers.     

The Active XML project: an overview

This paper provides an overview of the Active XML project developed at INRIA over the past five years. Active XML (AXML, for short), is a declarative framework that harnesses Web services for distributed data management, and is put to work in a peer-to-peer architecture. The model is based on AXML documents, which are XML documents that may contain embedded calls to Web services, and on AXML services, which are Web services capable of exchanging AXML documents. An AXML peer is a repository of AXML documents that acts both as a client by invoking the embedded service calls, and as a server by providing AXML services, which are generally defined as queries or updates over the persistent AXML documents. The approach gracefully combines stored information with data defined in an intensional manner as well as dynamic information. This simple, rather classical idea leads to a number of technically challenging problems, both theoretical and practical. In this paper, we describe and motivate the AXML model and language, overview the research results obtained in the course of the project, and show how all the pieces come together in our implementation. The first and third authors were partially funded by the European Project Edos. Work done when the second and third authors were at INRIA. Work done when the second and third authors were at INRIA.     

R1-soar: an experiment in knowledge-intensive programming in a problem-solving architecture

This paper presents an experiment in knowledge-intensive programming within a general problem-solving production-system architecture called Soar. In Soar, knowledge is encoded within a set of problem spaces, which yields a system capable of reasoning from first principles. Expertise consists of additional rules that guide complex problem-space searches and substitute for expensive problem-space operators. The resulting system uses both knowledge and search when relevant. Expertise knowledge is acquired either by having it programmed, or by a chunking mechanism that automatically learns new rules reflecting the results implicit in the knowledge of the problem spaces. The approach is demonstrated on the computer-system configuration task, the task performed by the expert system R1.     

Investigating preservice teachers' professional growth in self-regulated learning environments.

Educational reforms have suggested that the ability to self-regulate learning is essential for teachers' professional growth during their entire career as well as for their ability to promote these processes among students. This study observed teachers' professional growth along 3 dimensions: self-regulated learning (SRL) in pedagogical context, pedagogical knowledge, and perceptions of teaching and learning. The authors examined 194 preservice teachers' professional growth in 4 learning environments: e-learning (EL) and face-to-face (F2F) learning, either supported by SRL (EL + SRL; F2F + SRL) or unsupported by SRL (EL; F2F). SRL support was based on the IMPROVE metacognitive self-questioning method (B. Kramarski & Z. R. Mevarech, 2003). Mixed quantitative and qualitative analyses showed that preservice teachers in both supported SRL conditions outperformed their unsupported peers on all professional growth measures. Moreover, EL + SRL teachers exhibited the highest SRL ability (cognition, metacognition, motivation), pedagogical knowledge (designing a learning unit), and student-centered learning perceptions (self-construction of knowledge). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An Algebra for Pomsets

We study languages for manipulatingpartially orderedstructures withduplicates(e.g., trees, lists). As a general framework, we consider thepomset(partially ordered multiset) data type. We introduce an algebra forpomsets, which generalizes traditional algebras for (nested) sets, bags, and lists. This paper is motivated by the study of the impact of different language primitives on the expressive power. We show that the use of partially ordered types increases the expressive power significantly. Surprisingly, it turns out that the algebra when restricted to both unordered (bags) and totally ordered (lists) intermediate types, yields the same expressive power as fixpoint logic with counting on relational databases. It therefore constitutes a rather robust class of relational queries. On the other hand, we obtain a characterization of PTIME queries on lists by considering only totally ordered types.