The role of Information Technology (IT) is critical in supporting business processes. This role is even more critical when organizations operate in a dynamic, uncertain and extremely competitive environment. The growing role of IT in organizations imposes the alignment of their use with business processes requirements and company strategy. The necessity of Business/IT alignment is a key to improve business performance. This paper proposes a methodology for analyzing and evaluating the quality of business process execution. The aim of this methodology is to assess the business process during its lifecycle and to propose some solutions to restore the alignment between IT infrastructure and Business Process in a collaborative context. Our approach is composed of 5 models, (1) analysis reference model (risk, maturity...) for analyzing the component execution traces in business processes, (2) ontological model to ensure the description of processes between the applicative level (execution), functional level and business level, (3) interpretation model (butom-up) for aggregating the performance of processes at business level, (4) assessment business process model based on Key Indicators Performance and (5) aggregation model to validate the final performance for collaborative business process.

With XML becoming a ubiquitous language for data interoperability purposes in various domains, efficiently querying XML data is a critical issue. This has lead to the design of algebraic frameworks based on tree-shaped patterns akin to the tree-structured data model of XML. Tree patterns are graphic representations of queries over data trees. They are actually matched against an input data tree to answer a query. Since the turn of the 21st century, an astounding research effort has been focusing on tree pattern models and matching optimization (a primordial issue). This paper is a comprehensive survey of these topics, in which we outline and compare the various features of tree patterns. We also review and discuss the two main families of approaches for optimizing tree pattern matching, namely pattern tree minimization and holistic matching. We finally present actual tree pattern-based developments, to provide a global overview of this significant research topic.

Business Intelligence plays an important role in decision making. Based on data warehouses and Online Analytical Processing, a business intelligence tool can be used to analyze complex data. Still, summarizability issues in data warehouses cause ineffective analyses that may become critical problems to businesses. To settle this issue, many researchers have studied and proposed various solutions, both in relational and XML data warehouses. However, they find difficulty in evaluating the performance of their proposals since the available benchmarks lack complex hierarchies. In order to contribute to summarizability analysis, this paper proposes an extension to the XML warehouse benchmark (XWeB) with complex hierarchies. The benchmark enables us to generate XML data warehouses with scalable complex hierarchies as well as summarizability processing. We experimentally demonstrated that complex hierarchies can definitely be included into a benchmark dataset, and that our benchmark is able to compare two alternative approaches dealing with summarizability issues.