Guillermo Nudelman Hess

Inventing Less, Reusing More, and Adding Intelligence to Business Process Modeling

Recently, a variety of workflow patterns has been proposed focusing on specific aspects like control flow, data flow, and resource assignments. Though these patterns are relevant for implementing Business Process Modeling (BPM) tools and for evaluating the expressiveness of BPM languages, they do not contribute to reduce redundant specifications of recurrent business functions when modeling business processes. Furthermore, contemporary BPM tools do not support process designers in defining, querying, and reusing activity patterns as building blocks for process modeling. Related to these problems this paper proposes a set of activity patterns, evidences their practical relevance, and introduces a BPM tool for the modeling of business processes based on the reuse of these activity patterns. Altogether our approach fosters reuse of business function specifications and helps to improve the quality and comparability of business process models.

Towards effective geographic ontology matching

The integration and matching of geographic ontologies is a field in which many efforts are being employed. There are many proposals, addressing a diversity of features, both at the concept as at the instance-level. In order to make clear the issues that are involved in the matching process, in this paper we present the formal definition of the heterogeneities that may occur when comparing two geographic ontologies. Some of the heterogeneities are common to the ones found in conventional ontologies integration, and some others are specific for the geographic field. Furthermore, we discuss some still open issues, neglected up to now, but very important to achieve good results in a real scenario.

Geographic ontology matching with iG-match

To achieve accurate results when matching geographic ontologies, it is important to have clear what has to be compared, and just then start comparing them. In this paper we define a geographic ontology reference model and, from it, the set of heterogeneities that may occur when comparing two geographic ontologies is elaborated, at both the concept and instance-level. Based on the heterogeneities set we then present the iG-Match, which consists in a software architecture that implements a methodology to perform geographic ontology matching, using some metrics specially developed for the geographic domain.

Analysis Patterns for the Geographic Database Conceptual Schema: An Ontology Aided Approach

Conceptual modeling of Geographic Databases (GDB) has become a very important task due to both the increasing exchange and reuse of geographic information. Most of the GDB support a proprietary data model, specific for a particular system architecture. This design scenario leads to a non-reusable as well as implementation-dependent geographic database project. The reuse is especially interesting in GDB, since the precise modeling process can be of significant complexity. Furthermore, a wide set of real world entities must be represented in the database of most geographic applications. To support this kind of reuse, the analysis patterns methodology [2] is a very useful technique. Analysis patterns are the core of the conceptual modeling for the solution of a recurrent problem in a specific context. Having the patterns stored in a knowledge base that can be easily searched and updated, a designer is able to search, retrieve and reuse the most adequate concept representation that applies to a specific modeling process. To support this approach, a ontology can be used to play the role of the knowledge base mentioned above.