Leonardo Guerreiro Azevedo

A Method for Service Identification from Business Process Models in a SOA Approach

Various approaches for services development in SOA propose business processes as a starting point. However, there is a lack of systematic methods for services identification during business analysis. We believe that there has to exist a integrated view of organizational business processes to promote an effective SOA approach, which will improve IS requirements understanding. In this context, we propose a method, and a detailed set of activities, for guiding the service designer in identifying the most appropriate set of services to support organization business activities. The method was applied in a real scenario of a Brazilian Petroleum organization.

Approximate Query Processing in Spatial Databases Using Raster Signatures

A main issue in database area is to process queries efficiently so that the user does not have to wait a long time to get an answer. However, there are many cases where it is not easy to accomplish this requirement. In addition, a fast answer could be more important for the user than receiving an accurate one. In other words, the precision of the query could be lessened, and an approximate answer could be returned, provided that it is much faster than the exact query processing and it has an acceptable accuracy.

Service identification in aspect-oriented business process models

A Service-Oriented Architecture (SOA) can be created through the use of various approaches; among them, service identification from business process models is recognized as a promising starting point. In this approach, the concept of modularization plays an important role. Modularization is also central to the aspect-oriented business process modeling (AO-BPM) approach. We understand that the combination of these two approaches can bring improvements to service identification. This paper proposes adaptations to an existing service identification method using, as input, an aspect-oriented business process modeling approach. An example is provided to demonstrate the effectiveness of our proposal.

An Experiment on Process Model Understandability Using Textual Work Instructions and BPMN Models

It is widely accepted that presenting data in the form of pictures or models can enhance comprehension, decision making and communication of the underlying information. However, there are few systematic studies that examine whether graphical models are more effective than other representation (such as textual descriptions). Process models provide an abstract graphical view of organizational procedures by reducing the complex reality of the work performed by a company to its most important activities. Such models are useful to train new employees, to document and allow improving organizational procedures and policies. This paper describes an experiment to address if there are significant differences in terms of process understand ability depending on whether textual work instructions or process models are used to represent a business process. We compared a control group of subjects that received textual work instructions to a second group, which received process models, in terms of their ability to understand the process. We found empirical support that using textual work instructions or process models do not influence process understand ability for non-expert users but do influence for experienced users.

Estimating the overlapping area of polygon join

Traditional query processing provides exact answers to queries trying to maximize throughput while minimizing response time. However, in many applications the response time of exact answers is often longer than what is acceptable. Approximate query processing has emerged as an alternative approach to give to the user an answer in a shorter time than the traditional approach. The goal is to provide an estimated result very close to the exact answer, along with a confidence interval, in a short time. There is a large set of techniques for approximate query processing available in different research areas. However most of them are only suitable for traditional data. This work is concerned with approximate query processing in spatial databases. We propose a new algorithm to estimate the overlapping area of polygon join using raster signatures. We executed experimental tests over real world data sets, and the results demonstrated our approach effectiveness.

Polyline Spatial Join Evaluation Using Raster Approximation

The main subject of spatial joins is polygons and polylines. Typical polygons and polylines can occupy several Kbytes. Since approximations use much less space, the processing of spatial joins can be greatly improved by the use of filters that reduce the need for examining the exact geometry of spatial objects in order to find the intersecting ones. Candidate pairs of approximations of spatial objects are evaluated using such filters. As a result, three possible sets of answers are identified: the positive one, composed of intersecting pairs; the negative one, composed of non-intersecting pairs; and the inconclusive one, composed of the remaining pairs of candidates. There are many approximations designed for polygons, but few are suitable for approximating polylines. This paper presents a spatial join processor based on the multi step query processor (MSQP) architecture [24]. We have developed a new polyline approximation, named five color direction raster signature (5CDRS) [18]. It is used as the filter of MSQP’s second step. The performance of the join processor and the approximation was evaluated with real world data sets. The results showed that our approach, when compared to others presented in the literature, reduced the inconclusive answers by 29% in the average. Consequently, the need for retrieving the representation of polylines and carrying out exact geometry tests is reduced by the same factor. As the exact geometry test is the most time consuming step, we have noticed that the overall time is also reduced by 38% in the average. The disk accesses are reduced by 41% in the average.

Filtering with raster signatures

Efficient evaluation of spatial queries is an important issue in spatial database. Among spatial operations, spatial join is very useful, intersection being the most common predicate. However, the exact intersection test of two spatial objects is the most time-consuming and I/O-consuming step in processing spatial joins. On the other hand, the use of approximations can reduce the need for examining the exact geometry of spatial objects in order to find the intersecting ones. This work proposes a new raster approximation (Three-Color Raster Signature - 3CRS) for representing different data types (polygons, polylines and points), and to be used as filter in the second step of the Multi-Step Query Processor. We have also executed experimental tests over real datasets, the results having demonstrated the effectiveness of our approach.

Polygon and Polyline Join Using Raster Filters

Processing spatial joins efficiently is crucial to rendering the spatial data analysis process feasible. As pointed out in many works, the exact intersection test of two spatial objects is the most time-consuming and I/O-consuming step in processing spatial joins. The use of approximations can reduce the need for examining the exact geometry of spatial objects in order to find the intersecting ones. In previous works, approximations were proposed to perform spatial joins between similar objects: polygons × polygons or polylines × polylines. This work evaluates the benefits of using approximations in spatial joins performed on polygons and polylines sets. Also, a new algorithm is proposed to compare approximations of polygons and polylines. The experiments performed with real data sets resulted in performance gains validating approach effectiveness. The number of exact intersection tests was reduced by 59%. The overall execution time and number of disk accesses were both reduced by 48%.

Automating the identification of opportunities for business process improvement patterns application

Business process management is increasingly present in organisations, and process improvement is one of its focuses. Patterns for process redesign provide solutions for recurring problems in business process improvement initiatives. However, choosing which patterns to apply in a process is not an easy task, especially in large and complex processes scenarios. This paper proposes heuristics to automate the process redesign pattern selection. The heuristics indicates specific process parts to apply improvement patterns, considering the business process model elements. A case study was performed to evaluate the proposal. The results highlight the applicability and reliability of heuristics to identify improvement opportunities in business processes models.

ENTERPRISE ONTOLOGY MANAGEMENT - An Approach based on Information Architecture

Ontologies have gained popularity, but its promises of being a key point to the solution of real-world problems and mitigating interoperability problems at a large scale have not yet been accomplished. Ontology management is at the kernel of this evolution, and there is a lack of adequate strategies and mechanisms for handling it in such a way to contribute to a better alignment between business and IT. This work proposes an approach for enterprise ontology management as part of an Information Architecture initiative. This approach provides a more complete foundation of the ontology lifecycle while guiding the enterprise in this management, by defining a set of processes, roles and competencies required for ontology management. It was applied to a big enterprise in Brazil at the Data Integration department.