Lucinéia Heloisa Thom

Activity patterns in process-aware information systems: basic concepts and empirical evidence

Recently, a variety of workflow patterns have been suggested for capturing different aspects in process-aware information systems (PAISs), including control and data flow, resources, process change and exception handling. All these patterns are highly relevant for implementing PAISs and for designing process modelling languages. However, current patterns provide only a partial answer to the question of which business functions a designer might want to reuse when modelling processes. This paper presents a revised version of a collection of activity patterns to deal with this challenge. Each of them is related to a recurrent business function as it can be frequently found in process models (e.g., task execution request, notification, approval). We describe the identified activity patterns and their variants in detail. The main purpose of our paper is to discuss results from empirical studies in which we analysed more than 200 process models in order to evidence the practical relevance of the patterns. This includes a detailed analysis of the context in which activity patterns occur as well as the frequency of this occurrence. These empirical findings can be used for the design of more intelligent, pattern-based process modelling tools.

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.

DISCOVERY AND ANALYSIS OF ACTIVITY PATTERN CO-OCCURRENCES IN BUSINESS PROCESS MODELS

Research on workflow activity patterns recently emerged in order to increase the reuse of recurring business functions (e.g., notification, approval, and decision). One important aspect is to identify pattern cooccurrences and to utilize respective information for creating modeling recommendations regarding the most suited activity patterns to be combined with an already used one. Activity patterns as well as their cooccurrences can be identified through the analysis of process models rather than event logs. Related to this problem, this paper proposes a method for discovering and analyzing activity pattern co-occurrences in business process models. Our results are used for developing a BPM tool which fosters the modeling of business processes based on the reuse of activity patterns. Our tool includes an inference engine whichconsiders the patterns co-occurrences to give design time recommendations for pattern usage.

A survey on reuse in the business process management domain

Business process management (BPM) is an important technological support to improve organisation competitiveness. BPM can benefit from reuse approaches and techniques at several stages of the business process life cycle in order to increase dynamism, flexibility and competitiveness. Existing reuse techniques from areas such as software engineering can be extended to this emerging domain. This paper presents the results of a literature review of reuse in the BPM domain. It aims to provide an overview and an overall discussion of most relevant research projects that have been developed applying reuse in BPM.

Ontology-Based Discovery of Workflow Activity Patterns

Workflow activity patterns represent a set of recurrent behaviors that can be found in a wide range of business processes. In this paper we address the problem of determining the presence of these patterns in process models. This is usually done manually by the analyst, and it requires interpreting the process in terms of the semantics of those patterns. We describe an ontology-based approach to perform this discovery in an automated way. The approach makes use of an ontology, and a mapping between the elements in the given process and the classes in the ontology. A reasoner is then used to discover the patterns, and a SPARQL query is used to retrieve them. The approach is illustrated for a business process in a travel booking scenario.

Grouping of business processes models based on an incremental clustering algorithm using fuzzy similarity and multimodal search

A model for searching business processes, based on a multimodal approach that integrates textual and structural information.A clustering mechanism that uses a similarity function based on fuzzy logic for grouping search results.Evaluation of search method using internal quality assessment and external assessment based on human criteria. Nowadays, many companies standardize their operations through Business Process (BP), which are stored in repositories and reused when new functionalities are required. However, finding specific processes may become a cumbersome task due to the large size of these repositories. This paper presents MulTimodalGroup, a model for grouping and searching business processes. The grouping mechanism is built upon a clustering algorithm that uses a similarity function based on fuzzy logic; this grouping is performed using the results of each user request. By its part, the search is based on a multimodal representation that integrates textual and structural information of BP. The assessment of the proposed model was carried out in two phases: 1) internal quality assessment of groups and 2) external assessment of the created groups compared with an ideal set of groups. The assessment was performed using a closed BP collection designed collaboratively by 59 experts. The experimental results in each phase are promising and evidence the validity of the proposed model.

A semantic approach to the discovery of workflow activity patterns in event logs

Workflow activity patterns represent a set of recurrent behaviours that can be found in a wide range of business processes. In this paper we address the problem of determining the presence of these patterns in process models. This is usually done manually by the analyst, who inspects the model and interprets its elements in terms of the semantics of those patterns. Here, we present an approach to perform this discovery based on the event log created during process execution. The approach makes use of an ontology and the semantic annotation of the event log in order to discover the patterns automatically by means of semantic reasoning. We illustrate the application of the proposed approach in a case study involving a purchase process implemented in a commercial workflow system.

A METHOD FOR REWRITING LEGACY SYSTEMS USING BUSINESS PROCESS MANAGEMENT TECHNOLOGY

Legacy systems are systems which execute useful tasks for the organization. Unfortunately, to maintain a legacy system running is a complex and costly task. Thus, in recent years several approaches were suggested to rewrite legacy systems using contemporary technologies. In this paper we present a method for rewriting legacy systems based on Business Process Management (BPM). The use of BPM for migrating legacy systems facilitates the monitoring and continuous improvement of the information systems existing in the organization.

A distributed repository for managing business process models in cross-organizational collaborations

Cross-organizational collaborations require the management of models for: collaborative business processes (CBPs), which define the collaborations behavior; and integration business processes (IBPs), which define the behavior that supports the role an organization performs in a CBP. Managing these business process models becomes a complex task when organizations integrate collaborative networks and set up several cross-organizational collaborations. This paper presents a distributed repository that provides the functionalities required to manage conceptual business process models involved in cross-organizational collaborations. A service-oriented architecture is proposed for the distributed repository. This architecture enables organizations to access a global repository for managing collaborative networks, cross-organizational collaborations, and their CBP models. Organizations can also maintain local repositories of IBP models, which are synchronized and consistent with CBP models, while preserving their private aspects. By using verification methods and a model-driven architecture method, the distributed repository provides services that support the synchronization, consistency and interoperability requirements for CBP and IBP models. A case study is presented along with an implementation of the distributed repository.

A Semi-automatic Approach to Identify Business Process Elements in Natural Language Texts.

In organizations, business process modeling is very important to report, understand and automate processes. However, the documentation existent in organizations about such processes is mostly unstructured and difficult to be understood by analysts. The extracting of process models from textual descriptions may contribute to minimize the effort required in process modeling. In this context, this paper proposes a semi-automatic approach to identify process elements in natural language texts, which may include process descriptions. Therefore, based on the study of natural language processing, we defined a set of mapping rules to identify process elements in texts. In addition, we developed a prototype which is able to semi-automatically identify process elements in texts. Our evaluation shows promising results. The analyses of 56 texts revealed 91.92% accuracy and a case study showed that 93.33% of the participants agree with the mapping rules.