Jorge Roa

A Modeling Approach for Collaborative Business Processes Based on the UP-ColBPIP Language

The modeling of collaborative business processes is an important issue in order to allow enterprises to implement B2B collaborations with their business partners. We have proposed an MDA-based methodology for the modeling, verification and implementation of collaborative processes. Since collaborative process models are the main artifacts in this MDA-based methodology, a suitable modeling approach is required to design collaborative processes. In this work we describe a modeling approach for collaborative processes based on the UP-ColBPIP language, which is oriented to support the model-driven development of collaborative processes and B2B information systems. The behavior of collaborative processes is modeled through interaction protocols. Enhances to the control flow constructors of interaction protocols are introduced. In addition, we describe an Eclipse-based tool that supports this language.

A Verification Method for Collaborative Business Processes

The verification of collaborative processes is a key issue to consider in cross-organizational modeling methodologies. Some of the existing verification approaches provide only partial support, whereas others impose some restrictions to verify models with advanced control flow, compromise (completely or partially) the enterprise autonomy, or are focused on technology-dependent specifications. In order to deal with these issues we introduce Global Interaction Nets, which are based on Hierarchical and Colored Petri Nets, and the Global Interaction Soundness property, which was adapted from the classical definition of soundness, as the main correctness criterion. The method can be used to formalize and verify models defined with different modeling languages. In addition, we apply the method through a case study modeled with UP-ColBPIP, which is a modeling language for collaborative processes, and formalize its constructs by means of Global Interaction Nets.

Model-Driven Development Methodology for B2B Collaborations

The design and implementation of collaborative business processes and the Business-to-Business (B2B) systems that support them is an important issue in order to enable enterprises to set up B2B collaborations. This involves new challenges, mainly regarding the ability to cope with change, decentralized management, peer-to-peer interactions, preservation of enterprise autonomy, and the support for interoperability. The design and implementation of B2B collaborations require the use of conceptual models that differ in viewpoint, target people, abstraction level and granularity. This makes the use of traditional software development methodologies inappropriate. In this paper, we propose a methodology for the design and implementation of B2B collaborations that support the above issues. The methodology supports a development framework and is based on the Model-Driven Development (MDD). The methodology provides guidelines, languages, methods, model transformations and tools to support the representation of business requirements, the definition of technology-independent collaborative process models, the derivation of technology-independent processes and IT architectures that enterprises require to support collaborative processes as well as the generation of a technology-specific solution for each enterprise. This methodology guarantees the alignment and consistency between the business and technological solutions for B2B collaborations.

Specification of behavioral anti-patterns for the verification of block-structured Collaborative Business Processes

Context: The verification of the control flow of a Collaborative Business Process (CBP) is important when developing cross-organizational systems, since the control flow defines the behavior of the cross-organizational collaboration. Behavioral anti-patterns have been proposed to improve the performance of formal verification methods. However, a systematic approach for the discovery and specification of behavioral anti-patterns of CBPs has not been proposed so far.Objective: The aim of this work is an approach to systematically discover and specify the behavioral anti-patterns of block-structured CBP models.Method: The approach proposes using the metamodel of a CBP language to discover all possible combinations of constructs leading to a problem in the behavior of block-structured CBPs. Each combination is called minimal CBP. The set of all minimal CBPs with behavioral problems defines the unsoundness profile of a CBP language, from which is possible specifying the behavioral anti-patterns of such language.Results: The approach for specification of behavioral anti-patterns was applied to the UP-ColBPIP language. Twelve behavioral anti-patterns were defined, including support to complex control flow such as advanced synchronization, cancellation and exception management, and multiple instances. Anti-patterns were evaluated on a repository of block-structured CBP models and compared with a formal verification method. Results show that the verification based on anti-patterns is as accurate as the formal method, but it clearly improves the performance of the latter.Conclusion: By using the proposed approach, it is possible to systematically specify behavioral anti-patterns for block-structured CBP languages. During the discovery of anti-patterns different formalisms can be used. With this approach, the specification of anti-patterns provides the exact combination of elements that can cause a problem, making error correction and result interpretation easier. Although the proposed approach was defined for the context of CBPs, it could be applied to the context of intra-organizational processes.

Ontology-Based Heuristics for Process Behavior: Formalizing False Positive Scenarios

Verification methods to detect errors in the behavior of process models can be formal or informal. The former are based on formal languages, whereas the latter are based on heuristics. The main advantage of informal methods with respect to the formal ones is their short run-time. However, heuristics may lead to false positives, i.e. they may detect errors in a process model even though such model is correct. In this work, we propose using ontologies to formalize heuristics that avoid false positive scenarios. With ontologies it is possible to avoid ambiguities in heuristics that may lead to inaccurate implementations and to enable their execution by ontology reasoners. To this aim, we propose a set of false positive scenarios and define SWRL rules and SPARQL queries to formalize heuristics for such scenarios by means of ontologies. In addition, we identified three requirements that should be met in order to formalize heuristics and their false positive scenarios.

Institutional Violence Complaints in Argentina: A Privacy Study

Argentina is a federal republic located in South America. Despite Argentina’s redemocratization in 1983, conditions favoring human rights abuses still persist. Institutional violence refers to structured practices of human rights violation by state officials belonging to public institutions. In this paper, we outline and discuss privacy issues in institutional violence complaints in Argentina. To this aim, we defined a BPMN process model for registering victims’ complaints in a database, and proposed an approach to investigate the privacy of such process from a threat modeling perspective. With the approach, we identified privacy threats of information disclosure and content unawareness, and defined privacy requirements and controls needed to mitigate these threats.

Towards Ontology-Based Anti-patterns for the Verification of Business Process Behavior

A business process model defines how an organization perform its activities. Since the incorrect definition of business processes behavior may increase costs and development time, it is required the verification of process behavior. Verification methods based on anti-patterns are a promising approach to deal with this issue, but their informal definition may lead to ambiguities and different interpretations of what problem a given anti-pattern represents, and how it should be applied or implemented to detect behavioral errors in process models. The aim of this paper is to assess the feasibility of business process behavior verification by means of the ontological specification of behavioral anti-patterns. The study is based on the detection of anti-patterns in a BPMN process model by exploiting a set of standard ontological reasoning services.

Formal Semantics for Modeling Collaborative Business Processes Based on Interaction Protocols

Collaborative business processes (CBPs) are expected to conduct the behavior among organizations that participate in collaborative networks. Although languages for CBPs emerged from the industry and academic sides, not much effort has been put to add formal semantics to the constructs of the languages to reason on structural aspects of CBP models. In particular, the UP-ColBPIP language supports the modeling of collaborative business processes in terms of interaction protocols, which describes a choreography of business messages based on speech acts. This paper presents an approach to add formal semantics to the UP-ColBPIP language, by defining an OntoUML conceptual model of the constructs that allows modeling CBPs as interaction protocols. The formal semantics of the constructs of UP-ColBPIP enables the definition of design guidelines and the development of techniques for the structural analysis of CBP models represented in terms of interaction protocols. Finally, the work depicts an OWL ontology implementing the proposed conceptual model, with the purpose of answering queries about the messages based on speech acts as well as other structural aspects of CBP models.

A Survey on Purchase Intention of Hello Barbie in Brazil and Argentina

Children’s toys have become increasingly sophisticated over the years, with a growing shift from simple physical products to toys that engage the digital world by the use of software and hardware. A smart toy, such as Hello Barbie, is defined as a device consisting of a physical toy component that connects to a computing system with online services through networking to enhance the functionality of a traditional toy. Hello Barbie is introduced by Mattel as “the first fashion doll that can have a two-way conversation with girls” with speech recognition and online connection to Cloud computing technologies. While the doll is made by Mattel, the online English conversation software is powered by ToyTalk.com. The targeted players are 7–13 years old children. Adding the ability of speech recognition and online connection raises the risk of privacy breaches in children. Since its introduction in February 2015, Hello Barbie has been criticized for the negative effects on children along with privacy concerns in the United States How will consumers in other countries react to this type of smart toys. The main objective of this paper is to present a survey of purchase intention of Hello Barbie in Brazil and Argentina, where consumers still have not been massively presented to this type of smart toy. Our results indicate that Brazilian consumers have better perception and evaluation of the toy and thus higher purchase intention toward the toy than Argentinian consumers do. Such difference is explained by the culture differences between the two countries, such as relatively low vs. high uncertainty avoidance.