On separation of concurrency and conflicts in acyclic process models

Recently, a new approach for structuring acyclic process models has been introduced. The algorithm is based on a transformation between the Refined Process Structure Tree (RPST) of a control flow graph and the Modular Decomposition Tree (MDT) of ordering relations. In this paper, an extension of the algorithm is presented that allows to partially structure process models in the case when a process model cannot be structured completely. We distinguish four different types of unstructuredness of process models and show that only two are possible in practice. For one of these two types of unstructuredness an algorithm is proposed that returns the maximally structured representation of a process model.

Weak conformance of process models with respect to data objects

Process models specify behavioral aspects by describing ordering constraints between tasks which must be accomplished to achieve envisioned goals. Tasks usually exchange information by means of data objects, i.e., by writing information to and reading information from data objects. A data object can be characterized by its states and allowed state transitions. In this paper, we propose a notion which checks conformance of a process model with respect to data objects that its tasks access. This new notion can be used to tell whether in every execution of a process model each time a task needs to access a data object in a particular state, it is ensured that the data object is in the expected state or can reach the expected state and, hence, the process model can achieve its goals.

Structural abstraction of process specifications

Software engineers constantly deal with problems of designing, analyzing, and improving process specifications, e.g., source code, service compositions, or process models. Process specifications are abstractions of behavior observed or intended to be implemented in reality which result from creative engineering practice. Usually, process specifications are formalized as directed graphs in which edges capture temporal relations between decisions, synchronization points, and work activities. Every process specification is a compromise between two points: On the one hand engineers strive to operate with less modeling constructs which conceal irrelevant details, while on the other hand the details are required to achieve the desired level of customization for envisioned process scenarios. In our research, we approach the problem of varying abstraction levels of process specifications. Formally, developed abstraction mechanisms exploit the structure of a process specification and allow the generalization of low-level details into concepts of a higher abstraction level. The reverse procedure can be addressed as process specialization.

Structuring acyclic process models

This paper addresses the problem of transforming a process model with an arbitrary topology into an equivalent well-structured process model. While this problem has received significant attention, there is still no full characterization of the class of unstructured process models that can be transformed into well-structured ones, nor an automated method to structure any process model that belongs to this class. This paper fills this gap in the context of acyclic process models. The paper defines a necessary and sufficient condition for an unstructured process model to have an equivalent structured model under fully concurrent bisimulation, as well as a complete structuring method.

Unveiling hidden unstructured regions in process models

Process models define allowed process execution scenarios. The models are usually depicted as directed graphs, with gateway nodes regulating the control flow routing logic and with edges specifying the execution order constraints between tasks. While arbitrarily structured control flow patterns in process models complicate model analysis, they also permit creativity and full expressiveness when capturing non-trivial process scenarios. This paper gives a classification of arbitrarily structured process models based on the hierarchical process model decomposition technique. We identify a structural class of models consisting of block structured patterns which, when combined, define complex execution scenarios spanning across the individual patterns. We show that complex behavior can be localized by examining structural relations of loops in hidden unstructured regions of control flow. The correctness of the behavior of process models within these regions can be validated in linear time. These observations allow us to suggest techniques for transforming hidden unstructured regions into block-structured ones.

Business process model abstraction

In order to execute, study, or improve operating procedures, companies document them as business process models. Often, business process analysts capture every single exception handling or alternative task handling scenario within a model. Such a tendency results in large process specifications. The core process logic becomes hidden in numerous modeling constructs. To fulfill different tasks, companies develop several model variants of the same business process at different abstraction levels. Afterwards, maintenance of such model groups involves a lot of synchronization effort and is erroneous. We propose an abstraction technique that allows generalization of process models. Business process model abstraction assumes a detailed model of a process to be available and derives coarse-grained models from it. The task of abstraction is to tell significant model elements from insignificant ones and to reduce the latter. We propose to learn insignificant process elements from supplementary model information, e.g., task execution time or frequency of task occurrence. Finally, we discuss a mechanism for user control of the model abstraction level – an abstraction slider.

On application of structural decomposition for process model abstraction

Real world business process models may consist of hundreds of elements and have sophisticated structure. Although there are tasks where such models are valuable and appreciated, in general complexity has a negative influence on model comprehension and analysis. Thus, means for managing the complexity of process models are needed. One approach is abstraction of business process models-creation of a process model which preserves the main features of the initial elaborate process model, but leaves out insignificant details. In this paper we study the structural aspects of process model abstraction and introduce an abstraction approach based on process structure trees (PST). The developed approach assures that the abstracted process model preserves the ordering constraints of the initial model. It surpasses pattern-based process model abstraction approaches, allowing to handle graph-structured process models of arbitrary structure. We also provide an evaluation of the proposed approach.

The triconnected abstraction of process models

Companies use business process models to represent their working procedures in order to deploy services to markets, to analyze them, and to improve upon them. Competitive markets necessitate complex procedures, which lead to large process specifications with sophisticated structures. Real world process models can often incorporate hundreds of modeling constructs. While a large degree of detail complicates the comprehension of the processes, it is essential to many analysis tasks. This paper presents a technique to abstract, i.e., to simplify process models. Given a detailed model, we introduce abstraction rules which generalize process fragments in order to bring the model to a higher abstraction level. The approach is suited for the abstraction of large process specifications in order to aid model comprehension as well as decomposing problems of process model analysis. The work is based on process structure trees that have recently been introduced to the field of business process management.

Process model abstraction : a slider approach

Process models provide companies efficient means for managing their business processes. Tasks where process models are employed are different by nature and require models of various abstraction levels. However, maintaining several models of one business process involves a lot of synchronization effort and is erroneous. Business process model abstraction assumes a detailed model of a process to be available and derives coarse grained models from it. The task of abstraction is to tell significant model elements from insignificant ones and to reduce the latter. In this paper we argue that process model abstraction can be driven by different abstraction criteria. Criterion choice depends on a task which abstraction facilitates. We propose an abstraction slider - a mechanism that allows user control of the model abstraction level. We discuss examples of combining the slider with different abstraction criteria and sets of process model transformation rules.

Simplified computation and generalization of the refined process structure tree

A business process is often modeled using some kind of a directed flow graph, which we call a workflow graph. The Refined Process Structure Tree (RPST) is a technique for workflow graph parsing, i.e., for discovering the structure of a workflow graph, which has various applications. In this paper, we provide two improvements to the RPST. First, we propose an alternative way to compute the RPST that is simpler than the one developed originally. In particular, the computation reduces to constructing the tree of the triconnected components of a workflow graph in the special case when every node has at most one incoming or at most one outgoing edge. Such graphs occur frequently in applications. Secondly, we extend the applicability of the RPST. Originally, the RPST was applicable only to graphs with a single source and single sink such that the completed version of the graph is biconnected. We lift both restrictions. Therefore, the RPST is then applicable to arbitrary directed graphs such that every node is on a path from some source to some sink. This includes graphs with multiple sources and/or sinks and disconnected graphs.

Flexible process graph : a prologue

Businesses document their operational processes as process models. The common practice is to represent process models as directed graphs. The nodes of a process graph represent activities and directed edges constitute activity ordering constraints. A flexible process graph modeling approach proposes to generalize process graph structure to a hypergraph. Obtained process structure aims at formalization of ad-hoc process control flow. In this paper we discuss aspects relevant to concurrent execution of process activities in a collaborative manner organized as a flexible process graph. We provide a real world flexible process scenario to illustrate the approach.

Amateur Media : Social, Cultural and Legal Perspectives

The rise of Web 2.0 has pushed the amateur to the forefront of public discourse, public policy and media scholarship. Typically non-salaried, non-specialist and untrained in media production, amateur producers are now seen as key drivers of the creative economy. But how do the activities of citizen journalists, fan fiction writers and bedroom musicians connect with longer traditions of extra-institutional media production? This edited collection provides a much-needed interdisciplinary contextualisation of amateur media before and after Web 2.0. Surveying the institutional, economic and legal construction of the amateur media producer via a series of case studies, it features contributions from experts in the fields of law, economics and media studies based in the UK, Europe and Singapore. Each section of the book contains a detailed case study on a selected topic, followed by two further pieces providing additional analysis and commentary. Using an extraordinary array of case studies and examples, from YouTube to online games, from subtitling communities to reality TV, the book is neither a celebration of amateur production nor a denunciation of the demise of professional media industries. Rather, this book presents a critical dialogue across law and the humanities, exploring the dynamic tensions and interdependencies between amateur and professional creative production. This book will appeal to both academics and students of intellectual property and media law, as well as to scholars and students of economics, media, cultural and internet studies.

Teaching and using analogy in law

Analogy plays a central role in legal reasoning, yet how to analogize is poorly taught and poorly practiced. We all recognize when legal analogies are being made: when a law professor suggests a difficult hypothetical in class and a student tentatively guesses at the answer based on the cases she read the night before, when an attorney advises a client to settle because a previous case goes against him, or when a judge adopts one precedent over another on the basis that it better fits the present case. However, when it comes to explaining why certain analogies are compelling, persuasive, or better than the alternative, lawyers usually draw a blank. The purpose of this article is to provide a simple model that can be used to teach and to learn how analogy actually works, and what makes one analogy superior to a competing analogy. The model is drawn from a number of theories of analogy making in cognitive science. Cognitive science is the “long-term enterprise to understand the mind scientifically.” The field studies the mechanisms that are involved in cognitive processes like thinking, memory, learning, and recall; and one of its main foci has been on how people construct analogies. The lessons from cognitive science theories of analogy can be applied to legal analogies to give students and lawyers a better understanding of this fundamental process in legal reasoning.

Expanding horizons : scientific frontiers, legal regulation, and globalization

In the six decades since the discovery of the double helix structure of DNA by Watson and Crick in 1953, developments in genetic science have transformed our understanding of human health and disease. These developments, along with those in other areas such as computer science, biotechnology, and nanotechnology, have opened exciting new possibilities for the future. In addition, the increasing trend for technologies to converge and build upon each other potentially increases the pace of change, constantly expanding the boundaries of the scientific frontier. At the same time, however, scientific advances are often accompanied by public unease over the potential for unforeseen, negative outcomes. For governments, these issues present significant challenges for effective regulation. This Article analyzes the challenges associated with crafting laws for rapidly changing science and technology. It considers whether we need to regulate, how best to regulate for converging technologies, and how best to ensure the continued relevance of laws in the face of change.