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Proceedings of the BPM Demo Session 2015. Co-located with the 13th International Conference on Business Process Management (BPM 2015)
This volume collects the descriptions of the demonstrations that were presented at the 13th International Conference on Business Process Management (BPM), which was held from August 31st to September 3rd, 2015, in Innsbruck, Austria. The conference brings together researchers and practitioners alike and represents one of the most prestigious scienti c events on BPM worldwide. BPM is an area of research that is strongly intertwined with practice, and the demonstration track assumes a major role in the program of the conference. It allows everybody to showcase novel software solutions related to the topics of the conference, ranging, for example, from process modeling tools for end{users to low{level process mining algorithms running hidden in a back{oce or in the cloud. This year we got an exceptional number of 40 submissions of demonstration proposals. While, on the one hand, this is an extraordinary result, on the other hand, it also meant that we had to carefully select the proposals with the help of the PC of the Demo track. Unfortunately, space and equipment are limited, and we could not accommodate everybody. In the end, 28 demonstrations were selected for presentation and are printed in this volume. We are proud about the nal demo program of this year's edition of the conference, which we believe is of very high quality, and we are con dent that it contains something interesting for everybody working on BPM and related topics. We would like the thank everybody who contributed to the demo program: the authors, the PC members, and of course the organizers of the conference. It was a pleasure working with you.
Automatic comparison of business processes plays an important role
in their analysis and optimization. In this paper we present the web-based tool
BPMNDiffViz, that finds business processes discrepancies and visualizes them.
BPMN (Business Process Model and Notation) 2.0 - one of the most commonly
used notations for process modeling was chosen as a representation. This tool
implements a structural graph-based comparison analysis using an A* algorithm.
Process mining techniques relate observed behavior to modeled behavior, e.g., the automatic discovery of a process model based on an event log. Process mining is not limited to process discovery and also includes conformance checking and model enhancement. Conformance checking techniques are used to diagnose the deviations of the observed behavior as recorded in the event log from some process model. Model enhancement allows to extend process models using additional perspectives, conformance and performance information. In recent years, BPMN (Business Process Model and Notation) 2.0 has become a de facto standard for modeling business processes in industry. This paper presents the BPMN support current in ProM. ProM is the most known and used open-source process mining framework. ProM’s functionalities of discovering, analyzing and enhancing BPMN models are discussed. Support of the BPMN 2.0 standard will help ProM users to bridge the gap between formal models (such as Petri nets, causal nets and others) and process models used by practitioners.
This volume contains a set of dedicated scientific contributions to the 11th International Conference on Perspectives in Business Informatics Research. The peer-reviewed and tentatively selected papers cover a broad scope of modern research in Business Informatics, and include new results in such domains as: Knowledge Management and Semantic Web, Business and information systems development, Business, people and systems interoperability and Business intelligence.
In 2012 the conference is hosted by National Research University Higher School of Economics (NRU HSE) in Nizhny Novgorod. Our university is Russia’s leader in the field of scientific research conducted at the junction of Management, Economics and Governance of IT. In particular, NRU HSE is the originator and the promoter of Business Informatics in Russia. Therefore NRU HSE pays particular attention to sustainable international cooperation and leverages scientific research in that area.
We strongly believe that materials presented will contribute to further advances in Business Informatics and will foster intensive scientific cooperation between researchers.
To large organizations, business intelligence (BI) promises the capability of collecting and analyzing internal and external data to generate knowledge and value, thus providing decision support at the strategic, tactical, and operational levels. BI is now impacted by the “Big Data” phenomena and the evolution of society and users. In particular, BI applications must cope with additional heterogeneous (often Web-based) sources, e.g., from social networks, blogs, competitors’, suppliers’, or distributors’ data, governmental or NGO-based analysis and papers, or from research publications. In addition, they must be able to provide their results also on mobile devices, taking into account location-based or time-based environmental data. The lectures held at the Third European Business Intelligence Summer School (eBISS), which are presented here in an extended and refined format, cover not only established BI and BPM technologies, but extend into innovative aspects that are important in this new environment and for novel applications, e.g., pattern and process mining, business semantics, Linked Open Data, and large-scale data management and analysis. Combining papers by leading researchers in the field, this volume equips the reader with the state-of-the-art background necessary for creating the future of BI. It also provides the reader with an excellent basis and many pointers for further research in this growing field.
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Since their inception in 1962, Petri nets have been used in a wide variety of application domains. Although Petri nets are graphical and easy to understand, they have formal semantics and allow for analysis techniques ranging from model checking and structural analysis to process mining and performance analysis. Over time Petri nets emerged as a solid foundation for Business Process Management (BPM) research. The BPM discipline develops methods, techniques, and tools to support the design, enactment, management, and analysis of operational business processes. Mainstream business process modeling notations and workflow management systems are using token-based semantics borrowed from Petri nets. Moreover, state-of-the-art BPM analysis techniques are using Petri nets as an internal representation. Users of BPM methods and tools are often not aware of this. This paper aims to unveil the seminal role of Petri nets in BPM.
The research reported in this paper aims at introducing principally new approach to the design of traceability applications for supply network by the means of semantically consistent and conceptually aligned abstractions of business-processes, data, and software architecture. To derive needed abstractions, proposed approach uses the general principles of enterprise ontology for meta-description of business objects and processes, conceptual modeling techniques for data representation in a universal format, and multi-agent solution adjusted with an ontological view on data model and business processes of organizations. The method for data modeling consistent with the business view on supply chain activities is introduced and exemplified. Agent-based approach to tracing data analysis and particular model of intellectual agents are presented.
Key performance indicators (KPI) present an effective, high-precision framework for continuous monitoring of target achievements. The KPI framework has proved itself to be a functional tool within different economic sectors in series of large and mid-size companies. Notwithstanding all ad- vantages and effects of the implementation of KPI framework, it cannot be used for assessment and monitoring of operational risk level that was accepted for achievement of defined targets. Switching towards a risk-balanced approach in process management requires the definition and implementation of framework for monitoring the compliance of company risk-profile with its risk-tolerance. This requirement results in a key risk indicators KRI framework. The article provides an example of deve- loping a set of KRI for internal information system.
In order to support management functions in dynamically changing corporate enterprises, adequate information systems need to be built, automating desirable adaptation of inter- and intra- organizational business processes. This paper therefore introduces a new approach to the design of multi-agent information systems meant for planning, discovering, monitoring deviations, and optimizing business processes. Expected qualitative breakthrough in the system’s capacity is based on the matching of its constructional and behavioral perspective with the ontological model of supported enterprise. Besides, conformity between organizational and information systems is supplemented by their conceptual alignment in the description of states and processes. The method of multi-agent framework construction and its application for traceability in supply chains are presented in this paper.
This article is devoted to study of management evolution in approaches for Business Process Management (BPM). Research is based on the taking into account 2 factors: standardization of approaches for BPM; and scope of enterprise as reflexive management. Authors used own consulting experience and intermediate results of the scientific researches carried out in State University HSE.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traffic is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the final node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a finite-dimensional system of differential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of differential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.
I give the explicit formula for the (set-theoretical) system of Resultants of m+1 homogeneous polynomials in n+1 variables