E-Government Services: Comparing Real and Expected User Behavior
E-government web services are becoming increasingly popular among citizens of various countries. Usually, to receive a service, the user has to perform a sequence of steps. This sequence of steps forms a service rendering process. Using process mining techniques this process can be discovered from the information system’s event logs. A discovered process model of a real user behavior can assist in the analysis of service usability. Thus, for popular and well-designed services this process model will coincide with a reference process model of the expected user behavior. While for other services the observed real behavior and the modeled expected behavior can differ significantly. The main aim of this work is to suggest an approach for the comparison of process models and evaluate its applicability when applied to real-life e-government services.
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 chapter explores Russia’s implementation of the national e-government strategy and information policies. . Based on official, national strategic documents and a number of e-government cases that highlight different projects at the federal and regional levels, we outline the formidable barriers and idiosyncrasies of managing e-government development in Russia.
The 1st International Conference on Electronic Governance and Open Society: Challenges in Eurasia, EGOSE2014 took place in St Petersburg, Russia from 18-20 November 2014. It was the first international academic event in the field e-Governance ever held entirely in the English language in the vast Eurasian region comprising mainly the post-Soviet states. It was designed as an opportunity for researchers and practitioners from Eurasia to discuss the use of digital technologies in and for governance with their peers from other regions and thus help integrate closer into a global academic community. Specific issues that conference planned to address focused on the current and emerging challenges these countries are facing in developing sound and effective e-Governance solutions that promote public sector innovations both in terms of administrative efficiency and governance openness. The goal was to seek other regions' experiences to compare approaches, solutions, practices and thus to raise eventually the quality of research at the crossroads of technology, government and society in the region, which is lagging behind from other regions. The Conference was seen as new opportunity for researchers to publish the results of their studies in the global context.
Nowadays information technologies become integral part of developing society. Enormous volumes and speed of information transfer make sufficiency and efficiency of obtaining the information the main condition of development of the public relations. It can be provided by introduction of nowaday information telecommunication technologies.
The 6th International Conference on Theory and Practice of Electronic Governance, ICEGOV2012, was organized in Albany, New York, United States (US) from the 22nd to the 25th of October 2012, hosted by the Center for Technology in Government, University at Albany, State University of New York under the patronage of the United States National Archives and Record Administration. The ICEGOV (International Conference on Theory and Practice of Electronic Governance) series focuses on the use of technology to transform relationships between government and citizens, businesses, civil society and other arms of government (Electronic Governance).
Process mining is a relatively new field of computer science, which deals with process discovery and analysis based on event logs. In this paper we consider the problem of models and event logs conformance checking. Conformance checking is intensively studied in the frame of process mining research, but only models and event logs of the same granularity were considered in the literature. Here we present and justify the method of checking conformance between a high-level model (e.g. built by an expert) and a low-level log (generated by a system).
The article discusses the bureucratization of the legislative and executive authorities at the re gional level, starting from the stage of formation of Russian (centralixed) state to the analysis of the current situation in the country.
Operational processes leave trails in the information systems supporting them. Such event data are the starting point for process mining – an emerging scientific discipline relating modeled and observed behavior. The relevance of process mining is increasing as more and more event data become available. The increasing volume of such data (“Big Data”) provides both opportunities and challenges for process mining. In this paper we focus on two particular types of process mining: process discovery (learning a process model from example behavior recorded in an event log) and conformance checking (diagnosing and quantifying discrepancies between observed behavior and modeled behavior). These tasks become challenging when there are hundreds or even thousands of different activities and millions of cases. Typically, process mining algorithms are linear in the number of cases and exponential in the number of different activities. This paper proposes a very general divide-and-conquer approach that decomposes the event log based on a partitioning of activities. Unlike existing approaches, this paper does not assume a particular process representation (e.g., Petri nets or BPMN) and allows for various decomposition strategies (e.g., SESE- or passage-based decomposition). Moreover, the generic divide-and-conquer approach reveals the core requirements for decomposing process discovery and conformance checking problems.