2015. No. 2 (32)

Albert Fleischmann - Owner, Interaktiv Unternehmensberatung.
Address: 16, Burgfriedenstraße, Pfaffenhofen, 85276, Germany
E-mail: albert.fleischmann@interaktiv.expert

Werner Schmidt - Professor for Business Informatics, Technische Hochschule Ingolstadt, Business School.
Address: 10, Esplanade, Ingolstadt, 85049, Germany
E-mail: werner.schmidt@thi.de

      Subject-oriented Business Process Management (S-BPM) is a relatively new approach for the overall handling of work procedures in organizations, from analysis to IT-based execution. It focuses on the acting entities in processes (people, software, robots etc.) and their interactions to achieve the process goal. The explicit stakeholder and communication orientation makes it a promising candidate to overcome the major drawbacks of traditional BPM, as there are deviations of lived processes from their specification (model-reality divide), giving away opportunities for improvement proposed by employees (lost innovation) and slow adaption of organization and IT to changing requirements.
      With its easy-to-understand and easy-to-use notation based on the Subject-Predicate-Object scheme of natural language, S-BPM facilitates semantic and organizational integration of people in the design of their work procedures. On the other hand, clear formal semantic behind the graphical notation allows automatic code generation for workflow execution at runtime. Hence, stakeholders can instantly test the models they created, and iteratively improve and complete them until they are considered ready for going live and being executed by a workflow engine. This leads to seamless roundtrip engineering based on a common understanding of both business and IT people, so it can significantly increase organizational agility.
      The article first briefly explains the properties of the S-BPM approach, and then details their impact on the BPM lifecycle activities, with regard to improving stakeholder participation and BPM lifecycle responsiveness.

Mikhail M. Komarov - Associate Professor, Department of Innovations and Business in IT, School of Business Informatics, Faculty of Business and Management, National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: mkomarov@hse.ru

Anna D. Khokhlova  - MSc Program Student, School of Business Informatics, Faculty of Business and Management, National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: khokhlova.a.d@gmail.com

      The object of this research paper is the way to organize an e-business based on the concept of smart things. In order to achieve the objective of this work - the development of a business model for Social Web of Services - several tasks were set and accomplished: existing concepts of the Internet of Things, the Internet of Service and the Web of Service were described, defined and redefined, making clear the differences and similarities between them. After this, the vision of the Social Web of Service concept is provided and several business models of service providers are reviewed based on the mentioned concept. The business models are presented in graphical view according to the business models representation methodology by Alexander Osterwalder. There is also a presentation of a new business model for a Social Web of Service company. Tis model was developed according to the analysis of existing companies, their strength points and ways of monetization, and main trends in this sphere. Moreover, some limitations of this model along with possible future development areas for it are provided. The offered paper may be considered as a novelty due to the new approach presented in it, identifying the Social Web of Service and the business model developed for companies working according to the for Social Web of Service concept, considering also companies working in areas close to Social Web of Service.

Pavel P. Oleynik - System Architect Software, Aston Company; Associate Professor, Shakhty Institute (branch), Platov South Russian State Polytechnic University (NPI).
Address: 1, Lenin square, Shakhty, Rostov Region, 346500, Russian Federation.
E-mail: xsl@list.ru

      Modern corporate information systems (CIS) are designed by employing object-oriented paradigm and concepts. This approach is often applied both to implement client applications and to build a server component (target DBMS). The application of object-oriented design pattern in software development enables to save business objects from RAM to persistent memory. This paper focuses on XOQL (XML Object Query Language) - an object query language that uses XML to describe syntax. This article presents a deep and comprehensive review of existing publications. Abundance of examples enables to demonstrate various currently available languages.
      This paper suggests a feasible option to present basic syntactic constructions of object query language in the form of XML-documents. Prior to syntax design the optimality criteria have been formulated (these are described in detail in this paper). Query language syntax extensions are outlined in addition to basic ones, as well as extension approaches by involving proprietary constructions. An optimal language structure is presented accompanied by descriptions of tags, attributes and admissible values. At the end of this article there are plenty of examples of various common queries. 

Alexey A. Neznanov - Associate Professor, School of Data Analysis and Artificial Intelligence, Faculty of Computer Science, National Research University Higher School of Economics; Head of Information-Analytical Department, Federal State Budget Institute “Federal Scientific and Clinical Centre of Pediatric Hematology, Oncology and Immunology named after Dmitry Rogachev”, Ministry of Health of the Russian Federation.  
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation.
E-mail: aneznanov@hse.ru 

Julia V. Starichkova - Deputy Head of Information-Analytical Department, Federal State Budget Institute “Federal Scientific and Clinical Centre of Pediatric Hematology, Oncology and Immunology named after Dmitry Rogachev”, Ministry of Health of the Russian Federation. 
Address: 1, Samory Mashela Street., Moscow, 117997, Russian Federation.
E-mail: julia.starichkova@fnkc.ru

      Medical information systems constitute a separate class of corporate information systems, specifically designed to improve the efficiency of healthcare. The purpose of implementation of healthcare information systems in clinical centers is to provide a comprehensive solution of information support issues associated with delivery of health services, with emphasis on the formalization of healthcare business processes, collection and secure storage of patients’ personal data, optimal interface solutions for clinicians and nurses, special management of medications and expendable supplies. Key roles of medical information system users include heads of clinical departments, doctors and nurses. This paper addresses a range of challenges relating to clinical diagnoses in medical information systems, including formalization, input efficiency, validity and completeness checking of enhanced diagnoses, as well as ex-post analysis of clinical data focusing on specific signs of diagnoses.
      Traditionally a diagnosis constitutes an unstructured text in a natural language with further assignment of codes of the International Classification of Diseases or other universal classifications. There are standardized guidelines and local conventions to insert and to change this text, but basically these conventions are not formalized in medical information systems, and that leads to the above-listed problems. A comparative analysis of the International Classification of Diseases has been conducted involving a preliminary assessment of refinements suggested by experts and actually used relating to most common pediatric oncology and hematology diseases. This paper suggests an approach to formalize an additional classification of clinical diagnoses, both simple and effective, a prototype with description of templates and schemes to enhance diagnoses for certain diseases in the JSON format and to optimize interface of the “diagnosis” standard field in medical information systems. This approach has been successfully tested in pediatric oncology information system design.   

Sergey A. Glushenko - Post-graduate student, Department of Information Systems and Applied Computer Science,
Faculty of Computer Technologies and Information Security, Rostov State Economic University (RINE).
Address: 69, Bolshaya Sadovaya street, Rostov-on-Don, 344002, Russian Federation.
E-mail: gs-gears@yandex.ru

Alexey I. Doljenko - Professor, Department of Information Systems and Applied Computer Science, Faculty of Computer Technologies and Information Security, Rostov State Economic University (RINE).
Address: 69, Bolshaya Sadovaya street, Rostov-on-Don, 344002, Russian Federation.
E-mail: doljenkoalex@gmail.com

      This paper substantiates the importance of risk analysis in implementation of an investment and construction project (ICP) and validates feasibility of fuzzy logic in risk assessment.  Application of fuzzy models enables to consider both quantitative and qualitative characteristics, as well as to represent fuzzy descriptions by using fuzzy sets and linguistic variables.
      A fuzzy production model (FPM) introduced contains 19 input linguistic variables characterizing risk factors, 14 output linguistic variables characterizing risks in different areas of the ICP. The model builds on a set of 14 rules and allows a linguistic analysis of risks, which may cause potential detriment to a project, as well as to identify risk priorities (extremely  high, high, medium, low, extremely low) that are essential for investment & construction project management. The FPM enables to remove restrictions on the number of considered input variables and to integrate both qualitative and quantitative approaches to risk assessment.
      A problem statement is formulated for risk management tools to support fuzzy models and expediency of a proprietary decision support system (DSS) for risk analysis is justified. Then this paper describes a process of fuzzy modeling of the set of rules by using ModelingFuzzySet DSS that has been developed. Mamdani algorithm-based risk assessment mechanism enables to quantify risk, to obtain a linguistic description of a risk and expert’s degree of confidence relating to risk occurrence. 
      The simulation results have been used by decision-makers to identify risk priorities and allowed to develop an effective action plan to mitigate the impact of the most dangerous threats faced by an investment & construction project.

Zaur N. Ismikhanov - Associate Professor, Department of Mathematical and Natural Sciences, Faculty of Management, Dagestan State University
Address: 43A, Gadjieva Street, Makhachkala, Republic of Dagestan, 367000, Russian Federation.
E-mail:Zaur_7979@mail.ru
      The issues related to cognitive structuring of subject area and cognitive model building, as well as with scenario modeling of situation dynamics in the social and economic domains of the Republic of Dagestan are considered and solved.
      The first task is solved on the basis of a SWOT analysis of the main problems related to the current situation and tendencies of Dagestan’s development. This solution helped to reveal the main factors of the current situation and prospects of the republic’s social and economic development. The cognitive model of the regional social and economic system has been created. A cognitive model is a functional graph of the considered system, where the peaks correspond to the system factors, and the curves reflect their functional interdependence.
      The second task is solved with the help of the Ditch (“Kanava”) cognitive modeling system. A cognitive model was used to forecast the scenario of target social and economic indicators depending on the managing factors’ influence. .
      The results of forecasting the regional social and economic development are obtained on the basis of impulse modeling. They help to reveal the social, economic and political patterns of warning and preventing negative tendencies of social and economic development, obtain theoretical and practical knowledge of problems in the region, and formulate practical conclusion on this basis. In particular, it is offered to enhance the activity of the governing bodies, in order to reduce the administrative and corruptive pressure on business. This will lead to the increase of the investment attractiveness level of the republic. The problem of unemployment can be solved by efficient use of reserves and resources for small business development.

Tatiana K. Kravchenko - Professor, Head of Department of Business Analytics, School of Business Informatics, Faculty of Business and Management, National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: tkravchenko@hse.ru

Alexey A. Druzhaev - Associate Professor, Department of Business Analytics, School of Business Informatics, Faculty of Business and Management, National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: druzhaev@hse.ru

      Analytical justification of solutions using a decision support system (DSS) significantly increases the quality of decisions. The existing DSS generally employs 1 or 2 methods of decision-making. It does not always lead to the desired results, as each method is based on certain assumptions and is not universal. The maximum effect can be achieved only insofar a set of decision-making methods is included into the knowledge base of the DSS. The only system that meets these requirements is the Expert Decision Support System (EDSS) developed under supervision of the author. Currently the EDSS includes about 50 decision-making methods. The expansion of the EDSS knowledge base by including new methods will allow for choosing the most suitable method for solving each decision-making task.
      Enhancing the Decision Table model underlying the system knowledge base allows you to develop the EDSS without complete reworking of the system code. The system knowledge base contains decision rules built on the principle of “if... then...” (if certain conditions of decision making exist, then a definite method of decision-making should be employed). To expand the EDSS knowledge base, ELECTRE collection methods were selected. Their key feature consists in not using the convolution operation of evaluation of the alternatives specified in different scales on individual criteria. This was the reason for selecting the methods of this family. In the article, the algorithms of these methods are adapted for their inclusion in the EDSS. An algorithm for obtaining a criterion-alternative matrix is proposed. It serves as input information for the ELECTRE family methods in cases where there is no objective information for its formation.
      The results of the study can be used to develop the EDSS, allowing analytical justification of solutions using methods that have not previously been used in the system.