A Model-Driven Approach for Business Process Management

The Business Process Management is a common mechanism recommended by a high number of standards for the management of companies and organizations. In software companies this practice is every day more accepted and companies have to assume it, if they want to be competitive. However, the effective definition of these processes and mainly their maintenance and execution are not always easy tasks. This paper presents an approach based on the Model-Driven paradigm for Business Process Management in software companies. This solution offers a suitable mechanism that was implemented successfully in different companies with a tool case named NDTQ-Framework.Ministerio de Educación y Ciencia TIN2010-20057-C03-02Junta de Andalucía TIC-578

A methodological proposal and tool support for the HL7 standards compliance in the development of health information systems

Health information systems are increasingly complex, and their development is presented as a challenge for software development companies offering quality, maintainable and interoperable products. HL7 (Health level 7) International, an international non-profit organization, defines and maintains standards related to health information systems. However, the modelling languages proposed by HL7 are far removed from standard languages and widely known by software engineers. In these lines, NDT is a software development methodology that has a support tool called NDT-Suite and is based, on the one hand, on the paradigm of model-driven engineering and, on the other hand, in UML that is a widely recognized standard language. This paper proposes an extension of the NDT methodology called MoDHE (Model Driven Health Engineering) to offer software engineers a methodology capable of modelling health information systems conforming to HL7 using UML domain models

Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines

Background: Multiple imputation (MI) provides an effective approach to handle missing covariate data within prognostic modelling studies, as it can properly account for the missing data uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling techniques to obtain the estimates of interest. The estimates from each imputed dataset are then combined into one overall estimate and variance, incorporating both the within and between imputation variability. Rubin's rules for combining these multiply imputed estimates are based on asymptotic theory. The resulting combined estimates may be more accurate if the posterior distribution of the population parameter of interest is better approximated by the normal distribution. However, the normality assumption may not be appropriate for all the parameters of interest when analysing prognostic modelling studies, such as predicted survival probabilities and model performance measures. Methods: Guidelines for combining the estimates of interest when analysing prognostic modelling studies are provided. A literature review is performed to identify current practice for combining such estimates in prognostic modelling studies. Results: Methods for combining all reported estimates after MI were not well reported in the current literature. Rubin's rules without applying any transformations were the standard approach used, when any method was stated. Conclusion: The proposed simple guidelines for combining estimates after MI may lead to a wider and more appropriate use of MI in future prognostic modelling studies

Multiple Approaches to Absenteeism Analysis

Absenteeism research has often been criticized for using inappropriate analysis. Characteristics of absence data, notably that it is usually truncated and skewed, violate assumptions of OLS regression; however, OLS and correlation analysis remain the dominant models of absenteeism research. This piece compares eight models that may be appropriate for analyzing absence data. Specifically, this piece discusses and uses OLS regression, OLS regression with a transformed dependent variable, the Tobit model, Poisson regression, Overdispersed Poisson regression, the Negative Binomial model, Ordinal Logistic regression, and the Ordinal Probit model. A simulation methodology is employed to determine the extent to which each model is likely to produce false positives. Simulations vary with respect to the shape of the dependent variable\u27s distribution, sample size, and the shape of the independent variables\u27 distributions. Actual data,based on a sample of 195 manufacturing employees, is used to illustrate how these models might be used to analyze a real data set. Results from the simulation suggest that, despite methodological expectations, OLS regression does not produce significantly more false positives than expected at various alpha levels. However, the Tobit and Poisson models are often shown to yield too many false positives. A number of other models yield less than the expected number of false positives, thus suggesting that they may serve well as conservative hypothesis tests

The Research of Technological Approach to the Modeling of Information and Analytic Provision of Managing an Enterprise

The article is devoted to the solution of actual problems of innovative development of information and analytical provision of managing an enterprise according to the newest technology. A number of recommendations concerning technological upgrading foundation of modernization of information and analytic provision of managing an enterprise are elaborated. Technological approach to the modeling of information provision of business management is substantiated. Actualizing information and analytic provision of managing an enterprise has been carried out in developed flexible information system that is organized as internal network structure. Technological foundation of information and analytical process enterprise to modernize has been considered based on the modern tools of information and communication decisions. Information and analytical provision of managing have been developed through internal and external parallels of impact, which interconnection coordinates theory, methodology and organization of information processes with actualization of its model. The model of information and analytic provision of managing an enterprise according to the individual characteristics of corporate culture, and information environment and development strategy of business entity on the basis of characteristics of technological provision of information process is developed. Information complex has been suggested as developed system with technological process of forming initial data and modernizing processing, transmission and storage of information in accordance with distinctive characteristics of enterprise and general tendencies of its developmen

A theoretical framework for analysing the contribution of education to sustainable peacebuilding: 4Rs in conflict-affected contexts

This paper presents the theoretical and analytic framework for a Research Consortium on Education and Peacebuilding supported by UNICEF’s Peacebuilding, Education and Advocacy (PBEA) programme which began in July 2014 led by the Universities of Amsterdam, Sussex and Ulster. The consortium seeks to build knowledge on the relationship between education and peacebuilding in conflict‐affected contexts and has emerged out of a long‐standing relationship between the authors, UNICEF and the Ministry of Foreign Affairs of the Government of the Netherlands that stretches back to 2006

Principles of forming a modern accounting and analytical model of commercial organization in digital economy

Purpose: The article presents basic methodological approaches to the creation of a new model of forming and functioning of the accounting and analytical system to meet the information needs of internal and external stakeholders of organizations. Design/Approach/Methodology: Substantiation of the principles of building a system for accounting and analytical information management that meets current conditions for the business functioning using modern hardware and software. Findings: The developed model of cascade functioning of organization’s information support system optimizes the structure and content of accounting and analytical modules, contributes to the effective implementation of management functions, timely control and rapid response to the impact of negative factors. Practical implications: The principles of information flow management system constructing formulated in the article contribute to optimization of expenses for organization of accounting and analytical functions, improvement of quality of financial and non-financial reporting, realistic assessment and forecasting of business efficiency. Originality/Value: The proposed new model for constructing an accounting and analytical information base allows to improve the procedures of collection, processing, storage and disclosure of financial and non-financial information, to create a balanced structure of the database on the basis of cascade digitization of primary and derived data.peer-reviewe

Exploring the Potential of Developmental Work Research and Change Laboratory to Support Sustainability Transformations:A Case Study of Organic Agriculture in Zimbabwe

This paper explores the emergence of transgressive learning in CHAT-informed development work research in a networked organic agriculture case study in Zimbabwe, based on intervention research involving district organic associations tackling interconnected issues of climate change, water, food security and solidarity. The study established that We change laboratories can be used to support transgressive learning through: confronting unproductive local norms; collective reframing of problematic issues; stimulating expansive learning and sustainability transformations in minds, relationships and landscapes across time. The study also confirms the need for fourth generation CHAT to address the complex social-ecological problems of today

Knowledge Management for Public Administrations: Technical Realizations of an Enterprise Attention Management System

The improvement of governments’ efficiency has gained great importance and validity especially in the current times of economic downturn. E-Government constitutes the most contemporary techno-managerial proposition in the track of possible interventions. The paper addresses, more specifically, empowerments necessitated by Public Administration (PA) organizations. Anchored on the needs of three real-life cases, the paper describes the conception and the realization of an IT artefact together with its methodological appeals aiming at improving information access and delivery and thus PAs’ decision making capacity. Our proposition constitutes a novel approach for managing users’ attention in knowledge intensive organizations which goes beyond informing a user about changes in relevant information towards proactively supporting the user to react on changes. The approach is based on an expressive attention model, which is realized by combining ECA (Event-Condition-Action) rules with ontologies. The technical realizations described in the paper constitute the underlying infrastructure of an Enterprise Attention Management System