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The purpose of this paper is to conceptualize data quality (DQ) in the context of business process management and to propose a DQ oriented approach for business process modeling. The approach is based on key concepts and metrics from the data quality management domain and supports decision‐making in process re‐design projects on the basis of process models.

The paper applies a design oriented research approach, in the course of which a modeling method is developed as a design artifact. To do so, method engineering is used as a design technique. The artifact is theoretically founded and incorporates DQ considerations into process re‐design. Furthermore, the paper uses a case study to evaluate the suggested approach.

The paper shows that the DQ oriented process modeling approach facilitates and improves managerial decision‐making in the context of process re‐design. Data quality is considered as a success factor for business processes and is conceptualized using a rule‐based approach.

The paper presents design research and a case study. More research is needed to triangulate the findings and to allow generalizability of the results.

The paper supports decision‐makers in enterprises in taking a DQ perspective in business process re‐design initiatives.

The paper reports on integrating DQ considerations into business process management in general and into process modeling in particular, in order to provide more comprehensive decision‐making support in process re‐design projects. The paper represents one of the first contributions to literature regarding a contemporary phenomenon of high practical and scientific relevance.

The purpose of this paper is to develop data quality (DQ) assessment model based on content analysis and metadata analysis.

A literature review of DQ assessment models has been conducted. A study of DQ key performances (KPIs) has been done. Finally, the proposed model has been developed and applied in a case study.

The results of this study shows that the metadata data have important information about DQ in a database and can be used to assess DQ to provide decision support for decision makers.

There is a lot of DQ assessment in the literature; however, metadata are not considered in these models. The model developed in this study is based on metadata in addition to the content analysis, to find a quantitative DQ assessment.

Aims to present a new approach for formulating state‐space equations of an electromechanical actuator using magnetic flux linkages as state variables.

The model is based on employment of discrete databases and their interpolation. The algorithm of determination of databases defining the flux/current characteristics of an actuator is described. Graphical interpretation of variable transformation is presented. A simplified, two‐axis model of reluctance motor is used to illustrate the application of the proposed modelling technique. Comparison with the classical model of the motor is used to verify the validity of the method. Analysis is focused on determination of saturation phenomenon influence on formulation methodology and on correctness of obtained results.

A very good agreement is observed between reference dq model and the proposed model. The main problem of the presented method is the existence of undefined entries in databases. Sufficiently dense databases can be used to overcome the problem.

The model is limited to actuators in which eddy currents and hysteresis phenomenon can be neglected. Future research will be concentrated on evaluation of different interpolation strategies of databases used in the model for realistic saturation conditions.

The model can be used as a library block for testing various control strategies for actuators without standard simplifying assumptions (e.g. sinusoidal winding distribution). It can be implemented in any simulational software (e.g. SIMULINK) as its block diagram is simple and no numerical differentiation is necessary in derivation of the model data.

Presents an extension of state‐space model of an actuator based on database discretised description of variables to two or more state variables.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.

The purpose of the paper is to present an analysis of an influence of shape and material of rotor bars on the process of self-excitation and performance characteristics of single-phase, self-excited induction generator (SP-SEIG).

The presented analysis is based on the results of transient simulations of SP-SEIG performed with the use of field-circuit model of the machine. Four various shapes of the rotor bars and two different conductor materials were investigated. The results for the base model with rounded trapezoidal rotor slots were validated by measurements.

An improvement of the performance characteristics – the extension of the stable operating range of the generator – was obtained for rectangular copper rotor bars. The improvement is the result of strong skin effect in the squirrel rotor cage. Application of round rotor slots results in shorter time of voltage build-up during the self-excitation of the generator caused by less apparent deep bar effect in round bars.

The originality of the paper is the application of the copper rotor cage in the single-phase, self-excited induction generator. Its use is beneficial, as it allows for extension of the range of stable operating range. The results may be used for designing new constructions of the single-phase, self-excited induction generators, as well as the constructions based on general purpose single-phase induction motors.

The purpose of this paper is to update and re‐examine the role of corporate narrative reporting in improving investors' ability to better forecast future earnings change. The paper also aims to construct a risk factor for disclosure quality (DQ) and test whether such a factor is useful in explaining the time‐series variation of UK stock returns.

The paper uses the return‐future earnings regression model to update and re‐examine the value relevance of DQ for investors. It also constructs a DQ factor and adds it to Fama‐French three‐factor model. This is undertaken in order to investigate the usefulness of such a factor in explaining the time‐series variation of UK portfolio returns over and above the role of the original Fama‐French factors.

The paper contributes to the market‐based accounting research in three crucial ways. First, it offers updated evidence on the usefulness of corporate narrative reporting to investors. Second, it offers evidence that the DQ factor is a significant risk factor in the UK. Third, and finally, it finds that the Fama‐French factors might contain DQ‐related information.

The results suggest that narrative reporting contains value‐relevant information for the stock market. Therefore, regulators should think about asking companies to produce compulsory narrative sections (i.e. operating and financial reviews) in their annual reports.

To the best of the authors' knowledge, this paper is the first to construct and add the DQ factor in the original Fama‐French factors.

The purpose of this paper is to understand genomics scientists’ perceptions in data quality assurances based on their domain knowledge.

The study used a survey method to collect responses from 149 genomics scientists grouped by domain knowledge. They ranked the top-five quality criteria based on hypothetical curation scenarios. The results were compared using χ2 test.

Scientists with domain knowledge of biology, bioinformatics, and computational science did not reach a consensus in ranking data quality criteria. Findings showed that biologists cared more about curated data that can be concise and traceable. They were also concerned about skills dealing with information overloading. Computational scientists on the other hand value making curation understandable. They paid more attention to the specific skills for data wrangling.

This study takes a new approach in comparing the data quality perceptions for scientists across different domains of knowledge. Few studies have been able to synthesize models to interpret data quality perception across domains. The findings may help develop data quality assurance policies, training seminars, and maximize the efficiency of genome data management.

This study aims to demonstrate the numerical application of differential quadrature (DQ) methods and show the experimental application of free vibration analysis of fiber-metal laminated composite (FML) plates with various boundary conditions.

The FMLs are hybrid structures consisting of fiber-reinforced polymer matrix composites such as carbon, glass, aramid and different metal sheets, and are currently widely used in the automobile, aircraft and aerospace industries. Thus, free vibration analysis of these hybrid materials is necessary for the design process. The governing equations of motion are derived based on the classical plate theory. The DQ, generalized DQ (GDQ) and harmonic DQ (HDQ) differential quadrature methods have been used to solve the governing equations of an FML composite plate numerically. The accuracy and convergence of the numerical model have been verified by comparing the results available in the published literature with the results obtained from these methods. Moreover, an experimental procedure has been performed in order to compare the results against those of the numerical methods.

It is noteworthy that a high degree of similarity and accuracy was observed between the numerical results obtained by the DQ methods and the experimental results. Thus, the present study validates the applicability of the DQ methods for designing the FML composite plates.

In this study, the advantages of the DQ methods have been demonstrated differently from previous studies on the vibration analysis of the FML plates.

The purpose of this paper is to propose a new method that allows to compare the magnetic pressures of different pulse width modulation (PWM) strategies in a fast and efficient way.

The voltage harmonics are determined using the double Fourier integral. As for current harmonics and waveforms, a new generic model based on the Park transformation and a dq model of the machine was established taking saturation into consideration. The obtained analytical waveforms are then injected into a finite element software to compute magnetic pressures using nodal forces.

The overall proposed method allows to accelerate the calculations and the comparison of different PWM strategies and operating points as an analytical model is used to generate current waveforms.

While the analytical expressions of voltage harmonics are already provided in the literature for the space vector pulse width modulation, they had to be calculated for the discontinuous pulse width modulation. In this paper, the obtained expressions are provided. For current harmonics, different models based on a linear and a nonlinear model of the machine are presented in the referenced papers; however, these models are not generic and are limited to the second range of harmonics (two times the switching frequency). A new generic model is then established and used in this paper after being validated experimentally. And finally, the direct injection of analytical current waveforms in a finite element software to perform any magnetic computation is very efficient.

The purpose of this paper is to investigate the influence of end‐effect and cross‐coupling on the torque‐speed characteristics of switched flux permanent magnet (SFPM) machines.

The torque‐speed characteristics are predicted using two different methods. These are direct and indirect finite element methods, at different cross‐coupling levels, namely, full cross‐coupling on both PM flux linkage and dq‐axis inductances, partial cross‐coupling on the PM flux linkage only and without cross‐coupling.

The influence of the cross‐coupling on dq‐axis inductances of the studied machine is relatively small. However, it is more significant on the PM flux linkage. Therefore, the partial cross‐coupling model, which is much easier and faster, exhibits almost the same accuracy as the full cross‐coupling model. Furthermore, the end‐effect causes a large reduction in torque‐speed characteristics. However, such a reduction is more significant in the flux weakening operation region.

This is the first time that the influence of end‐effect of SFPM machines on the torque‐speed characteristics, especially in flux weakening region, and on the dq‐axis inductances has been investigated.