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Measuring risk aversion is sensitive to assumptions about the wealth in subjects’ utility functions. Data from the same subjects in low- and high-stake lottery decisions allow estimating the wealth in a pre-specified one-parameter utility function simultaneously with risk aversion. This paper first shows how wealth estimates can be identified assuming constant relative risk aversion (CRRA). Using the data from a recent experiment by Holt and Laury (2002a), it is shown that most subjects’ behavior is consistent with CRRA at some wealth level. However, for realistic wealth levels most subjects’ behavior implies a decreasing relative risk aversion. An alternative explanation is that subjects do not fully integrate their wealth with income from the experiment. Within-subject data do not allow discriminating between the two hypotheses. Using between-subject data, maximum-likelihood estimates of a hybrid utility function indicate that aggregate behavior can be described by expected utility from income rather than expected utility from final wealth and partial relative risk aversion is increasing in the scale of payoffs.

In response to food supply constraints resulting from coronavirus disease 2019 (COVID-19) restrictions, in the year 2020, the project developed automated household Aquaponics units to guarantee food self-sufficiency. However, the automated aquaponics solution did not fully comply with data privacy and portability best practices to protect the data of household owners. The purpose of this study is to develop a data privacy and portability layer on top of the previously developed automated Aquaponics units.

Design Science Research (DSR) is the research method implemented in this study.

General Data Protection and Privacy Regulations (GDPR)-inspired principles empowering data subjects including data minimisation, purpose limitation, storage limitation as well as integrity and confidentiality can be implemented in a federated learning (FL) architecture using Pinecone Matrix home servers and edge devices.

The literature reviewed for this study demonstrates that the GDPR right to data portability can have a positive impact on data protection by giving individuals more control over their own data. This is achieved by allowing data subjects to obtain their personal information from a data controller in a format that makes it simple to reuse it in another context and to transmit this information freely to any other data controller of their choice. Data portability is not strictly governed or enforced by data protection laws in the developing world, such as Zimbabwe's Data Protection Act of 2021.

Privacy requirements can be implemented in end-point technology such as smartphones, microcontrollers and single board computer clusters enabling data subjects to be incentivised whilst unlocking the value of their own data in the process fostering competition among data controllers and processors.

The use of end-to-end encryption with Matrix Pinecone on edge endpoints and fog servers, as well as the practical implementation of data portability, are currently not adequately covered in the literature. The study acts as a springboard for a future conversation on the topic.

This study investigates differences and commonalities in data production, sharing and reuse across the widest range of disciplines yet and identifies types of improvements needed to promote data sharing and reuse.

The first authors of randomly selected publications from 2018 to 2019 in 20 Scopus disciplines were surveyed for their beliefs and experiences about data sharing and reuse.

From the 3,257 survey responses, data sharing and reuse are still increasing but not ubiquitous in any subject area and are more common among experienced researchers. Researchers with previous data reuse experience were more likely to share data than others. Types of data produced and systematic online data sharing varied substantially between subject areas. Although the use of institutional and journal-supported repositories for sharing data is increasing, personal websites are still frequently used. Combining multiple existing datasets to answer new research questions was the most common use. Proper documentation, openness and information on the usability of data continue to be important when searching for existing datasets. However, researchers in most disciplines struggled to find datasets to reuse. Researchers' feedback suggested 23 recommendations to promote data sharing and reuse, including improved data access and usability, formal data citations, new search features and cultural and policy-related disciplinary changes to increase awareness and acceptance.

This study is the first to explore data sharing and reuse practices across the full range of academic discipline types. It expands and updates previous data sharing surveys and suggests new areas of improvement in terms of policy, guidance and training programs.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2021-0423.

This paper aims to discuss the challenges encountered in collecting, cleaning and analyzing the large data set of bibliographic metadata records in machine-readable cataloging [MARC 21] format. Possible solutions are presented.

This mixed method study relied on content analysis and social network analysis. The study examined subject representation in MARC 21 metadata records created in 2020 in WorldCat – the largest international database of “big smart data.” The methodological challenges that were encountered and solutions are examined.

In this general review paper with a focus on methodological issues, the discussion of challenges is followed by a discussion of solutions developed and tested as part of this study. Data collection, processing, analysis and visualization are addressed separately. Lessons learned and conclusions related to challenges and solutions for the design of a large-scale study evaluating MARC 21 bibliographic metadata from WorldCat are given. Overall recommendations for the design and implementation of future research are suggested.

There are no previous publications that address the challenges and solutions of data collection and analysis of WorldCat’s “big smart data” in the form of MARC 21 data. This is the first study to use a large data set to systematically examine MARC 21 library metadata records created after the most recent addition of new fields and subfields to MARC 21 Bibliographic Format standard in 2019 based on resource description and access rules. It is also the first to focus its analyzes on the networks formed by subject terms shared by MARC 21 bibliographic records in a data set extracted from a heterogeneous centralized database WorldCat.

This paper aims to identify the controls provisioned in ISO/IEC 27001:2013 and ISO/IEC 27002:2013 that need to be extended to adequately meet, data protection requirements set by the General Data Protection Regulation (GDPR); it also indicates security management actions an organisation needs to perform to fulfil GDPR requirements. Thus, ISO/IEC 27001:2013 compliant organisations, can use this paper as a basis for extending the already existing security control modules towards data protection; and as guidance for reaching compliance with the regulation.

This study has followed a two-step approach; first, synergies between ISO/IEC 27001:2013 modules and GDPR requirements were identified, by analysing all 14 control modules of the ISO/IEC 27001:2013 and proposing the appropriate actions towards the satisfaction of data protection requirements. Second, this paper identified GDPR requirements not addressed by ISO/IEC 27001:2013.

The findings of this work include the identification of the common ground between the security controls that ISO/IEC 27001:2013 includes and the requirements that the GDPR imposes; the actions that need to be performed based on these security controls to adequately meet the data protection requirements that the GDPR imposes; and the identification of the remaining actions an ISO/IEC 27001 compliant organisation needs to perform to be able to adhere with the GDPR.

This paper provides a gap analysis and a further steps identification regarding the additional actions that need to be performed to allow an ISO/IEC 27001:2013 certified organisation to be compliant with the GDPR.

The purpose of this paper is to study the difference of subject service between Chinese and German libraries. Subject service is the key direction of user-oriented service in libraries at home and abroad, especially in university libraries. It is an innovative measure to provide service for teaching, learning and research in libraries under the information environment. Subject service has strong practicality, and with the increasing demand of users and the continuous change of external information environment, the service content and mode are gradually improved.

By investigating the selected websites of University Libraries between China and Germany, the specific practice status of subject services between these two countries was known, and the study provided a basis for the comparative analysis of the practice status of subject services between China and Germany. By using the elastic analysis model, the library services in foreign countries and China can be quantitatively analyzed to find out the matching situation between resources and reader’s needs, and then formulate the countermeasures for the allocation of literature resources. In this way, readers can find out the hotspot topics which are more in line with their needs, as well as in the field of inquiry. It is also helpful for readers to further study and analyze the knowledge background and subject distribution in this field.

The results show that there are still some deficiencies in China’s participation in international scientific research cooperation. By mapping high-frequency keyword co-occurrence network and clustering knowledge map, it is seen that there are differences in user research, information search, subject service platform and other aspects between Chinese and German library subject services. There are also some gaps in such aspects as location, disciplines service website revealing mode, resources support, disciplines service platform and so on.

Although this study compares the status of scientific research and practice of discipline services between China and Germany, due to the limited capacity, the paper only selects a number of key points for comparative analysis of discipline services at home and abroad. Due to the limited range of data collected by WOS and Chinese Social Sciences Index, there are some deviations in data processing in the software used, which makes the theoretical research and comparison results have certain limitations.

By investigating and analyzing the current situation of subject service in university libraries between China and Germany, this paper points out the shortcomings of subject service in university libraries in China on the basis of comparative analysis and draws on the advanced experience of German subject service to provide guidance for improving the problems in subject service in China.

The innovation of this study lies in the comparative analysis of Chinese and German subject services from the perspective of subject service research and work practice and puts forward some strategies to improve the development of domestic subject services. At present, there are few domestic literatures comparing the research status of subject services between China and Germany by using visualization method. This study quantitatively compares the time distribution, knowledge evolution direction, research hotspots and topics of subject services at home and abroad by using visualization technology and summarizes the evolution direction of subject services between China and Germany.

This paper presents a systematic XML Schema design approach which conceptually captures semantics of the problem domain at conceptual level and represents such semantics in XML Schema at schema level. At the conceptual level, objects, their inter‐relationships and constraints are semantically powered by object‐oriented models. At the schema level, these conceptual semantics are comprehensively represented in textbased representation of XML Schema using various schema components and design styles, each of which offers different quality characteristics. Two primary design styles in use are nesting and linking. The nesting design styles are developed based on the choice of schema components and their definition/declaration scopes (global vs. local), whereas the linking design styles use referencing facilities provided by XML Schema and other XML technologies such as XLink and XPointer. With an in‐depth analysis of outstanding problems of existing approaches, the proposed design approach is motivated to help improve the quality and robustness of the XML documents in large‐scale XML‐based applications.

The Unified Modeling Language has become an alternative to traditional modeling languages such as data flow diagrams for use in systems analysis. A modeling language is used to represent an information system so that analysts can use the model to make decisions about the design of the system and to communicate with stakeholders about the system. This study examines the comparative effectiveness of the UML and traditional modeling languages in communicating information about a system design. The study examines this on three types of individuals: individuals with no knowledge of either modeling language, individuals with no knowledge of either language that were provided training in one of the languages, and individuals that have had more extensive training in one of the languages. The study finds that there is no difference in the ability to communicate system design information between the languages for the first two types of individuals. However, the study finds that, for more extensively trained individuals, systems modeled with the UML are better able to communicate information about the data in the system while systems modeled with traditional languages are better able to communicate information about the process used by the system.

Drowsiness is a common cause of severe road accidents. Therefore, numerous drowsiness detection methods were developed and explored in recent years, especially concepts using physiological measurements achieved promising results. Nevertheless, existing systems have some limitations that hinder their use in vehicles. To overcome these limitations, this paper aims to investigate the development of a low-cost, non-invasive drowsiness detection system, using physiological signals obtained from conventional wearable devices.

Two simulator studies, the first study in a low-level driving simulator (N = 10) to check feasibility and efficiency, and the second study in a high-fidelity driving simulator (N = 30) including two age groups, were conducted. An algorithm was developed to extract features from the heart rate signals and a data set was created by labelling these features according to the identified driver state in the simulator study. Using this data set, binary classifiers were trained and tested using various machine learning algorithms.

The trained classifiers reached a classification accuracy of 99.9%, which is similar to the results obtained by the studies which used intrusive electrodes to detect ECG. The results revealed that heart rate patterns are sensitive to the drivers’ age, i.e. models trained with data from one age group are not efficient in detecting drowsiness for another age group, suggesting to develop universal driver models with data from different age groups combined with individual driver models.

This work investigated the feasibility of driver drowsiness detection by solely using physiological data from wrist-worn wearable devices, such as smartwatches or fitness trackers that are readily available in the consumer market. It was found that such devices are reliable in drowsiness detection.

Applied Behavior Analysis (ABA) is a scientific method for modelling human behavior, successfully applied in the context of Autism. Recording and sharing measurable data (on subjects’ performance) between caregivers guarantees consistency of learning programs and allows monitoring the learning enhancements. Data are usually recorded on paper, which requires considerable effort and is subject to error. The purpose of this paper is to describe a portable application developed to support ABA tutors in their work with autistic subjects. It allows gathering data from ABA sessions, giving tutors rapid access to information, also in graphical formats.

The tool was designed via participatory design. Various ABA team members were involved, in order to make the application respond perfectly to their needs. The approach aims to ensure maximum usability, while minimizing errors and ambient interference.

The use of mobile devices (i.e. tablets or smartphones) allows mobility and ease of interaction, enabling efficient data collection and processing. Data plotting allows one to easily interpret gathered data.

The proposed application, free open source software, can be a valuable aid for supporting the ABA intervention and favor the inclusion of children with autism.

Available software to assist tutors during therapy sessions is often proprietary, and research prototypes are not freely available, so paper forms are still widespread. Besides, without attention to usability requirements, assisting tools would be comparable in efficiency with data insertion on paper. Our software was specifically designed following ABA principles and favors efficient data entry allowing natural interaction with touch screen interfaces: drag and drop, taps and gestures. Furthermore, it is shared in the public domain.