Earticle

Moving learning analytics from the research labs to the classrooms, lecture halls, and digital learning spaces requires data sharing. Routine production and consumption of data is no limited to controlled settings as data can be sourced from an increasing diversity of data points and combined or aggregated from these sources within and often beyond the institution. This scaling up of learning analytics raises a host of questions on behalf of the data subjects and therefore informs requirements for design of new solutions and practices. This paper analyses a corpus of more than 250 questions gathered by a European project that organized international workshops and facilitated community exchange. It explores how these questions could inform both the problem space of data sharing and the solution space yet to be fully scoped by research and development within this emerging field. The analysis shows that the discourse on data sharing and big data for education is still at an early stage. Conceptual issues dominate this discourse; however, the elicited questions also hold numerous challenges for technical development and implementation. In concluding we propose a short inventory of what the emerging solution space may entail and suggest a path for further work.

Recently, data-based administration is being activated to strengthen the ability to predict and respond to disasters. Accordingly, the importance of efficient decision-making using disaster safety information and data and preparation of prediction and response plans is emerging. Therefore, this study analyzed the current state of the disaster safety management information system for practical collection and sharing of distributed disaster safety data and information and application of a user-centered sharing platform. Problems were derived and the development direction of the disaster safety data sharing platform currently under construction was proposed. As a result of the analysis, many of the problems in the disaster safety knowledge information sharing system that have been continuously pointed out in the past have not been improved. Problems of the disaster safety knowledge sharing platform include the lack of data provider institutions, limited disaster type classification, lack of real-time disaster situation information, lack of visualization and analysis functions, and lack of network communities among users. As an improvement plan, a data connection plan and a plan to provide information for each stage of disaster management were presented. In addition, diversification of data format and strengthening of networking among users were suggested.

인공지능과 빅데이터의 기술혁신에도 인공지능과 빅데이터가 시장경쟁 영향에 대한 이론연구들은 아직 초기이 다. 따라서 본 논문은 인공지능, 빅데이터, 데이터 공유가 신규 진입기업에 미치는 영향을 게임이론을 활용하여 분석하 였다. 먼저 기업의 경영환경을 내부와 외부로 구분하였다. 이후 인공지능 알고리즘을 (1) 고객마케팅, (2) 비용 절감, (3) 비용 절감을 위한 자동화 알고리즘으로 구분하였다. 또한 빅데이터를 외부 및 내부 데이터로 구분하였다. 분석 결과 외부 데이터의 공유는 기존 기업의 고객마케팅 알고리즘에는 영향이 없고 신규 기업의 진입장벽을 완화했다. 하지만 기존 기업의 비용 절감 알고리즘들과 내부 빅데이터의 개선은 신규기업의 시장진입 장벽이 될 수 있다. 이러한 시사점들 은 (1) 인공지능, 빅데이터, 데이터 공유에 따른 시장구조, 경쟁, 기업행태 영향분석과 (2) 인공지능과 빅데이터 정책 수립 시 이바지할 수 있다.

Despite the innovation of AI and Big Data, theoretical research bout the effect of AI and Big Data on market competition is still in early stages; therefore, this paper analyzes the effect of AI, Big Data, and data sharing on an entry firm by using game theory. In detail, the firms' business environments are divided into internal and external ones. Then, AI algorithms are divided into algorithms for (1) customer marketing, (2) cost reduction without automation, and (3) cost reduction with automation. Big Data is also divided into external and internal data. this study shows that the sharing of external data does not affect the incumbent firm's algorithms for consumer marketing while lessening the entry firm's entry barrier. Improving the incumbent firm's algorithms for cost reduction (with and without automation) and external data can be an entry barrier for the entry firm. These findings can be helpful (1) to analyze the effect of AI, Big Data, and data sharing on market structure, market competition, and firm behaviors and (2) to design policy for AI and Big Data.

The present study specifies the historical development of data sharing practices in three disciplines?oceanography, ecology, and genomics?along with the evolving progress of movements?e-Science, cyberinfrastructure, and open science?that expedite data sharing in more diverse disciplines. The review of these disciplinary data-sharing practices and the movements suggests opportunities and challenges that would serve as a basis for implementing data-sharing practices. The increasing need for large-scale and interdisciplinary research provides momentum for initiating data sharing. In addition, the development of data repositories and standards for metadata and data format facilitates data sharing. However, challenges need to be addressed, in regard to conflicting issues of patenting data, concerns about privacy and confidentiality, and informed consent that adequately enables data sharing. It is also necessary to consider the needs of the various stakeholders involved in data sharing to incentivize them to improve its impact.

Purpose: This study aimed to ascertain the attitudes of Korean scholarly journal editors and publishers toward research data sharing policies and the publication of data papers through a survey. Methods: Between May 16 and June 16, 2023, a SurveyMonkey survey link was distributed to 388 societies, including 270 member societies of the Korean Council of Science Editors and118 societies that used an e-submission system operated by the Korea Institute of Science andTechnology Information. A total of 78 societies (20.1%) responded, from which 72 responses (18.6%) were analyzed after excluding invalid responses. Results: Out of the representatives of 72 journals, 20 editors or publishers (27.8%) declared adata sharing policy. Those journals that did not have such a policy often expressed uncertainty about their future plans regarding this issue. A common concern was a potential decrease in manuscript submissions, primarily due to the increased workload this policy might impose oneditors and manuscript editors. Four respondents (5.6%) had published data papers, with twoof them including this as a publication type in their author guidelines. Concerns about copyright and data licensing were cited as drawbacks to publishing data papers. However, the expansion of publication types and the promotion of data reuse were viewed as benefits. Conclusion: Korean scholarly journal editors’ and publishers’ attitudes toward data sharing policy and publishing data papers are not yet favorable. More training courses are needed to raise awareness of data sharing platforms and emphasize the need for research data sharing and data papers.

Purpose: This study explored to what extent and how researchers in five Korean government research institutes that implement research data management practices share their research data and investigated the challenges they perceive regarding data sharing. Methods: The study collected survey data from 224 respondents by posting a link to a SurveyMonkey questionnaire on the homepage of each of the five research institutes from June 15 to 29, 2022. Descriptive statistical analyses were conducted. Results: Among 148 respondents with data sharing experience, the majority had shared some or most of their data. Restricted data sharing within a project was more common than sharing data with outside researchers on request or making data publicly available. Sharing data directly with researchers who asked was the most common method of data sharing, while sharing data via institutional repositories was the second most common method. The most frequently cited factors impeding data sharing included the time and effort required to organize data, concerns about copyright or ownership of data, lack of recognition and reward, and concerns about data containing sensitive information. Conclusion: Researchers need ongoing training and support on making decisions about access to data, which are nuanced rather than binary. Research institutes’ commitment to developing and maintaining institutional data repositories is also important to facilitate data sharing. To address barriers to data sharing, it is necessary to implement research data management services that help reduce effort and mitigate concerns about legal issues. Possible incentives for researchers who share data should also continue to be explored.

Purpose: The present study analyzed the current status of the data sharing policies of journals published in Brazil, France, and Korea that were listed in the 2018 Scimago Journal and Country Ranking and Web of Science Core Collection. Methods: Web of Science journals were selected from the 2018 Scimago Journal and Country Ranking. The homepages of all target journals were searched for the presence of statements on data sharing policies, including clinical trial data sharing policies, the level of the policies, and actual statements of data availability in articles. Results: Out of 565 journals from these three countries, 118 (20.9%) had an optional data sharing policy, and one had a mandatory data sharing policy. Harvard Dataverse was the repository of one journal. The number of journals that had adopted a data sharing policy was 11 (6.7%) for Brazil, 64 (27.6%) for France, and 44 (25.9%) for Korea. One journal from Brazil and 20 journals from Korea had adopted clinical trial data sharing policies in accordance with the International Committee of Medical Journal Editors. Statements of data sharing were found in articles from two journals. Conclusion: Journals from France and Korea adopted data sharing policies more actively than those from Brazil. However, the actual implementation of these policies through descriptions of data availability in articles remains rare. In many journals that appear to have data sharing policies, those policies may just reflect a standard description by the publisher, especially in France. Actual data sharing was not found to be frequent.

Purpose This study analyzed the present status of data sharing polices and attitudes towards such policies through a web-based survey of editors of scholarly journals published in Korea. Methods From December 26, 2018 to January 3, 2019, a survey was distributed to 1,055 persons listed in the member directories of both the Korean Council of Science Editors and the Korean Federation of Science & Technology Societies. The survey contained four items on subjects’ information, three items that gathered information about the journals, and two further items on reasons for adopting or not adopting a data sharing policy and further opinions about such policies. Results Of the 100 respondents (from 100 journals), 13 stated that their journals had already adopted a data sharing policy. The strength of the policy was recommendation-only in 10 of those 13 journals. The most frequent reason for adopting a data sharing policy was to follow international trends. The repository sites were the Harvard Dataverse for two journals and Mendeley Data for one. The most common reasons for not adopting a data sharing policy were a lack of knowledge on data sharing, the possibility that submitters would not want to share their data, and the questionable effect of data sharing on scientific development. Conclusion Data sharing policies were uncommon among Korean scholarly journals. The advantages and disadvantages of adopting such policies should be discussed more actively among editors and researchers. Furthermore, data sharing infrastructure and training courses are required for data sharing policies to be established in scholarly journals in Korea. Keywords: Data availability; Journal editor; Knowledge; Republic of Korea

Cloud storage is provided as a service in order to keep pace with the increasing use of digital information. It can be used to store data via networks and various devices and is easy to access. Unlike existing removable storage, many users can use cloud storage because it has no storage capacity limit and does not require a storage medium. Cloud storage reliability has become a topic of importance, as many users employ it for saving great volumes of data. For protection against unethical administrators and attackers, a variety of cryptography systems, such as searchable encryption and proxy re-encryption, are being applied to cloud storage systems. However, the existing searchable encryption technology is inconvenient to use in a cloud storage environment where users upload their data. This is because this data is shared with others, as necessary, and the users with whom the data is shared change frequently. In this paper, we propose a searchable re-encryption scheme in which a user can safely share data with others by generating a searchable encryption index and then re-encrypt it.

Purpose: This study investigated the current status and factors associated with adopting data sharing policies in Asian journals. Data sharing policies vary by country and region, and few studies have examined the trends and factors related to these policies in journals across the Asian region.Methods: The 2020 Scimago Journal and Country Rank was used to download data about 1,143 Asian journals indexed in Web of Science. Excluding 40 journals inaccessible via the Internet or without English-language websites and author guidelines, 1,103 journals were analyzed through descriptive statistical analyses and the chi-square test.Results: Of the 1,103 journals, 325 (29.5%) had data sharing policies, showing a moderate level of policy adoption among Asian journals. The results of the chi-square test suggested that the impact factor and publisher type (whether a publisher was commercial) were significantly associated with the presence of data sharing policies in journals, but subject categories were not identified as a significant factor. Regarding the strength of data sharing policies, most journals provided policies that only encouraged data sharing.Conclusion: Policies only encouraging data sharing are unlikely to lead to actual data sharing; thus, considering varying levels of policy strength and effective ways to induce authors’ compliance with the policies is important. Further research needs to examine other factors affecting the presence or strength of data sharing policies.

Thanks to the roll-out of smart meters, availability of fine-grained electricity usage data has rapidly grown. Such data has enabled utility companies to perform robust and efficient grid operations. However, at the same time, privacy concerns associated with sharing and disclosure of such data have been raised. In this paper, we first demonstrate the feasibility of estimating privacy-sensitive household attributes based solely on the energy usage data of residential customers. We then discuss a framework to measure privacy gain and evaluate the effectiveness of customer-centric privacy-protection schemes, namely redaction of data irrelevant to services and addition of bounded artificial noise.

To identify health risks in working environments, it is crucial for companies to share personal health data demonstrating to clients and suppliers their employees are healthy, while being compliant with data protection legislation. Based on these considerations, our Blockchain-based BlockHealth solution allows personal health data sharing with tamper proofing and data protection. Traditionally, the Blockchain guarantees data immutability but not confidentiality. On the contrary, BlockHealth stores in the Blockchain only hash values of data. Health data is stored in private databases managed by companies, thus also allowing to delete data in compliance with the right to be forgotten.

Research data means data used or created in the course of research or experiments. Research data is very important for validation of research conducted and for use in future research and projects. Recently, convergence research between various fields and international cooperation has been continuously done due to the explosive increase of research data and the increase in the complexity of science and technology. Developed countries are actively promoting open science policies that share research results and processes to create new knowledge and values through convergence research. Communities to promote the sharing and utilization of research data such as RDA (Research Data Alliance) and COAR (Confederation of Open Access Repositories) are active, and various platforms for managing and sharing research data are being developed and used. OpenAIRE (Open Access Infrastructure for Research In Europe), a research data platform in Europe, ARDC (Australian Research Data Commons) in Australia, and IRDB (Institutional Repositories DataBase) in Japan provide research data or research data related services. Korea has been establishing and implementing a research data sharing and utilization strategy to promote the sharing and utilization of research data at the national level, led by the central government. Based on this strategy, KISTI has been building a Korean research data platform (DataON) since 2018, and has been providing research data sharing and utilization services to users since January 2020. This paper reviews the characteristics of DataON and how it is used for research by showing its applications.

Purpose: The aim of this study was to examine the relationships among parenting role sharing, parenting stress, happiness, and parenting behavior of mothers with 6-year-old children. Methods: This study used data from the seventh Panel Study of Korean Children, which began collecting longitudinal data on a sample of newborn households nationwide in 2008 and will continue yearly until 2027. The participants were 1,560 mothers of children aged 6 years. We conducted statistical analyses using descriptive statistics, the t-test, analysis of variance, Pearson correlation coefficients, and stepwise multiple regression. Results: The mean age of the mothers was 36.8±3.7 years. The mothers' perceived parenting role sharing (r=.07, p=.007), parenting stress (r=-.54, p<.001), and happiness (r=.38, p<.001) were significantly correlated with warm parenting behavior. Stepwise multiple regression analysis revealed that parenting stress (β=-.47, p<.001), happiness (β=.15, p<.001), and parenting role sharing (β=.11, p<.001) were significant predictors for warm parenting behavior by mothers. Conclusion: It is essential to reduce mothers' stress and increase their positive emotions (happiness). Fathers should actively share parenting roles in raising children to enhance mothers' warm parenting behavior.

This paper proposes a practical, privacypreserving healthcare data-sharing architecture that integrates a local CDM(Common Data Model) with a FHIR (Fast Healthcare Interoperability Resources)–based self-serve interface under a federated data-mesh governance model. Each organization operates autonomously as a domain team and maintains its own data lake. In the upload flow, source data are standardized into a local CDM and passed through a De-ID gate for pseudonymization, date shifting, generalization, and freetext PII redaction before being stored in a Processed-DeID zone. In the download flow, only cataloged and validated data products are exposed as FHIR resources, where context- and authorization-aware dynamic masking is applied, with support for Bulk Export and incremental queries. Federated computational governance enforces standards, security, and change management as policy-as-code, ensuring consistent compliance at deploy time and runtime. Internally, CDM ensures data quality and consistency; across organizations, FHIR simplifies data contracts and standardizes discovery, authorization, and use. The architecture enables safe exchange and reuse even among institutions with different CDMs, while improving lineage visibility, accountability, operational scalability, and change predictability. This two-layer model can serve as a reference architecture for accelerating data flows across clinical, research, and industry collaborations.

Data plays an ever greater part in the tourism industry. While the platform-based sharing of open public data, private-sector intermediary platforms, and the use of social media to understand consumer trends are already well recognized, more potential for innovation exists in sharing private data among organizations in Smart Tourism Destinations. Research into the factors enabling and hindering coopetition in this kind of data sharing platforms is still in the nascent stage of development. Our case study of Sapporo, a major Japanese city endeavouring to create itself as a Smart Tourism Destination, sheds light on the initial approaches to involve organizations to such a data sharing agreement. Founding on seven interviews with ten participants of Sapporo Smart City project organization (SARD), we derived enablers and impediments that promote coopetition in data sharing as part of Smart Tourism Destination development. We also present practical recommendations and future research opportunities for such initiatives.

건강의료데이터의 사용과 공유는 디지털경제 발전을 추진함에 있어 현실적으로 반드시 필요하다. 또 중국의 건강의료 발전 전략목표를 실현하는데 있어서도 핵심적 사항이기도 하다. 그러나 중국의 건강의료데이터 공유와 사용은 여전히 데이터 권한의 분배에 대한 불명확성, 개인의 프라이버시 유출, 개인정보의 남용, 협력 메 커니즘의 미흡 등 여러 문제에 직면해 있다. 이와 같이 빅데이터 시대의 건강의료 데이터 공유와 사용의 현실적 문제를 해결하기 위해, 건강의료데이터의 권한 분배 를 명확히 할 필요가 있다. 건강의료데이터는 환자, 의료기관, 일반대중이라는 이 해관계자를 포함한다. 또, ‘환자-의료기관-공중보건 관리기관’ 간의 건강의료데이 터에 대한 권한을 적절히 조정하여야 한다. 건강의료데이터의 효과적인 사용면에 서 볼 때, 환자의 건강의료데이터 권한은 개인의 권리(인격권 등)의 연장선에 놓여 있을 뿐, 이를 자원으로 활용한다는 의미에서 사용 권한을 포함하지 않는다. 건강 의료데이터의 자원 활용에 있어 사용 권한은 실제로 건강의료데이터를 소유하거 나 통제하는 의료기관에 있다. 한편, 공공이익을 위해 서비스하는 공중보건관리기 관에게는 공공이익의 필요를 충족시키기에 필요한 권한만 부여된다. 한편, 건강의료데이터의 공유와 프라이버시권 침해에 대한 문제를 해결하여야 한다. 이는 환자의 개인정보에 대한 자기결정권 행사를 개선하고, 의료건강데이 터의 유형과 그 민감정도에 따라 등급을 나눔으로써 가능할 것이다. 또한, 건강 의료데이터에 대한 관리감독을 강화할 필요가 있다. 건강의료데이터를 전문적으 로 관리감독하는 기관을 두어 환자의 프라이버시 보호는 물론, 데이터 안전을 보장할 수 있도록 하여야 한다. 그리고 의료건강데이터의 협력 메커니즘을 강화 하고, 의료건강데이터 자원에 대한 목록을 작성하여 통용되는 표준을 마련할 필 요가 있다. 이는 의료건강데이터에 대한 기술적･제도적 차원에서 안전성을 확보 할 수 있을 것이다.

Promoting the circulation and sharing of health care data is not only a practical necessity for the advancement of the digital economy, but also a key to achieving the strategic goals of China's health care development. However, the sharing and utilization of China's health care data still face a series of challenges, including unclear allocation of rights and interests of data, breaches of personal privacy, misuse of personal information, and an underdeveloped collaborative mechanism. To overcome these barriers in the era of big data, firstly it is necessary to clarify the rights and interests’ allocation of health care data. Health care data involves three categories of stakeholders: patients, medical institutions, and the public. It is essential to appropriately allocate the rights and interests to health care data among patients, medical institutions, and public health management agencies. From the perspective of effectively utilizing health care data, the rights and interests of patients to their personal health care data are merely an extension of their individual rights and do not include the right to use the data in terms of resource utilization. The rights and interests to use health care data for resource utilization should be granted to medical institutions that actually own or control the health care data. For public health management agencies serving the public interest, only necessary rights and interests should be granted when meeting the needs of the public interest. Secondly, it is necessary to balance the inherent contradiction between sharing and privacy. This requires improving the means by which patients can exercise control over their personal information, establishing a tiered protection mechanism based on the type and sensitivity of health care data, and enhancing the enforcement of health care data regulations to ensure the protection of personal privacy and data security. Ensuring efficient sharing of health data, while respecting individual privacy. Lastly, strengthening the collaborative mechanism for health care data, accelerating the compilation of a health care data resource catalog, and developing universal standards for health care data. From both technical and institutional perspectives, this lays the foundation for the orderly and secure sharing of health care data.

促进健康医疗数据的流通、共享，既是推动数字经济发展的现实需要，也是实现 中国健康医疗发展战略目标的关键。然而，中国健康医疗数据共享利用仍然面临数 据权益配置不明、个人隐私泄露、个人信息被滥用、协作机制不健全等一系列问 题。为了破解大数据时代健康医疗数据共享利用的现实壁垒，首先是要明晰健康医 疗数据的权益配置。健康医疗数据涉及患者个人、医疗机构、社会公众三类利益主 体，需要妥当配置患者个人、医疗机构和公共卫生管理机构对健康医疗数据的权 益。从有效利用健康医疗数据的角度来看，患者对其个人健康医疗数据的权益只是 个人权利的延伸，并不包括健康医疗数据资源化利用意义上的使用权。健康医疗数 据资源化利用的使用权，应该赋予实际上拥有或控制健康医疗数据的医疗机构。而 对服务于公共利益的公共卫生管理机构而言，只应赋予其必要的权益以满足公共利 益的需要。其次，还需平衡共享与隐私的内在矛盾，需完善患者个人信息自决的行 使途径，健全基于医疗健康数据类型及其敏感性的分级保护机制，并且通过加强健 康医疗数据的执法进一步让个人隐私、数据安全得到保证。确保医疗健康数据高效 共享的同时，又让个人隐私得到应有的尊重。最后，强化医疗健康数据的协作机 制，加快编制医疗健康数据资源目录，制定医疗健康数据通用标准。从技术、制度 层面，进一步奠定医疗健康数据有序、安全共享的基础。

The sharing economy has significantly changed the way of living for years. The emergence and expansion of sharing economy empowered by the mobile information technologies and intellectual algorithms reconfigure how people use transportation means. In this paper, the bike sharing phenomenon is highlighted. Combining a big data set provided by the Seoul government about user logs and air quality data set, the empirical findings reveal that temperature change is tightly associated bike sharing activities. Also, the concentration of particulate matter is weakly related to bike sharing, but the trend should be carefully examined. By considering external environmental factors to bike sharing businesses, this work is differentiated. To further understand empirical data, data mining methods and econometric approaches were adopted.