Journal articles: 'Data sharing approach'

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Khusro, Ameer, and Chirom Aarti. "TB-PACTS: A fresh emphatic data sharing approach." Asian Pacific Journal of Tropical Disease 7, no. 2 (January 2017): 97–98. http://dx.doi.org/10.12980/apjtd.7.2017d6-357.

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Krumm, Andrew E., Jared Boyce, and Howard T. Everson. "A Collaborative Approach to Sharing Learner Event Data." Journal of Learning Analytics 8, no. 2 (September 3, 2021): 73–82. http://dx.doi.org/10.18608/jla.2021.7375.

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This paper describes a collaboration organized around exchanging data between two technological systems to support teachers’ instructional decision-making. The goals of the collaboration among researchers, technology developers, and practitioners were not only to support teachers’ instructional decision-making but also to document the challenges and opportunities associated with bringing together data from instruction- and assessment-focused technologies. The approach described in this paper illustrates the potential importance of anchoring data products that combine data between two systems in the needs of teachers as well as aligning the content that students learn and are assessed on between systems. The increasing presence of data standards has made sharing complex data increasingly more feasible. The example collaboration described in this paper demonstrates the role that non-technical activities can play in supporting the exchange and use of learner event data.

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Khan, Huda, Brian Caruso, Jon Corson-Rikert, Dianne Dietrich, Brian Lowe, and Gail Steinhart. "DataStaR: Using the Semantic Web approach for Data Curation." International Journal of Digital Curation 6, no. 2 (July 25, 2011): 209–21. http://dx.doi.org/10.2218/ijdc.v6i2.197.

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In disciplines as varied as medicine, social sciences, and economics, data and their analyses are essential parts of researchers’ contributions to their respective fields. While sharing research data for review and analysis presents new opportunities for furthering research, capturing these data in digital forms and providing the digital infrastructure for sharing data and metadata pose several challenges. This paper reviews the motivations behind and design of the Data Staging Repository (DataStaR) platform that targets specific portions of the research data curation lifecycle: data and metadata capture and sharing prior to publication, and publication to permanent archival repositories. The goal of DataStaR is to support both the sharing and publishing of data while at the same time enabling metadata creation without imposing additional overheads for researchers and librarians. Furthermore, DataStaR is intended to provide cross-disciplinary support by being able to integrate different domain-specific metadata schemas according to researchers’ needs. DataStaR’s strategy of a usable interface coupled with metadata flexibility allows for a more scaleable solution for data sharing, publication, and metadata reuse.

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Ma, Xinwei, Ruiming Cao, and Yuchuan Jin. "Spatiotemporal Clustering Analysis of Bicycle Sharing System with Data Mining Approach." Information 10, no. 5 (May 2, 2019): 163. http://dx.doi.org/10.3390/info10050163.

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The main objective of this study is to explore the spatiotemporal activities pattern of bicycle sharing system by combining together temporal and spatial attributes variables through clustering analysis method. Specifically, three clustering algorithms, i.e., hierarchical clustering, K-means clustering, expectation maximization clustering, are chosen to group the bicycle sharing stations. The temporal attributes variables are obtained through the statistical analysis of bicycle sharing smart card data, and the spatial attributes variables are quantified by point of interest (POI) data around bicycle sharing docking stations, which reflects the influence of land use on bicycle sharing system. According to the performance of the three clustering algorithms and six cluster validation measures, K-means clustering has been proven as the better clustering algorithm for the case of Ningbo, China. Then, the 477 bicycle sharing docking stations were clustered into seven clusters. The results show that the stations of each cluster have their own unique spatiotemporal activities pattern influenced by people’s travel habits and land use characteristics around the stations. This analysis will help bicycle sharing operators better understand the system usage and learn how to improve the service quality of the existing system.

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Giuliani, Gregory, Nicolas Ray, Stefan Schwarzer, Andrea De Bono, Pascal Peduzzi, Hy Dao, Jaap Van Woerden, Ron Witt, Martin Beniston, and Anthony Lehmann. "Sharing Environmental Data through GEOSS." International Journal of Applied Geospatial Research 2, no. 1 (January 2011): 1–17. http://dx.doi.org/10.4018/jagr.2011010101.

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Understanding the complexity of earth-system processes is crucial to convey improved information on the environment to decision-makers and the general public. Addressing this need by sharing environmental data is challenging because it requires a common agreed framework that allows easy and seamless integration of data from different sources. In this regard, the Global Earth Observation System of Systems (GEOSS) portends major benefits through various sharing mechanisms and by giving access to services that could be linked together to process and generate new understandable knowledge and information. Various United Nations projects could greatly benefit from the GEOSS approach.

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Dueker, Kenneth, J. Allison Butler, Paul Bender, and Jihong Zhang. "Clearinghouse Approach to Sharing Geographic Information Systems-Transportation Data." Transportation Research Record: Journal of the Transportation Research Board 1768, no. 1 (January 2001): 203–9. http://dx.doi.org/10.3141/1768-24.

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Krishna, Prof B. S. Vamsi, and Bingi Anu Reshma. "A Novel Approach for Sharing Encrypted Data Over Cloud." IJARCCE 6, no. 5 (May 30, 2017): 771–77. http://dx.doi.org/10.17148/ijarcce.2017.65146.

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Miller, Katherine E., and Simon M. Lin. "Addressing a patient-controlled approach for genomic data sharing." Genetics in Medicine 19, no. 11 (April 20, 2017): 1280–81. http://dx.doi.org/10.1038/gim.2017.36.

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Resende, João S., Luís Magalhães, André Brandão, Rolando Martins, and Luís Antunes. "Towards a Modular On-Premise Approach for Data Sharing." Sensors 21, no. 17 (August 28, 2021): 5805. http://dx.doi.org/10.3390/s21175805.

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The growing demand for everyday data insights drives the pursuit of more sophisticated infrastructures and artificial intelligence algorithms. When combined with the growing number of interconnected devices, this originates concerns about scalability and privacy. The main problem is that devices can detect the environment and generate large volumes of possibly identifiable data. Public cloud-based technologies have been proposed as a solution, due to their high availability and low entry costs. However, there are growing concerns regarding data privacy, especially with the introduction of the new General Data Protection Regulation, due to the inherent lack of control caused by using off-premise computational resources on which public cloud belongs. Users have no control over the data uploaded to such services as the cloud, which increases the uncontrolled distribution of information to third parties. This work aims to provide a modular approach that uses cloud-of-clouds to store persistent data and reduce upfront costs while allowing information to remain private and under users’ control. In addition to storage, this work also extends focus on usability modules that enable data sharing. Any user can securely share and analyze/compute the uploaded data using private computing without revealing private data. This private computation can be training machine learning (ML) models. To achieve this, we use a combination of state-of-the-art technologies, such as MultiParty Computation (MPC) and K-anonymization to produce a complete system with intrinsic privacy properties.

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Bender, Stefam, and Jorg Heining. "The Research-Data-Centre in Research-Data-Centre Approach: A First Step Towards Decentralised International Data Sharing." IASSIST Quarterly 35, no. 3 (January 31, 2012): 10. http://dx.doi.org/10.29173/iq119.

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Bender, Stefam, and Jorg Heining. "The Research-Data-Centre in Research-Data-Centre Approach: A First Step Towards Decentralised International Data Sharing." IASSIST Quarterly 35, no. 3 (January 31, 2012): 10. http://dx.doi.org/10.29173/iq384.

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John, Naveen, and Shatheesh Sam. "Provably Secure Data Sharing Approach for Personal Health Records in Cloud Storage Using Session Password, Data Access Key, and Circular Interpolation." International Journal on Semantic Web and Information Systems 17, no. 4 (October 2021): 76–98. http://dx.doi.org/10.4018/ijswis.2021100105.

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Personal health record (PHR) system has become the most important platform to exchange health information, in which the patients can share and manage personal health information more effectively in cloud storage. However, the cloud server is unreliable, and the secure data of users may be disclosed. Therefore, a secure data sharing mechanism is developed in this research using the proposed session password, data access key, and circular interpolation (SKC)-based data-sharing approach for the secure sharing of PHR in the cloud. The proposed SKC-based data sharing approach provides high efficiency and high-security guarantee. It effectively satisfies various security properties, such as tamper resistance, openness, and decentralization. The proposed SKC-based data sharing approach is the reliable mechanism created for the doctors to share the PHR and to access the patient historical data while meeting the privacy preservation.

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Walters, Kellie M., Anna Jojic, Emily R. Pfaff, Marie Rape, Donald C. Spencer, Nicholas J. Shaheen, Brent Lamm, and Timothy S. Carey. "Supporting research, protecting data: one institution’s approach to clinical data warehouse governance." Journal of the American Medical Informatics Association 29, no. 4 (December 6, 2021): 707–12. http://dx.doi.org/10.1093/jamia/ocab259.

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Abstract Institutions must decide how to manage the use of clinical data to support research while ensuring appropriate protections are in place. Questions about data use and sharing often go beyond what the Health Insurance Portability and Accountability Act of 1996 (HIPAA) considers. In this article, we describe our institution’s governance model and approach. Common questions we consider include (1) Is a request limited to the minimum data necessary to carry the research forward? (2) What plans are there for sharing data externally?, and (3) What impact will the proposed use of data have on patients and the institution? In 2020, 302 of the 319 requests reviewed were approved. The majority of requests were approved in less than 2 weeks, with few or no stipulations. For the remaining requests, the governance committee works with researchers to find solutions to meet their needs while also addressing our collective goal of protecting patients.

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Zenk-Möltgen, Wolfgang, and Greta Lepthien. "Data sharing in sociology journals." Online Information Review 38, no. 6 (September 9, 2014): 709–22. http://dx.doi.org/10.1108/oir-05-2014-0119.

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Purpose – Data sharing is key for replication and re-use in empirical research. Scientific journals can play a central role by establishing data policies and providing technologies. The purpose of this paper is to analyses the factors which influence data sharing by investigating journal data policies and the behaviour of authors in sociology. Design/methodology/approach – The web sites of 140 sociology journals were consulted to check their data policy. The results are compared with similar studies from political science and economics. A broad selection of articles published in five selected journals over a period of two years are examined to determine whether authors really cite and share their data and the factors which are related to this. Findings – Although only a few sociology journals have explicit data policies, most journals make reference to a common policy supplied by their association of publishers. Among the journals selected, relatively few articles provide data citations and even fewer make data available – this is true both for journals with and without a data policy. But authors writing for journals with higher impact factors and with data policies are more likely to cite data and to make it really accessible. Originality/value – No study of journal data policies has been undertaken to date for the domain of sociology. A comparison of authors’ behaviours regarding data availability, data citation, and data accessibility for journals with or without a data policy provides useful information about the factors which improve data sharing.

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Sheeba, S. Lilly, and P. Yogesh. "Enhanced cache sharing through cooperative data cache approach in MANET." International Journal of Biomedical Engineering and Technology 32, no. 4 (2020): 384. http://dx.doi.org/10.1504/ijbet.2020.107204.

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Ennajjar, Ibtissam, Youness Tabii, and Abdelhamid Benkaddour. "An enhanced approach for data sharing security in cloud computing." International Journal of Cloud Computing 5, no. 3 (2016): 198. http://dx.doi.org/10.1504/ijcc.2016.080045.

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Benkaddour, Abdelhamid, Youness Tabii, and Ibtissam Ennajjar. "An enhanced approach for data sharing security in cloud computing." International Journal of Cloud Computing 5, no. 3 (2016): 198. http://dx.doi.org/10.1504/ijcc.2016.10000906.

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Wu, Yongwei, Maomeng Su, Weiming Zheng, Kai Hwang, and Albert Y. Zomaya. "Associative Big Data Sharing in Community Clouds: The MeePo Approach." IEEE Cloud Computing 2, no. 6 (November 2015): 64–73. http://dx.doi.org/10.1109/mcc.2015.123.

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Sheeba, S. Lilly, and P. Yogesh. "Enhanced cache sharing through cooperative data cache approach in MANET." International Journal of Biomedical Engineering and Technology 32, no. 4 (2020): 384. http://dx.doi.org/10.1504/ijbet.2020.10029249.

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Cassa, Christopher A., Rachel A. Miller, and Kenneth D. Mandl. "A novel, privacy-preserving cryptographic approach for sharing sequencing data." Journal of the American Medical Informatics Association 20, no. 1 (November 2, 2012): 69–76. http://dx.doi.org/10.1136/amiajnl-2012-001366.

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Piao, Chunhui, Liping Liu, Yajuan Shi, Xuehong Jiang, and Ning Song. "Clustering-based privacy preserving anonymity approach for table data sharing." International Journal of System Assurance Engineering and Management 11, no. 4 (July 29, 2019): 768–73. http://dx.doi.org/10.1007/s13198-019-00834-5.

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Witten, Ian H., Rarold W. Thimbleby, George Coulouris, and Saul Greenberg. "Liveware: a new approach to sharing data in social networks." International Journal of Man-Machine Studies 34, no. 3 (March 1991): 337–48. http://dx.doi.org/10.1016/0020-7373(91)90024-2.

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Хомяков, И. А. "Novel Approach for software metrics Sharing." Южно-Сибирский научный вестник, no. 5(39) (October 31, 2021): 133–37. http://dx.doi.org/10.25699/sssb.2021.39.5.007.

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Сбор метрик программного обеспечения является фундаментальной деятельностью, которая необходима для проведния практически любого эмпирического исследования в области программной инженерии. Однако, даже при наличии широкого спектра инструментов, сбор таких фундаментальных данных по-прежнему занимает много времени. Более того, каждый исследователь собирает практически одни и те же данные (например, метрики CK, цикломатическая сложность МакКейба и т.д.) из практически одних и тех же проектов (например, из известных проектов с открытым исходным кодом). Объем такой дублирующей работы, выполняемой в сообществе, уменьшает усилия, которые исследователи могут потратить на наиболее ценную часть своих исследований, такую как разработка новых теорий и моделей и их эмпирическая оценка. В данной работе предлагается новый подход для сбора и обмена данными метрик программного обеспечения, позволяющий сотрудничать исследователям и сократить количество напрасных усилий в сообществе разработчиков программного обеспечения. Мы стремимся достичь этой цели, предлагая Формат обмена программными метриками (SMEF)и REST API для сбора, хранения и обмена данными метрик программного обеспечения. In almost every empirical software engineering study, software metrics collection is a fundamental activity. Although many tools exist to collect this data, it still takes a considerable amount of time. In addition, almost all researchers collect essentially the same data (e.g., CK metrics, McCabe Cyclomatic Complexity, etc.) from essentially the same sources (e.g., well-known open-source projects).Having so much duplication of work done within a community reduces the amount of time that researchers can spend developing new ideas and evaluating them empirically, which is the most valuable part of their research. In this paper, we propose a novel approach for getting and sharing software metrics data that will allow them to collaborate and reduce the amount of wasted effort. SMEF, a file format for exchanging software metrics information, and a REST API, targeted at this objective, are proposed in this paper.

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Banothu, Narsimha, P. Dayaker, and P. Bhaskara Reddy. "A Novel Approach for Efficient Data Sharing and Revocation with Data Access control." International Journal of Computer Sciences and Engineering 6, no. 11 (November 30, 2018): 764–69. http://dx.doi.org/10.26438/ijcse/v6i11.764769.

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D’Amore, F., S. Cinnirella, and N. Pirrone. "Data and metadata management automation for an effective approach to sharing environmental data." E3S Web of Conferences 1 (2013): 18003. http://dx.doi.org/10.1051/e3sconf/20130118003.

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Yoon, Ayoung, and Youngseek Kim. "The role of data-reuse experience in biological scientists’ data sharing: an empirical analysis." Electronic Library 38, no. 1 (February 5, 2020): 186–208. http://dx.doi.org/10.1108/el-06-2019-0146.

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Purpose The purpose of this paper is to investigate how scientists’ prior data-reuse experience affects their data-sharing intention by updating diverse attitudinal, control and normative beliefs about data sharing. Design/methodology/approach This paper used a survey method and the research model was evaluated by applying structural equation modelling to 476 survey responses from biological scientists in the USA. Findings The results show that prior data-reuse experience significantly increases the perceived community and career benefits and subjective norms of data sharing and significantly decreases the perceived risk and effort involved in data sharing. The perceived community benefits and subjective norms of data sharing positively influence scientists’ data-sharing intention, whereas the perceived risk and effort negatively influence scientists’ data-sharing intention. Research limitations/implications Based on the theory of planned behaviour, the research model was developed by connecting scientists’ prior data-reuse experience and data-sharing intention mediated through diverse attitudinal, control and normative perceptions of data sharing. Practical implications This research suggests that to facilitate scientists’ data-sharing behaviours, data reuse needs to be encouraged. Data sharing and reuse are interconnected, so scientists’ data sharing can be better promoted by providing them with data-reuse experience. Originality/value This is one of the initial studies examining the relationship between data-reuse experience and data-sharing behaviour, and it considered the following mediating factors: perceived community benefit, career benefit, career risk, effort and subjective norm of data sharing. This research provides an advanced investigation of data-sharing behaviour in the relationship with data-reuse experience and suggests significant implications for fostering data-sharing behaviour.

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Vlahou, Antonia, Dara Hallinan, Rolf Apweiler, Angel Argiles, Joachim Beige, Ariela Benigni, Rainer Bischoff, et al. "Data Sharing Under the General Data Protection Regulation." Hypertension 77, no. 4 (April 2021): 1029–35. http://dx.doi.org/10.1161/hypertensionaha.120.16340.

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The General Data Protection Regulation (GDPR) became binding law in the European Union Member States in 2018, as a step toward harmonizing personal data protection legislation in the European Union. The Regulation governs almost all types of personal data processing, hence, also, those pertaining to biomedical research. The purpose of this article is to highlight the main practical issues related to data and biological sample sharing that biomedical researchers face regularly, and to specify how these are addressed in the context of GDPR, after consulting with ethics/legal experts. We identify areas in which clarifications of the GDPR are needed, particularly those related to consent requirements by study participants. Amendments should target the following: (1) restricting exceptions based on national laws and increasing harmonization, (2) confirming the concept of broad consent, and (3) defining a roadmap for secondary use of data. These changes will be achieved by acknowledged learned societies in the field taking the lead in preparing a document giving guidance for the optimal interpretation of the GDPR, which will be finalized following a period of commenting by a broad multistakeholder audience. In parallel, promoting engagement and education of the public in the relevant issues (such as different consent types or residual risk for re-identification), on both local/national and international levels, is considered critical for advancement. We hope that this article will open this broad discussion involving all major stakeholders, toward optimizing the GDPR and allowing a harmonized transnational research approach.

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Garrison, Nanibaa' A., Krysta S. Barton, Kathryn M. Porter, Thyvu Mai, Wylie Burke, and Stephanie Russo Carroll. "Access and Management: Indigenous Perspectives on Genomic Data Sharing." Ethnicity & Disease 29, Supp (December 12, 2019): 659–68. http://dx.doi.org/10.18865/ed.29.s3.659.

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As genomic researchers are encouraged to engage in broad genomic data sharing, American Indian/Alaska Native/Native Hawaiian (AI/AN/NH) leaders have raised questions about ownership of data and biospecimens and concerns over emerging challenges and potential threats to tribal sovereignty. Using a community-engaged research approach, we conducted 42 semi-structured interviews with tribal leaders, clinicians, researchers, policy makers, and tribal research review board members about their perspectives on ethical issues related to genetics in AI/AN/NH communities. We report findings related to perspectives on genetic research, data sharing, and envisioning stronger oversight and management of data. In particular, participants voiced concerns about different models of data sharing, infrastructure and logistics for housing data, and who should have authority to grant access to data. The results will ultimately guide policy-making and the creation of guidelines and new strategies for tribes to drive the research agenda and promote ethically and culturally appropriate research.Ethn Dis.2019;29(Suppl 3):659-668;doi:10.18865/ed.29.S3.659

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Kim, Youngseek, and Seungahn Nah. "Internet researchers’ data sharing behaviors." Online Information Review 42, no. 1 (February 12, 2018): 124–42. http://dx.doi.org/10.1108/oir-10-2016-0313.

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Purpose The purpose of this paper is to examine how data reuse experience, attitudinal beliefs, social norms, and resource factors influence internet researchers to share data with other researchers outside their teams. Design/methodology/approach An online survey was conducted to examine the extent to which data reuse experience, attitudinal beliefs, social norms, and resource factors predicted internet researchers’ data sharing intentions and behaviors. The theorized model was tested using a structural equation modeling technique to analyze a total of 201 survey responses from the Association of Internet Researchers mailing list. Findings Results show that data reuse experience significantly influenced participants’ perception of benefit from data sharing and participants’ norm of data sharing. Belief structures regarding data sharing, including perceived career benefit and risk, and perceived effort, had significant associations with attitude toward data sharing, leading internet researchers to have greater data sharing intentions and behavior. The results also reveal that researchers’ norms for data sharing had a direct effect on data sharing intention. Furthermore, the results indicate that, while the perceived availability of data repository did not yield a positive impact on data sharing intention, it has a significant, direct, positive impact on researchers’ data sharing behaviors. Research limitations/implications This study validated its novel theorized model based on the theory of planned behavior (TPB). The study showed a holistic picture of how different data sharing factors, including data reuse experience, attitudinal beliefs, social norms, and data repositories, influence internet researchers’ data sharing intentions and behaviors. Practical implications Data reuse experience, attitude toward and norm of data sharing, and the availability of data repository had either direct or indirect influence on internet researchers’ data sharing behaviors. Thus, professional associations, funding agencies, and academic institutions alike should promote academic cultures that value data sharing in order to create a virtuous cycle of reciprocity and encourage researchers to have positive attitudes toward/norms of data sharing; these cultures should be strengthened by the strong support of data repositories. Originality/value In line with prior scholarship concerning scientific data sharing, this study of internet researchers offers a map of scientific data sharing intentions and behaviors by examining the impacts of data reuse experience, attitudinal beliefs, social norms, and data repositories together.

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Heeney, Catherine. "An “Ethical Moment” in Data Sharing." Science, Technology, & Human Values 42, no. 1 (August 2, 2016): 3–28. http://dx.doi.org/10.1177/0162243916648220.

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This study draws on interviews with forty-nine members of a biomedical research community in the UK that is involved in negotiating data sharing and access. During an interview, an interviewee used the words “ethical moment” to describe a confrontation between collaborators in relation to data sharing. In this article, I use this as a lens for thinking about relations between “the conceptual and the empirical” in a way that allows both analyst and actor to challenge the status quo and consider other ethical possibilities. Drawing on actor network theory (ANT), I approach “the empirical” using the concepts of controversy and ontological uncertainty as methodological tools to tackle the problem of ethics. I suggest that these concepts also provide a bridge for understanding the ontological structure of the virtual and the actual, as described in Deleuze’s Difference and Repetition. While other science and technology studies scholars have sought to draw on Deleuze, this article addresses the integration of ethics and empirical research. It arises as a critical reaction to existing treatments of this problem as found in empirical ethics, especially in the sociology of bioethics, and indirectly in ANT texts.

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Higgins, Emma, Mark Taylor, Paulo Lisboa, and Farath Arshad. "Developing a data sharing framework: a case study." Transforming Government: People, Process and Policy 8, no. 1 (March 17, 2014): 151–64. http://dx.doi.org/10.1108/tg-02-2013-0007.

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Purpose – The purpose of the research project was to examine the process of developing a data sharing framework between different public sector organisations. Design/methodology/approach – A two-year case study of a data sharing project between a UK fire and rescue service, local council, NHS primary care trust and a police force was undertaken. Findings – It is important to carefully determine the requirements for data sharing, to establish data sharing agreements, to have secure arrangements for data sharing, and to ensure compliance with data protection legislation. Research limitations/implications – Data sharing between public sector organisations can operate effectively if appropriate care is taken when creating data sharing agreements between partner organisations. Practical implications – Data sharing can assist in reducing duplication of effort between public sector organisations and can reduce costs and enable more co-ordinated provision of public services. Originality/value – The detailed analysis of a data sharing case study identified the need for a systematic data sharing framework. Such a framework is proposed and illustrated with practical examples of specification, implementation and evaluation.

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Choudhary, Shipra PraveenKumar, Apeksha Katarni, Shweta Manjrekar, Mrs Vidyullata Devmane, and Mrs Vaishali Hirlekar. "Secret Sharing Approach in Multi-database System." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 15, no. 6 (April 20, 2016): 6819–23. http://dx.doi.org/10.24297/ijct.v15i6.1606.

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Secret sharing schemes are ideal for storingÂ highly sensitive data. A secret is divided into many parts and every participant gets his unique part. If we combine all of these parts and try regenerating the secret then it might be impractical, and therefore the threshold scheme is used. Shamirâ€™s secret sharing scheme supports the same. Here, some of the parts or all of them are required to reconstruct the secret. Any threshold number of parts are sufficient to reconstruct the original secret. The Admin has a set of files which are confidentiality and availability of data. Whenever a Client requests to access the files, the Admin performs authentication of the user through an encrypted and stored on multiple databases so as to achieve Authentication module, who makes use if Shamir's secret sharing concept. This is similar to the One Time Password (OTP) mechanism. If the Client is authentic, Admin grants him the decryption key and the Client can access the file. In this paper, we shall discuss all this in detail using which we can provide security, replication of data and authentication.Â

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Bonam, Janakiramaiah, and Ramamohan Reddy. "Balanced Approach for Hiding Sensitive Association Rules in Data Sharing Environment." International Journal of Information Security and Privacy 8, no. 3 (July 2014): 39–62. http://dx.doi.org/10.4018/ijisp.2014070103.

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Privacy preserving association rule mining protects the sensitive association rules specified by the owner of the data by sanitizing the original database so that the sensitive rules are hidden. In this paper, the authors study a problem of hiding sensitive association rules by carefully modifying the transactions in the database. The algorithm BHPSP calculates the impact factor of items in the sensitive association rules. Then it selects a rule which contains an item with minimum impact factor. The algorithm alters the transactions of the database to hide the sensitive association rule by reducing the loss of other non-sensitive association rules. The quality of a database can be well maintained by greedily selecting the alterations in the database with negligible side effects. The BHPSP algorithm is experimentally compared with a HCSRIL algorithm with respect to the performance measures misses cost and difference between original and sanitized databases. Experimental results are also mentioned demonstrating the effectiveness of the proposed approach.

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Aaliya, T., and R. Sharma. "SDSA An Implementation of Secure Data Sharing Approach Using Homomorphic Encryption." International Journal of Computer Sciences and Engineering 6, no. 5 (May 31, 2018): 118–25. http://dx.doi.org/10.26438/ijcse/v6i5.118125.

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Xu, Feifei, Liqing La, Feng Zhen, Tashi Lobsang, and Chao Huang. "A data-driven approach to guest experiences and satisfaction in sharing." Journal of Travel & Tourism Marketing 36, no. 4 (February 26, 2019): 484–96. http://dx.doi.org/10.1080/10548408.2019.1570420.

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Chen, Rufan, Yi Zhang, Zuochao Dou, Feng Chen, Kang Xie, and Shuang Wang. "Data Sharing and Privacy in Pharmaceutical Studies." Current Pharmaceutical Design 27, no. 7 (April 2, 2021): 911–18. http://dx.doi.org/10.2174/1381612827999210112204732.

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Abstract:: Adverse drug events have been a long-standing concern for the wide-ranging harms to public health, and the substantial disease burden. The key to diminish or eliminate the impacts is to build a comprehensive pharmacovigilance system. Application of the “big data” approach has been proved to assist the detection of adverse drug events by involving previously unavailable data sources and promoting health information exchange. Even though challenges and potential risks still remain. The lack of effective privacy-preserving measures in the flow of medical data is the most important Accepted: one, where urgent actions are required to prevent the threats and facilitate the construction of pharmacovigilance systems. Several privacy protection methods are reviewed in this article, which may be helpful to break the barrier.

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Nappo, A., and M. Giacomini. "An Experience of Microbiological Data Sharing." Methods of Information in Medicine 45, no. 02 (2006): 195–99. http://dx.doi.org/10.1055/s-0038-1634050.

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Summary Objectives: The control of infections and their resistance to antibiotics in hospitals is a matter of vital importance in the follow-up of transplant patients. This project has the purpose of translating microbiological reports from an obsolete file structure to a system which could guarantee a more correct and quick transmission of data, a system of storage which reduces the possibility of errors, a smoother manipulation, consultation and updating of data and, at least, a simple way to compute the cost of analysis, based on the costs determined by the national’s DRG. Methods: The proposed solution is a semiautomatic interface which translates these data into a relational database on a daily basis, interprets the requests coming from external centers and produces reports. The prospective to use this tool for several centers indicates to us the need to choose an HL7 output for the interface. Results: A prototype version of this program was installed in February 2004. In this period, routine work has been recorded with an average of 6.5 samples per day, with a maximum of 23 samples. Moreover, historical data from 1998 has been translated. The main source of errors in these data was due to patient identification problems with an average occurrence of 4.06% in the virology section and of 4.16% in the microbiological division. Conclusions: A complete reorganization of the system would be desirable but at the moment it is not realistic because of obvious budget problems. The proposed approach, mainly the HL7 interface, seems to be a reasonable compromise.

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Abbas, Antragama Ewa, Wirawan Agahari, Montijn van de Ven, Anneke Zuiderwijk, and Mark de Reuver. "Business Data Sharing through Data Marketplaces: A Systematic Literature Review." Journal of Theoretical and Applied Electronic Commerce Research 16, no. 7 (December 3, 2021): 3321–39. http://dx.doi.org/10.3390/jtaer16070180.

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Data marketplaces are expected to play a crucial role in tomorrow’s data economy, but such marketplaces are seldom commercially viable. Currently, there is no clear understanding of the knowledge gaps in data marketplace research, especially not of neglected research topics that may advance such marketplaces toward commercialization. This study provides an overview of the state-of-the-art of data marketplace research. We employ a Systematic Literature Review (SLR) approach to examine 133 academic articles and structure our analysis using the Service-Technology-Organization-Finance (STOF) model. We find that the extant data marketplace literature is primarily dominated by technical research, such as discussions about computational pricing and architecture. To move past the first stage of the platform’s lifecycle (i.e., platform design) to the second stage (i.e., platform adoption), we call for empirical research in non-technological areas, such as customer expected value and market segmentation.

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Ghoshal, Abhijeet, Jing Hao, Syam Menon, and Sumit Sarkar. "Hiding Sensitive Information when Sharing Distributed Transactional Data." Information Systems Research 31, no. 2 (June 2020): 473–90. http://dx.doi.org/10.1287/isre.2019.0898.

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Although retailers recognize the potential value of sharing transactional data with supply chain partners, many remain reluctant to share. However, there is evidence that the extent of sharing would be greater if information sensitive to retailers can be concealed before sharing. Extant research has only considered sensitive information at the organizational level. This is rarely the case in reality; the retail industry has adapted their offerings to region-wide differences in customer tastes for decades. Differences in customer characteristics across regions lead to region-specific sensitive information in addition to any at the organizational level. This is the first paper to propose an approach to solve this version of the problem. Region-level requirements increase the size of an already difficult (NP-hard) problem substantially, making adaptations of existing approaches impractical. We present an ensemble approach that draws intuition from Lagrangian relaxation to conceal sensitive patterns at the organizational and regional levels with minimal damage to the data set. Extensive computational experiments show that it identifies optimal or near-optimal solutions even when other approaches fail, doing so without any loss in recommendation effectiveness. This mitigates potential risks associated with sharing and should increase data sharing among partners in the supply chain.

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Huser, Vojtech, and Dikla Shmueli-Blumberg. "Data sharing platforms for de-identified data from human clinical trials." Clinical Trials 15, no. 4 (April 20, 2018): 413–23. http://dx.doi.org/10.1177/1740774518769655.

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Data sharing of de-identified individual participant data is being adopted by an increasing number of sponsors of human clinical trials. In addition to standardizing data syntax for shared trial data, semantic integration of various data elements is the focus of several initiatives that define research common data elements. This perspective article, in the first part, compares several data sharing platforms for de-identified clinical research data in terms of their size, policies and supported features. In the second part, we use a case study approach to describe in greater detail one data sharing platform (Data Share from National Institute of Drug Abuse). We present data on the past use of the platform, data formats offered, data de-identification approaches and its use of research common data elements. We conclude with a summary of current and expected future trends that facilitate secondary research use of data from completed human clinical trials.

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Okazaki, Shintaro, Ana M. Díaz-Martín, Mercedes Rozano, and Héctor David Menéndez-Benito. "Using Twitter to engage with customers: a data mining approach." Internet Research 25, no. 3 (June 1, 2015): 416–34. http://dx.doi.org/10.1108/intr-11-2013-0249.

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Purpose – The purpose of this paper is to explore customer engagement in Twitter via data mining. Design/methodology/approach – This study’s intended contributions are twofold: to find a clear connection among customer engagement, presumption, and Web 2.0 in a context of service-dominant (S-D) logic; and to identify social networks created by prosumers. To this end, the study employed data mining techniques. Tweets about IKEA were used as a sample. The resulting algorithm based on 300 tweets was applied to 4,000 tweets to identify the patterns of electronic word-of-mouth (eWOM). Findings – Social networks created in IKEA’s tweets consist of three forms of eWOM: objective statements, subjective statements, and knowledge sharing. Most objective statements are disseminated from satisfied or neutral customers, while subjective statements are disseminated from dissatisfied or neutral customers. Satisfied customers mainly carry out knowledge sharing, which seems to reflect presumption behavior. Research limitations/implications – This study provides partial evidence of customer engagement and presumption in IKEA’s tweets. The results indicate that there are three forms of eWOM in the networks: objective statements, subjective statements, and knowledge sharing. It seems that IKEA successfully engaged customers in knowledge sharing, while negative opinions were mainly disseminated in a limited circle. Practical implications – Firms should make more of an effort to identify prosumers via data mining, since these networks are hidden behind “self-proclaimed” followers. Prosumers differ from opinion leaders, since they actively participate in product development. Thus, firms should seek prosumers in order to more closely fit their products to consumer needs. As a practical strategy, firms could employ celebrities for promotional purposes and use them as a platform to convert their followers to prosumers. In addition, firms are encouraged to make public how they resolve problematic customer complaints so that customers can feel they are a part of firms’ service development. Originality/value – Theoretically, the study makes unique contributions by offering a synergic framework of S-D logic and Web 2.0. The conceptual framework collectively relates customer engagement, presumption, and Web 2.0 to social networks. In addition, the idea of examining social networks based on different forms of eWOM has seldom been touched in the literature. Methodologically, the study employed seven algorithms to choose the most robust model, which was later applied to 4,000 tweets.

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Doorn, Peter, Ingrid Dillo, and René Van Horik. "Lies, Damned Lies and Research Data: Can Data Sharing Prevent Data Fraud?" International Journal of Digital Curation 8, no. 1 (June 14, 2013): 229–43. http://dx.doi.org/10.2218/ijdc.v8i1.256.

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After a spectacular case of data fraud in the field of social psychology surfaced in The Netherlands in September 2011, the Dutch research community was confronted with a number of questions. Is this an isolated case or is scientific fraud with data more common? Is the scientific method robust enough to uncover the results of misconduct and to withstand the breach of trust that fraud causes? How responsible and reliable are researchers when they collect, process, analyse and report on data? How can we prevent data fraud? Do we need to adapt the codes of conduct for researchers or do we need stricter rules for data management and data sharing?This paper discusses the conclusions and recommendations of two reports that were published recently in consequence of this data fraud. The reports are relevant for scientific integrity and trustworthy treatment of research data. Next, this paper reports on the outcomes of enquiries in data cultures in a number of scientific disciplines. The concluding section of this paper contains a number of examples that show that the approach towards data sharing is improving gradually. The data fraud case can be regarded as a wake-up call.

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Guérin, Julien, Yec'han Laizet, Vincent Le Texier, Laetitia Chanas, Bastien Rance, Florence Koeppel, François Lion, et al. "OSIRIS: A Minimum Data Set for Data Sharing and Interoperability in Oncology." JCO Clinical Cancer Informatics, no. 5 (March 2021): 256–65. http://dx.doi.org/10.1200/cci.20.00094.

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PURPOSE Many institutions throughout the world have launched precision medicine initiatives in oncology, and a large amount of clinical and genomic data is being produced. Although there have been attempts at data sharing with the community, initiatives are still limited. In this context, a French task force composed of Integrated Cancer Research Sites (SIRICs), comprehensive cancer centers from the Unicancer network (one of Europe's largest cancer research organization), and university hospitals launched an initiative to improve and accelerate retrospective and prospective clinical and genomic data sharing in oncology. MATERIALS AND METHODS For 5 years, the OSIRIS group has worked on structuring data and identifying technical solutions for collecting and sharing them. The group used a multidisciplinary approach that included weekly scientific and technical meetings over several months to foster a national consensus on a minimal data set. RESULTS The resulting OSIRIS set and event-based data model, which is able to capture the disease course, was built with 67 clinical and 65 omics items. The group made it compatible with the HL7 Fast Healthcare Interoperability Resources (FHIR) format to maximize interoperability. The OSIRIS set was reviewed, approved by a National Plan Strategic Committee, and freely released to the community. A proof-of-concept study was carried out to put the OSIRIS set and Common Data Model into practice using a cohort of 300 patients. CONCLUSION Using a national and bottom-up approach, the OSIRIS group has defined a model including a minimal set of clinical and genomic data that can be used to accelerate data sharing produced in oncology. The model relies on clear and formally defined terminologies and, as such, may also benefit the larger international community.

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Chen, Dong, Wei Lu, Weiwei Xing, and Na Wang. "An Untraceable Data Sharing Scheme in Wireless Sensor Networks." Sensors 19, no. 1 (December 31, 2018): 114. http://dx.doi.org/10.3390/s19010114.

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With the wide application of wireless sensor networks (WSNs), secure data sharing in networks is becoming a hot research topic and attracting more and more attention. A huge challenge is securely transmitting the data from the source node to the sink node. Except for eavesdropping the information stored in the packages, the adversary may also attempt to analyze the contextual information of the network to locate the source node. In this paper, we proposed a secure data sharing approach to defend against the adversary. Specifically, we first design a secret key mechanism to guarantee the security of package delivery between a pair of nodes. Then, a light-weighted secret sharing scheme is designed to map the original message to a set of shares. Finally, the shares are delivered to the sink node independently based on a proper random routing algorithm. Simulation results illustrate that our approach can defend against the eavesdropping and tracing-back attack in an energy-efficient manner.

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Pandit, Harshvardhan Jitendra, and Adrian O’Riordan. "A model for contextual data sharing in smartphone applications." International Journal of Pervasive Computing and Communications 12, no. 3 (September 5, 2016): 310–31. http://dx.doi.org/10.1108/ijpcc-06-2016-0030.

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Purpose The purpose of this paper is to introduce a model for identifying, storing and sharing contextual information across smartphone apps that uses the native device services. The authors present the idea of using user input and interaction within an app as contextual information, and how each app can identify and store contextual information. Design/methodology/approach Contexts are modeled as hierarchical objects that can be stored and shared by applications using native mechanisms. A proof-of-concept implementation of the model for the Android platform demonstrates contexts modelled as hierarchical objects stored and shared by applications using native mechanisms. Findings The model was found to be practically viable by implemented sample apps that share context and through a performance analysis of the system. Practical implications The contextual data-sharing model enables the creation of smart apps and services without being tied to any vendor’s cloud services. Originality/value This paper introduces a new approach for sharing context in smartphone applications that does not require cloud services.

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Previtali, Mattia, and Riccardo Valente. "Archaeological documentation and data sharing: digital surveying and open data approach applied to archaeological fieldworks." Virtual Archaeology Review 10, no. 20 (January 28, 2019): 17. http://dx.doi.org/10.4995/var.2019.10377.

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The open data paradigm is changing the research approach in many fields such as remote sensing and the social sciences. This is supported by governmental decisions and policies that are boosting the open data wave, and in this context archaeology is also affected by this new trend. In many countries, archaeological data are still protected or only limited access is allowed. However, the strong political and economic support for the publication of government data as open data will change the accessibility and disciplinary expertise in the archaeological field too. In order to maximize the impact of data, their technical openness is of primary importance. Indeed, since a spreadsheet is more usable than a PDF of a table, the availability of digital archaeological data, which is structured using standardised approaches, is of primary importance for the real usability of published data. In this context, the main aim of this paper is to present a workflow for archaeological data sharing as open data with a large level of technical usability and interoperability. Primary data is mainly acquired through the use of digital techniques (e.g. digital cameras and terrestrial laser scanning). The processing of this raw data is performed with commercial software for scan registration and image processing, allowing for a simple and semi-automated workflow. Outputs obtained from this step are then processed in modelling and drawing environments to generate digital models, both 2D and 3D. These crude geometrical data are then enriched with further information to generate a Geographic Information System (GIS) which is finally published as open data using Open Geospatial Consortium (OGC) standards to maximise interoperability.Highlights:<ul><li>Open data will change the accessibility and disciplinary expertise in the archaeological field.</li><li>The main aim of this paper is to present a workflow for archaeological data sharing as open data with a large level of interoperability.</li><li>Digital acquisition techniques are used to document archaeological excavations and a Geographic Information System (GIS) is generated that is published as open data.</li></ul>

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Zhao, Wei, Bing Zhou, and ChaoYang Zhang. "Heterogeneous Social Linked Data Integration and Sharing for Public Transportation." Journal of Advanced Transportation 2022 (May 11, 2022): 1–14. http://dx.doi.org/10.1155/2022/6338365.

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Solid (social linked data) technology has made significant progress in social web applications developed, such as Facebook, Twitter, and Wikipedia. Solid is based on semantic web and RDF (Resource Description Framework) technologies. Solid platforms can provide decentralized authentication, data management, and developer support in the form of libraries and web applications. However, thus far, little research has been conducted on understanding the problems involved in sharing public transportation data through Solid technology. It is challenging to provide personalized and adaptable public transportation services for citizens because the public transportation data originate from different devices and are heterogeneous in nature. A novel approach is proposed in this study, in order to provide personalized sharing of public transportation data between different users through integrating and sharing these heterogeneous data. This approach not only integrates diverse data types into a uniform data type using the semantic web but also stores these data in a personal online data store and retrieves data through SPARQL on the Solid platform; these data are visualized on the web pages using Google Maps. To the best of our knowledge, we are the first to apply Solid in public transportation. Furthermore, we conduct performance tests of the new C2RMF (CSV to RDF Mapping File) algorithm and functional and non-functional tests to demonstrate the stability and effectiveness of the approach. Our results indicate the feasibility of the proposed approach in facilitating public transportation data integration and sharing through Solid and semantic web technologies.

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Cipriano, Marco, Luca Colomba, and Paolo Garza. "A Data-Driven Based Dynamic Rebalancing Methodology for Bike Sharing Systems." Applied Sciences 11, no. 15 (July 28, 2021): 6967. http://dx.doi.org/10.3390/app11156967.

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Mobility in cities is a fundamental asset and opens several problems in decision making and the creation of new services for citizens. In the last years, transportation sharing systems have been continuously growing. Among these, bike sharing systems became commonly adopted. There exist two different categories of bike sharing systems: station-based systems and free-floating services. In this paper, we concentrate our analyses on station-based systems. Such systems require periodic rebalancing operations to guarantee good quality of service and system usability by moving bicycles from full stations to empty stations. In particular, in this paper, we propose a dynamic bicycle rebalancing methodology based on frequent pattern mining and its implementation. The extracted patterns represent frequent unbalanced situations among nearby stations. They are used to predict upcoming critical statuses and plan the most effective rebalancing operations using an entirely data-driven approach. Experiments performed on real data of the Barcelona bike sharing system show the effectiveness of the proposed approach.

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Saunders, Pamela Anne, Erin E. Wilhelm, Sinae Lee, Elizabeth Merkhofer, and Ira Shoulson. "Data sharing for public health research: A qualitative study of industry and academia." Communication and Medicine 11, no. 2 (August 17, 2015): 179–87. http://dx.doi.org/10.1558/cam.v11i2.18310.

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Data sharing is a key biomedical research theme for the 21st century. Biomedical data sharing is the exchange of data among (non)affiliated parties under mutually agreeable terms to promote scientific advancement and the development of safe and effective medical products. Wide sharing of research data is important for scientific discovery, medical product development, and public health. Data sharing enables improvements in development of medical products, more attention to rare diseases, and cost-efficiencies in biomedical research. We interviewed 11 participants about their attitudes and beliefs about data sharing. Using a qualitative, thematic analysis approach, our analysis revealed a number of themes including: experiences, approaches, perceived challenges, and opportunities for sharing data.

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Hongmei, Zhao. "A Cross-Border E-Commerce Approach Based on Blockchain Technology." Mobile Information Systems 2021 (July 15, 2021): 1–10. http://dx.doi.org/10.1155/2021/2006082.

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In the current cross-border electronic commerce (e-commerce) system, various document recording and authorization processes are cumbersome, record sharing efficiency is low, and identity verification is difficult. A method of asymmetric encryption technology combining Blockchain technology and cryptography is proposed. The advantages of asymmetric encrypted communications include high security and ease of multiparties communication collaboration, being applied to a peer-to-peer network formed by Blockchain technology, and making cross-border e-commerce record cross-domain sharing traceable, data immutable, and identity verification simplified. First of all, based on the immutable modification of Blockchain technology and asymmetric encryption technology, file synchronization contracts and authorization contracts are designed. Its distributed storage advantages ensure the privacy of users’ cross-border e-commerce information. Second, the design of the cross-domain acquisition contract can effectively verify the identity and transmission efficiency of both parties to the data sharing, so that illegal users can be safely filtered without a third-party notary institution. The simulation experiment results show that the solution proposed in this paper has obvious advantages in data antitheft, multiparty authentication, and saving system overhead compared with traditional cloud computing methods to solve the problem of sharing medical records. It provides a reference for solving the security problems in the process of data sharing by using the advantages of Blockchain’s decentralization and auditability and provides reference ideas for solving the problems of data sharing and cross-domain authentication.

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Journal articles on the topic 'Data sharing approach'

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