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Journal articles on the topic 'Data commons'

Author: Grafiati

Published: 25 May 2024

Last updated: 25 July 2025

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1

Grossman, Robert L., Jonathan R. Dry, Sean E. Hanlon, et al. "BloodPAC Data Commons for Liquid Biopsy Data." JCO Clinical Cancer Informatics, no. 5 (April 2021): 479–86. http://dx.doi.org/10.1200/cci.20.00179.

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PURPOSE The Blood Profiling Atlas in Cancer (BloodPAC) Data Commons (BPDC) is being developed and is operated by the public-private BloodPAC Consortium to support the liquid biopsy community. It is an interoperable data commons with the ultimate aim of serving as a recognized source of valid scientific evidence for liquid biopsy assays for industry, academia, and standards and regulatory stakeholders. METHODS The BPDC is implemented using the open source Gen3 data commons platform ( https://gen3.org ). In particular, the BPDC Data Exploration Portal, BPDC Data Submission Portal, the BPDC Works

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Fedorov, A., W. Longabaugh, D. Pot, et al. "NCI Imaging Data Commons." International Journal of Radiation Oncology*Biology*Physics 111, no. 3 (2021): e101. http://dx.doi.org/10.1016/j.ijrobp.2021.07.495.

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Fedorov, Andrey, William J. R. Longabaugh, David Pot, et al. "NCI Imaging Data Commons." Cancer Research 81, no. 16 (2021): 4188–93. http://dx.doi.org/10.1158/0008-5472.can-21-0950.

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Hughes, LaRon, Robert L. Grossman, Zachary Flamig, et al. "Harmonization of clinical data across Gen3 data commons." Journal of Clinical Oncology 37, no. 15_suppl (2019): e18094-e18094. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e18094.

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e18094 Background: Gen3 is an open source software platform for developing and operating data commons. Gen3 systems are now used by a variety of institutions and agencies to share and analyze large biomedical datasets including clinical and genomic data. One of the challenges of working with these datasets is disparate clinical data standards used by researchers across different studies and fields. We have worked to address these hurdles in a variety of ways. Methods: Gen3 is an open source software platform for developing and operating data commons. Detailed specification and features can be

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Heath, Allison P., Vincent Ferretti, Stuti Agrawal, et al. "The NCI Genomic Data Commons." Nature Genetics 53, no. 3 (2021): 257–62. http://dx.doi.org/10.1038/s41588-021-00791-5.

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Spichtinger, Daniel. "Uncommon Commons? Creative Commons Licencing in Horizon 2020 Data Management Plans." International Journal of Digital Curation 17, no. 1 (2022): 9. http://dx.doi.org/10.2218/ijdc.v17i1.840.

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As policies, good practices and mandates on research data management evolve, more emphasis has been put on the licencing of data, which allows potential re-users to quickly identify what they can do with the data in question. In this paper I analyse a pre-existing collection of 840 Horizon 2020 public data management plans (DMPs) to determine which ones mention creative commons licences and among those who do, which licences are being used.  I find that 36% of DMPs mention creative commons and among those a number of different approaches towards licencing exist (overall policy per projec

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Kajander, Aleksi, and Thomas Hoffmann. "Smart City Data Commons under the Data Governance Act – Lowering the Threshold Toward Introducing Smart City Data Commons." International and Comparative Law Review 24, no. 2 (2024): 7–24. https://doi.org/10.2478/iclr-2024-0016.

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Summary Smart Cities will provide an unprecedented trove of data that is set to revolutionize the efficiency of cities and the competitiveness of businesses according to the EU’s Strategy for Data. The governance of this data is concerning, for it is already evident that non-personal data can significantly affect communities, an effect which would be amplified in a smart city. However, under the EU’s current legal framework the ability of communities to govern non-personal data in smart cities is almost non-existent. Consequently, smart city data commons have been highlighted as a possible sol

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Stein, Lincoln D., Bartha M. Knoppers, Peter Campbell, Gad Getz, and Jan O. Korbel. "Data analysis: Create a cloud commons." Nature 523, no. 7559 (2015): 149–51. http://dx.doi.org/10.1038/523149a.

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Schofield, Paul N., Janan Eppig, Eva Huala, et al. "Sustaining the Data and Bioresource Commons." Science 330, no. 6004 (2010): 592–93. http://dx.doi.org/10.1126/science.1191506.

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Plana, Alejandro, Brian Furner, Monica Palese, et al. "Pediatric Cancer Data Commons: Federating and Democratizing Data for Childhood Cancer Research." JCO Clinical Cancer Informatics, no. 5 (October 2021): 1034–43. http://dx.doi.org/10.1200/cci.21.00075.

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The international pediatric oncology community has a long history of research collaboration. In the United States, the 2019 launch of the Children's Cancer Data Initiative puts the focus on developing a rich and robust data ecosystem for pediatric oncology. In this spirit, we present here our experience in constructing the Pediatric Cancer Data Commons (PCDC) to highlight the significance of this effort in fighting pediatric cancer and improving outcomes and to provide essential information to those creating resources in other disease areas. The University of Chicago's PCDC team has worked wit

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Volchenboum, Samuel L., Suzanne M. Cox, Allison Heath, Adam Resnick, Susan L. Cohn, and Robert Grossman. "Data Commons to Support Pediatric Cancer Research." American Society of Clinical Oncology Educational Book, no. 37 (May 2017): 746–52. http://dx.doi.org/10.1200/edbk_175029.

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The falling costs and increasing fidelity of high-throughput biomedical research data have led to a renaissance in cancer surveillance and treatment. Yet, the amount, velocity, and complexity of these data have overcome the capacity of the increasing number of researchers collecting and analyzing this information. By centralizing the data, processing power, and tools, there is a valuable opportunity to share resources and thus increase the efficiency, power, and impact of research. Herein, we describe current data commons and how they operate in the oncology landscape, including an overview of

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Eschenfelder, Kristin R., and Andrew Johnson. "Managing the data commons: Controlled sharing of scholarly data." Journal of the Association for Information Science and Technology 65, no. 9 (2014): 1757–74. http://dx.doi.org/10.1002/asi.23086.

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13

Ci, Bo, Donghan M. Yang, Mark Krailo, et al. "Development of a Data Model and Data Commons for Germ Cell Tumors." JCO Clinical Cancer Informatics, no. 4 (September 2020): 555–66. http://dx.doi.org/10.1200/cci.20.00025.

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Germ cell tumors (GCTs) are considered a rare disease but are the most common solid tumors in adolescents and young adults, accounting for 15% of all malignancies in this age group. The rarity of GCTs in some groups, particularly children, has impeded progress in treatment and biologic understanding. The most effective GCT research will result from the interrogation of data sets from historical and prospective trials across institutions. However, inconsistent use of terminology among groups, different sample-labeling rules, and lack of data standards have hampered researchers’ efforts in data

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Volchenboum, Samuel L., Suzanne M. Cox, Allison Heath, Adam Resnick, Susan L. Cohn, and Robert Grossman. "Data Commons to Support Pediatric Cancer Research." American Society of Clinical Oncology Educational Book 37 (2017): 746–52. http://dx.doi.org/10.14694/edbk_175029.

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15

Contreras, J. L. "Prepublication Data Release, Latency, and Genome Commons." Science 329, no. 5990 (2010): 393–94. http://dx.doi.org/10.1126/science.1189253.

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Contreras, J. L., and J. H. Reichman. "Sharing by design: Data and decentralized commons." Science 350, no. 6266 (2015): 1312–14. http://dx.doi.org/10.1126/science.aaa7485.

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Kajander, Aleksi. "Legal Perspectives on Smart City Data as a Commons." International and Comparative Law Review 22, no. 2 (2022): 7–26. http://dx.doi.org/10.2478/iclr-2022-0012.

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Summary Smart cities are purported to produce vast amounts of data of immense value, both commercially and from a governance perspective. The control and stewardship of this smart city data remains controversial, with concerns for the role of the individual smart citizens and the control they exercise over the data they generate. Elinor Ostrom’s Nobel prize winning work on long-lasting and sustainable commons has been suggested as a solution, whereby the commons management principles would be applied to smart city data. This paper seeks to identify the current applications of Ostrom’s commons

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Wyatt, Kirk D., Véronique Minard-Colin, Gudrun Schleiermacher, Michaela Willi, and Samuel L. Volchenboum. "GDPR and data sharing: the Pediatric Cancer Data Commons experience." Lancet Oncology 25, no. 6 (2024): e227. http://dx.doi.org/10.1016/s1470-2045(24)00250-x.

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Prainsack, Barbara. "Logged out: Ownership, exclusion and public value in the digital data and information commons." Big Data & Society 6, no. 1 (2019): 205395171982977. http://dx.doi.org/10.1177/2053951719829773.

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In recent years, critical scholarship has drawn attention to increasing power differentials between corporations that use data and people whose data is used. A growing number of scholars see digital data and information commons as a way to counteract this asymmetry. In this paper I raise two concerns with this argument: First, because digital data and information can be in more than one place at once, governance models for physical common-pool resources cannot be easily transposed to digital commons. Second, not all data and information commons are suitable to address power differentials. In o

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Fia, Tommaso, and Gijs Van Maanen. "Through thick and thin: data commons, community and the struggle for collective data governance." Technology and Regulation 2025 (June 2, 2025): 114–36. https://doi.org/10.71265/tk2x3d39.

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Collective data governance mechanisms such as data commons have recently gained traction in both theoretical and policy-oriented discussions as promising alternatives to the shortcomings of individualistic data protection and data markets. Many of these approaches centre around the idea of community as the key social institution overcoming these limitations. Yet, far less attention has been paid to the meaning, features and implications that the language of community can have for data commons. This paper investigates the relationship between data commons and the community involved therein, wit

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Madison, Michael. "Tools for Data Governance." Technology and Regulation 2020 (July 16, 2020): 29–43. https://doi.org/10.71265/svpw6397.

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This article describes the challenges of data governance in terms of the broader framework of knowledge commons governance, an institutional approach to gov- erning shared knowledge, information, and data resources. Knowledge commons governance highlights the potential for effective community- and collective-based governance of knowledge resources. The article focuses on key concepts within the knowledge commons framework rather than on specific law and public pol- icy questions, directing the attention of researchers and policymakers to critical inquiry regarding relevant social groups and re

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22

Grossman, Robert L., Allison Heath, Mark Murphy, Maria Patterson, and Walt Wells. "A Case for Data Commons: Toward Data Science as a Service." Computing in Science & Engineering 18, no. 5 (2016): 10–20. http://dx.doi.org/10.1109/mcse.2016.92.

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23

Contreras, Jorge L., and Bartha M. Knoppers. "The Genomic Commons." Annual Review of Genomics and Human Genetics 19, no. 1 (2018): 429–53. http://dx.doi.org/10.1146/annurev-genom-083117-021552.

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Over its 30 or so years of existence, the genomic commons—the worldwide collection of publicly accessible repositories of human and nonhuman genomic data—has enjoyed remarkable, perhaps unprecedented, success. Thanks to the rapid public data release policies initiated by the Human Genome Project, free access to a vast array of scientific data is now the norm, not only in genomics, but in scientific disciplines of all descriptions. And far from being a monolithic creation of bureaucratic fiat, the genomic commons is an exemplar of polycentric, multistakeholder governance. But like all dynamic a

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Cook-Deegan, Robert, Mary A. Majumder, and Amy L. McGuire. "Introduction: Sharing Data in a Medical Information Commons." Journal of Law, Medicine & Ethics 47, no. 1 (2019): 7–11. http://dx.doi.org/10.1177/1073110519840479.

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Thuraga, Santhosh Reddy. "Data Commons Platforms: Addressing Challenges and Opportunities in Large-Scale Biomedical Data Integration and Analysis." International Journal for Research in Applied Science and Engineering Technology 12, no. 9 (2024): 1038–50. http://dx.doi.org/10.22214/ijraset.2024.64267.

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Abstract: Data Commons Platforms are emerging as transformative tools in the landscape of medical research, offering a centralized, accessible, and scalable infrastructure for managing, analyzing, and sharing vast amounts of biomedical data. This article provides a comprehensive examination of these platforms, exploring their core functionalities, benefits, and challenges in the context of advancing medical discovery. We discuss how Data Commons Platforms accelerate research by facilitating datadriven hypothesis generation, enhancing collaboration among researchers, improving data accessibilit

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Ottolia, Andrea, and Cristiana Sappa. "A Topography of Data Commons: From Regulation to Private Dynamism." GRUR International 71, no. 4 (2021): 335–45. http://dx.doi.org/10.1093/grurint/ikab156.

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Abstract Knowledge is subject to enclosure through digital technology and legal rules. Data collected, stored and pooled by the Internet of Things (IoT) or Artificial Intelligence (AI) are no exception to this. Operators acting in the markets related to the algorithmic society may have a quite diversified range of intellectual property rights (IPRs) to protect the information they produce and manage. This is exploited through algorithmic processing techniques, aggregating collected data for the generation of new ones, thus creating additional information and knowledge. This paper studies wheth

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Senabre Hidalgo, Enric, Antonio Calleja, Ricard Espelt, Sara Suárez Gonzalo, Mayo Fuster Morell, and Andreu Belsunces. "Co-creation of the Digital Democracy and Data Commons Manifesto: alternative sociotechnical visions of data." Open Research Europe 4 (March 1, 2024): 45. http://dx.doi.org/10.12688/openreseurope.17020.1.

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Amid public concern surrounding the proprietary and exploitative use of personal data by corporations and public institutions, and its consequences from a sociotechnical perspective, narratives around digital commons have recently emerged, framing potential alternatives. This paper presents the results of an experimental approach, methodology, and process, through which two main questions are addressed. Firstly, how to articulate co-creation dynamics for the structured and participatory elaboration of the Digital Democracy and Data Commons Manifesto, following principles of openness, diversity

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Cerami, E. G., B. E. Gross, E. Demir, et al. "Pathway Commons, a web resource for biological pathway data." Nucleic Acids Research 39, Database (2010): D685—D690. http://dx.doi.org/10.1093/nar/gkq1039.

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McGuire, Amy L., Jessica Roberts, Sean Aas, and Barbara J. Evans. "Who Owns the Data in a Medical Information Commons?" Journal of Law, Medicine & Ethics 47, no. 1 (2019): 62–69. http://dx.doi.org/10.1177/1073110519840485.

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In this paper, we explore the perspectives of expert stakeholders about who owns data in a medical information commons (MIC) and what rights and interests ought to be recognized when developing a governance structure for an MIC. We then examine the legitimacy of these claims based on legal and ethical analysis and explore an alternative framework for thinking about participants' rights and interests in an MIC.

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Crețu, Valentin Bogdan. "Data, governance and tackling the “tragedy of the commons”." International Journal of Advanced Statistics and IT&C for Economics and Life Sciences 12, no. 2 (2022): 17–23. http://dx.doi.org/10.2478/ijasitels-2022-0003.

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Abstract The purpose of this paper is to highlight the importance of active and continued public engagement in the debate regarding the regulation of artificial intelligence (AI). The results of several studies are presented, in reference to the benefits of this technology, its risks and limitations, and the shortcomings of traditional and hybrid approaches. Certain conceptual and practical approaches are presented, that aim to facilitate the participation of citizens and other stakeholders in the decision-making process of AI governance.

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Charbonneau, Amanda, Arthur Brady, Tanner Coon, et al. "Abstract 1064: Cancer data aggregator: a new cancer data discovery tool." Cancer Research 85, no. 8_Supplement_1 (2025): 1064. https://doi.org/10.1158/1538-7445.am2025-1064.

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Cancer research data is generated and managed in silos. Data repositories frequently use different models and vocabularies to describe their data holdings, and many specialize in certain data types, necessitating that data from a large integrative project be spread across several repositories. For researchers who want to reuse existing cancer data, just navigating this ecosystem of repositories, formats and models can be overwhelming. The Cancer Data Aggregator (CDA) is a new free National Cancer Institute (NCI) service that aims to increase the discoverability of cancer datasets by making the

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Gao, Galen F., Joel S. Parker, Sheila M. Reynolds, et al. "Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons’ Data." Cell Systems 9, no. 1 (2019): 24–34. http://dx.doi.org/10.1016/j.cels.2019.06.006.

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Ramasamy, Thelagavathy Naidu, and Shathees Baskaran. "The Influence of Health Data Spaces, Data Repositories, Data Collectives, Data Natives, and Data Commons on Artificial Intelligence for Clinical Decision-Making Among Physicians." Business Management and Strategy 15, no. 2 (2024): 306. http://dx.doi.org/10.5296/bms.v15i2.22260.

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This study investigated the perspectives of physicians regarding the influence of Health Data Spaces, Data Repositories, Data Collectives, Data Natives, and Data Commons on Clinical Decision Making in Malaysian Healthcare. In particular, this study addressed the mediating effect of artificial intelligence (AI) on the relationship between these health data concepts and Clinical Decision Making. A descriptive, analytical, cross-sectional study was conducted in public and private hospitals in Malaysia. The research population entails physicians with experience handling EMR. The sample included 16

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Baarbé, Jeremiah, Meghan Blom, and Jeremy De Beer. "A Proposed “Agricultural Data Commons” in Support of Food Security." African Journal of Information and Communication, no. 23 (June 28, 2019): 1–33. http://dx.doi.org/10.23962/10539/27534.

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Zhang, Guo-Qiang, Licong Cui, Remo Mueller, et al. "The National Sleep Research Resource: towards a sleep data commons." Journal of the American Medical Informatics Association 25, no. 10 (2018): 1351–58. http://dx.doi.org/10.1093/jamia/ocy064.

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Abstract Objective The gold standard for diagnosing sleep disorders is polysomnography, which generates extensive data about biophysical changes occurring during sleep. We developed the National Sleep Research Resource (NSRR), a comprehensive system for sharing sleep data. The NSRR embodies elements of a data commons aimed at accelerating research to address critical questions about the impact of sleep disorders on important health outcomes. Approach We used a metadata-guided approach, with a set of common sleep-specific terms enforcing uniform semantic interpretation of data elements across t

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Dobusch, Leonhard, Stefan Pawel, Gustav Pomberger, and René Riedl. "Open Government Data: eine Initiative der Open-Commons-Region Linz." HMD Praxis der Wirtschaftsinformatik 49, no. 1 (2012): 74–83. http://dx.doi.org/10.1007/bf03340665.

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37

Printz, Carrie. "Genomic Data Commons ushers in new era for information sharing." Cancer 122, no. 18 (2016): 2777–78. http://dx.doi.org/10.1002/cncr.30278.

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Kerlavage, Anthony. "Abstract IA24: A modern data commons approach to advance population science." Cancer Epidemiology, Biomarkers & Prevention 29, no. 9_Supplement (2020): IA24. http://dx.doi.org/10.1158/1538-7755.modpop19-ia24.

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Abstract Since 2014, NCI has been building data science platforms to integrate genetic information about tumors with data on how patients respond to therapy. This work advances the 2011 Institute of Medicine recommendation to build a unified system to collect, integrate, and share cancer data from the widest possible set of research studies. NCI is working to fulfill this recommendation by establishing an NCI Cancer Research Data Commons (CRDC), virtual, expandable informatics infrastructure and data repositories, which are designed to support the work of the NCI intramural and extramural canc

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39

Senabre Hidalgo, Enric, Antonio Calleja, Ricard Espelt, Sara Suárez Gonzalo, Mayo Fuster Morell, and Andreu Belsunces. "Co-creation of the Digital Democracy and Data Commons Manifesto: alternative sociotechnical visions of data." Open Research Europe 4 (October 25, 2024): 45. http://dx.doi.org/10.12688/openreseurope.17020.2.

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Amid public concern surrounding the proprietary and exploitative use of personal data by corporations and public institutions, and its consequences from a sociotechnical perspective, narratives around digital commons have recently emerged, framing potential alternatives. This paper presents the co-creation of the Digital Democracy and Data Commons Manifesto through a collaborative writing sprint, drawing on principles of openness, diversity, and inclusivity. The manifesto articulates a technopolitical vision for data governance that prioritizes community control over data. We analyze the manif

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Wong, Janis, and Tristan Henderson. "Co-Creating Autonomy: Group Data Protection and Individual Self-determination within a Data Commons." International Journal of Digital Curation 15, no. 1 (2020): 16. http://dx.doi.org/10.2218/ijdc.v15i1.714.

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 Recent privacy scandals such as Cambridge Analytica and the Nightingale Project show that data sharing must be carefully managed and regulated to prevent data misuse. Data protection law, legal frameworks, and technological solutions tend to focus on controller responsibilities as opposed to protecting data subjects from the beginning of the data collection process. Using a case study of how data subjects can be better protected during data curation, we propose that a co-created data commons can protect individual autonomy over personal data through collective curation and rebalance pow

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Yim, Hyung-Jun, Mikyoung Lee, Sa-Kwang Song, Dongmin Seo, and Minhee Cho. "Design and Application of Korea Research Data Commons for Data-Driven Research and Development." Journal of Korean Institute of Intelligent Systems 32, no. 5 (2022): 392–400. http://dx.doi.org/10.5391/jkiis.2022.32.5.392.

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Loomba, Johanna Jean, Glenn S. Wasson, Ravi Kiran Reddy Chamakuri, et al. "The iTHRIV Commons: a cross-institution information and health research data sharing architecture and web application." Journal of the American Medical Informatics Association 29, no. 4 (2021): 631–42. http://dx.doi.org/10.1093/jamia/ocab262.

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Abstract Objective The integrated Translational Health Research Institute of Virginia (iTHRIV) aims to develop an information architecture to support data workflows throughout the research lifecycle for cross-state teams of translational researchers. Materials and Methods The iTHRIV Commons is a cross-state harmonized infrastructure supporting resource discovery, targeted consultations, and research data workflows. As the front end to the iTHRIV Commons, the iTHRIV Research Concierge Portal supports federated login, personalized views, and secure interactions with objects in the ITHRIV Commons

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Dalla Torre, Cristina, Rocco Scolozzi, Elisa Ravazzoli, and Paola Gatto. "Endangered Commons? Modeling the Effects of Demographic Trends Coupled with Admission Rules to Common Property Institutions." Land 13, no. 10 (2024): 1704. http://dx.doi.org/10.3390/land13101704.

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This study investigates the long-term effects of demographic trends and admission rules on common properties in the Province of Trento, Italy, which we refer to as historical commons. Historical commons have evolved into socio-ecological systems over the centuries, meaning that communities governed collectively natural resources and lands essential for community survival. Communities and the admission rules that determine their composition are an important constituting element of historical commons because they have developed local ecological knowledge and practices of sustainable use of natur

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Bühler, Michael Max, Igor Calzada, Isabel Cane, et al. "Unlocking the Power of Digital Commons: Data Cooperatives as a Pathway for Data Sovereign, Innovative and Equitable Digital Communities." Digital 3, no. 3 (2023): 146–71. http://dx.doi.org/10.3390/digital3030011.

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Network effects, economies of scale, and lock-in-effects increasingly lead to a concentration of digital resources and capabilities, hindering the free and equitable development of digital entrepreneurship, new skills, and jobs, especially in small communities and their small and medium-sized enterprises (“SMEs”). To ensure the affordability and accessibility of technologies, promote digital entrepreneurship and community well-being, and protect digital rights, we propose data cooperatives as a vehicle for secure, trusted, and sovereign data exchange. In post-pandemic times, community/SME-led

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Nishikawa, Kai. "How are research data governed at Japanese repositories? A knowledge commons perspective." Aslib Journal of Information Management 72, no. 5 (2020): 837–52. http://dx.doi.org/10.1108/ajim-03-2020-0072.

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PurposeThe purpose of this paper is to survey how research data are governed at repositories in Japan by deductively establishing a governance typology based on the concept of openness in the context of knowledge commons and empirically assessing the conformity of repositories to each type.Design/methodology/approachThe fuzzy-set ideal type analysis (FSITA) was adopted. For data collection, a manual assessment was conducted with all Japanese research data repositories registered on re3data.org.FindingsThe typology constructed in this paper consists of three dimensions: openness to resources (h

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LaPlante, Emily, Bingxing Huo, DR Mani, and Ratna R. Thangudu. "Abstract 7420: Optimizing proteomic data access and analysis in the cloud: Leveraging Terra's integration with the Proteomic Data Commons." Cancer Research 84, no. 6_Supplement (2024): 7420. http://dx.doi.org/10.1158/1538-7445.am2024-7420.

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Abstract The Proteomic Data Commons (PDC) hosts cancer proteomics data with the goal of making this data available to the public to support development of cancer diagnostics, treatment, and progression tracking. As a part of the Cancer Research Data Commons (CRDC), the Terra platform provides a cloud workbench for the PDC data. FireCloud is a Broad Institute project funded by NCI to empower cancer researchers to access data, run analysis tools and collaborate securely in the cloud. It is powered by Terra, a secure, scalable cloud-native platform developed by the Broad Institute, Microsoft, and

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Chou, Austin, Abel Torres-Espín, J. Russell Huie, et al. "Empowering Data Sharing and Analytics through the Open Data Commons for Traumatic Brain Injury Research." Neurotrauma Reports 3, no. 1 (2022): 139–57. http://dx.doi.org/10.1089/neur.2021.0061.

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48

Grossman, Robert L. "Data Lakes, Clouds, and Commons: A Review of Platforms for Analyzing and Sharing Genomic Data." Trends in Genetics 35, no. 3 (2019): 223–34. http://dx.doi.org/10.1016/j.tig.2018.12.006.

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49

van Maanen, Gijs, Charlotte Ducuing, and Tommaso Fia. "Data commons." Internet Policy Review 13, no. 2 (2024). http://dx.doi.org/10.14763/2024.2.1748.

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Wong, Janis, Tristan Henderson, and Kirstie Ball. "Data protection for the common good: Developing a framework for a data protection-focused data commons." Data & Policy 4 (2022). http://dx.doi.org/10.1017/dap.2021.40.

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Abstract:

Abstract In our data-driven society, personal data affecting individuals as data subjects are increasingly being collected and processed by sizeable and international companies. While data protection laws and privacy technologies attempt to limit the impact of data breaches and privacy scandals, they rely on individuals having a detailed understanding of the available recourse, resulting in the responsibilization of data protection. Existing data stewardship frameworks incorporate data-protection-by-design principles but may not include data subjects in the data protection process itself, rely

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