Cited By
View all- Li FWang YBeyan OSchöneck MCaldeira L(2024)Voxel-Wise Medical Image Generalization for Eliminating Distribution ShiftACM Transactions on Knowledge Discovery from Data10.1145/364303418:7(1-16)Online publication date: 19-Jun-2024
Analyzing Distributed Medical Data in FAIR Data Spaces
Authors: 
Mehrshad Jaberansary, Macedo Maia, Yeliz Ucer Yediel, Oya Beyan, Toralf KirstenAuthors Info & Claims
Mehrshad Jaberansary, Macedo Maia, Yeliz Ucer Yediel, Oya Beyan, Toralf KirstenAuthors Info & ClaimsPages 1480 - 1484
Abstract
The exponential growth in data production has led to increasing demand for high-quality data-driven services. Additionally, the benefits of data-driven analysis are vast and have significantly propelled research in many fields. Data sharing benefits scientific advancement, as it promotes transparency, and collaboration, accelerates research and aids in making informed decisions. The European strategy for data aims to create a single data market that ensures Europe’s global competitiveness and data sovereignty. Common European Data Spaces ensure that data from different sources are available in the economy and society, while data providers (e.g., hospitals and scientists) control data access. The National Research Data Infrastructure for Personal Health Data (NFDI4Health) initiative is a prime example of an effort focused on data from clinical trials and public health studies. Collecting and analyzing this data is essential to developing novel therapies, comprehensive care approaches, and preventive measures in modern healthcare systems.
This work describes distributed data analysis services and components that adhere to the FAIR data principles (Findable, Accessible, Interoperable, and Reusable) within the data space environment. We focus on distributed analytics functionality in Gaia-X-based data spaces. Gaia-X offers a trustworthy federation of data infrastructure and service providers for European countries.
References
[1]
2019. ISIC Challenge 2019. Retrieved Feburary 17, 2023 from https://challenge.isic-archive.com/landing/2019
[2]
Oya Beyan, Ananya Choudhury, Johan van Soest, Oliver Kohlbacher, Lukas Zimmermann, Holger Stenzhorn, Md. Rezaul Karim, Michel Dumontier, Stefan Decker, Luiz Olavo Bonino da Silva Santos, and Andre Dekker. 2020. Distributed Analytics on Sensitive Medical Data: The Personal Health Train. Data Intelligence 2, 1-2 (01 2020), 96–107. https://doi.org/10.1162/dint_a_00032
[3]
Edward Curry, Simon Scerri, and Tuomo Tuikka. 2022. Data Spaces: Design, Deployment, and Future Directions. Springer International Publishing, 1–17. https://doi.org/10.1007/978-3-030-98636-0_1
[4]
Yongli Mou, Sascha Welten, Mehrshad Jaberansary, Yeliz Ucer Yediel, Toralf Kirsten, Stefan Decker, and Oya Beyan. 2021. Distributed skin lesion analysis across decentralised data sources. In Public Health and Informatics. IOS Press, 352–356.
[5]
Boris Otto. 2022. The Evolution of Data Spaces. Springer International Publishing, Cham, 3–15. https://doi.org/10.1007/978-3-030-93975-5_1
[6]
Hubert Tardieu. 2022. Role of Gaia-X in the European Data Space Ecosystem. Springer International Publishing, Cham, 41–59. https://doi.org/10.1007/978-3-030-93975-5_4
[7]
Sascha Welten, Laurenz Neumann, Yeliz Ucer Yediel, Luiz Olavo Bonino da Silva Santos, Stefan Decker, and Oya Beyan. 2021. DAMS: A Distributed Analytics Metadata Schema. Data Intelligence 3, 4 (10 2021), 528–547. https://doi.org/10.1162/dint_a_00100 arXiv:https://direct.mit.edu/dint/article-pdf/3/4/528/1968588/dint_a_00100.pdf
[8]
Sascha Martin Welten, Yongli Mou, Laurenz Neumann, Mehrshad Jaberansary, Yeliz Ucer Yediel, Toralf Kirsten, Stefan Josef Decker, and Oya Deniz Beyan. 2022. A Privacy-Preserving Distributed Analytics Platform for Health Care Data. Methods of Information in Medicine 61, S01 (2022), e1–e11. https://doi.org/10.1055/s-0041-1740564
[9]
Mark D. Wilkinson, Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, Jan-Willem Boiten, Luiz Bonino da Silva Santos, Philip E. Bourne, Jildau Bouwman, Anthony J. Brookes, Tim Clark, Mercè Crosas, Ingrid Dillo, Olivier Dumon, Scott Edmunds, Chris T. Evelo, Richard Finkers, Alejandra Gonzalez-Beltran, Alasdair J.G Gray, Paul Groth, Carole Goble, Jeffrey S. Grethe, Jaap Heringa, Peter A.C ’t Hoen, Rob Hooft, Tobias Kuhn, Ruben Kok, Joost Kok, Scott J. Lusher, Maryann E. Martone, Albert Mons, Abel L. Packer, Bengt Persson, Philippe Rocca-Serra, Marco Roos, Rene van Schaik, Susanna-Assunta Sansone, Erik Schultes, Thierry Sengstag, Ted Slater, George Strawn, Morris A. Swertz, Mark Thompson, Johan van der Lei, Erik van Mulligen, Jan Velterop, Andra Waagmeester, Peter Wittenburg, Katherine Wolstencroft, Jun Zhao, and Barend Mons. 2016. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3 (March 2016).
Index Terms
- Analyzing Distributed Medical Data in FAIR Data Spaces
Recommendations
Medical Big Data Warehouse: Architecture and System Design, a Case Study: Improving Healthcare Resources Distribution
The huge increases in medical devices and clinical applications which generate enormous data have raised a big issue in managing, processing, and mining this massive amount of data. Indeed, traditional data warehousing frameworks can not be effective ...
Data Work in Healthcare: Challenges for Patients, Clinicians and Administrators
CSCW '18 Companion: Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social ComputingWith the wide adoption of information infrastructures in healthcare (IIH), citizens and healthcare professionals now carry out intensive "data work' as part of their healthcare and self-management practices. For example, citizens use mobile apps to ...
Sharing medical data vs. health knowledge in chronic illness care
CHI EA '12: CHI '12 Extended Abstracts on Human Factors in Computing SystemsChronic illnesses are becoming more prevalent worldwide breeding an interest in supporting patient care through electronic health information exchange. Through a study of diabetes patients and the specialists in their care network, the challenges ...
Comments
Information & Contributors
Information
Published In
April 2023
1567 pages
ISBN:9781450394192
DOI:10.1145/3543873
Copyright © 2023 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 30 April 2023
Check for updates
Author Tags
Qualifiers
- Short-paper
- Research
- Refereed limited
Funding Sources
Conference
WWW '23
Sponsor:
Acceptance Rates
Overall Acceptance Rate 1,899 of 8,196 submissions, 23%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 134Total Downloads
- Downloads (Last 12 months)76
- Downloads (Last 6 weeks)5
Reflects downloads up to 17 Oct 2024
Other Metrics
Citations
Cited By
View all- Li FWang YBeyan OSchöneck MCaldeira L(2024)Voxel-Wise Medical Image Generalization for Eliminating Distribution ShiftACM Transactions on Knowledge Discovery from Data10.1145/364303418:7(1-16)Online publication date: 19-Jun-2024
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format