publication . Conference object . Preprint . 2018

How FAIR Can you Get? Image Retrieval as a Use Case to Calculate FAIR Metrics

Weber, Tobias; Kranzlmüller, Dieter;
Open Access
  • Published: 09 Oct 2018
  • Publisher: IEEE
Abstract
A large number of services for research data management strive to adhere to the FAIR guiding principles for scientific data management and stewardship. To evaluate these services and to indicate possible improvements, use-case-centric metrics are needed as an addendum to existing metric frameworks. The retrieval of spatially and temporally annotated images can exemplify such a use case. The prototypical implementation indicates that currently no research data repository achieves the full score. Suggestions on how to increase the score include automatic annotation based on the metadata inside the image file and support for content negotiation to retrieve the imag...
Subjects
free text keywords: Information retrieval, Computer science, Information repository, Metadata, Image file formats, computer.file_format, computer, Content negotiation, Image retrieval, Data mining, computer.software_genre, Data management, business.industry, business, Data as a service, Data integration, Computer Science - Computers and Society
Related Organizations
31 references, page 1 of 3

[1] P. Ayris, J. Berthou, R. Bruce, S. Lindstaedt, A. Monreale, B. Mons, Y. Murayama, C. So¨ derga˚rd, K. Tochtermann, and R. Wilkinson, “Realising the european open science cloud,” First report and recommendations of the Commission High Level Expert Group on the European Open Science Cloud, 2016.

[2] L. Federer, “Research data management in the age of big data: Roles and opportunities for librarians,” Information Services & Use, vol. 36, no. 1-2, pp. 35-43, 2016. [OpenAIRE]

[3] M. D. Wilkinson, M. Dumontier, I. J. Aalbersberg, G. Appleton, M. Axton, A. Baak, N. Blomberg, J.-W. Boiten, L. B. da Silva Santos, P. E. Bourne et al., “The FAIR Guiding Principles for scientific data management and stewardship,” Scientific data, vol. 3, 2016.

[4] S. Cox and J. Yu, “ OzNome 5-start Tool: A Rating System for making data FAIR and Trustable (presentation given at the 2017 eResearch Australasia Conference),” Oct. 2017. [Online]. Available: https://conference.eresearch.edu.au/wp-content/uploads/2017/ 07/Simon-Cox.pdf

[5] M. D. Wilkinson, S.-A. Sansone, E. Schultes, P. Doorn, L. O. Bonino da Silva Santos, and M. Dumontier, “A design framework and exemplar metrics for fairness,” bioRxiv, 2017. [Online]. Available: https://www.biorxiv.org/content/early/2017/12/01/225490

[6] M. Wilkinson, L. O. Bonino, N. Nichols, and K. Leinweber, “FAIRMetrics/Metrics: Proposed FAIR Metrics and results of the Metrics evaluation questionnaire,” Mar. 2018. [Online]. Available: https://doi.org/10.5281/zenodo.1205235

[7] J. Boehmer, A. Dunning, and M. de Smaele, Are the FAIR Data Principles fair?, 1 2017.

[8] --, “Evaluation of data repositories based on the FAIR Principles for IDCC 2017 practice paper,” http://dx.doi.org/10.4121/uuid: 5146dd06-98e4-426c-9ae5-dc8fa65c549f.

[9] M. D. Wilkinson, R. Verborgh, L. O. Bonino da Silva Santos, T. Clark, M. A. Swertz, F. D. Kelpin, A. J. Gray, E. A. Schultes, E. M. van Mulligen, P. Ciccarese, A. Kuzniar, A. Gavai, M. Thompson, R. Kaliyaperumal, J. T. Bolleman, and M. Dumontier, “Interoperability and fairness through a novel combination of web technologies,” PeerJ Computer Science, vol. 3, p. e110, Apr. 2017. [Online]. Available: https://doi.org/10.7717/peerj-cs.110

[10] Members of the RDA Research Data Repository Interoperability Working Group, “Research data repository interoperability primer,” jun 2017, This document is a Research Data Alliance Supporting Output. [Online]. Available: https://doi.org/10.15497/RDA00020

[11] K. Gregory, P. Groth, H. Cousijn, A. Scharnhorst, and S. Wyatt, “Searching data: A review of observational data retrieval practices,” arXiv preprint arXiv:1707.06937, 2017.

[12] R. Devarakonda, G. Palanisamy, J. M. Green, and B. E. Wilson, “Data sharing and retrieval using OAI-PMH,” Earth Science Informatics, vol. 4, no. 1, pp. 1-5, 2011.

[13] H. v. d. Sompel, M. L. Nelson, C. Lagoze, and S. Warner, “Resource harvesting within the OAI-PMH framework,” D-Lib Magazine; 2004 [10] 12, 2004. [Online]. Available: http://www.sciencedirect.com/ science/article/pii/S0164121214002040

[14] M. Kindling, H. Pampel, S. van de Sandt, J. R u¨cknagel, P. Vierkant, G. Kloska, M. Witt, P. Schirmbacher, R. Bertelmann, and F. Scholze, “The Landscape of Research Data Repositories in 2015: A re3data analysis,” D-Lib Magazine, vol. 23, no. 3/4, 2017. [Online]. Available: http://www.dlib.org/dlib/march17/kindling/03kindling.html

[15] H. Jagadish, J. Gehrke, A. Labrinidis, Y. Papakonstantinou, J. M. Patel, R. Ramakrishnan, and C. Shahabi, “Big data and its technical challenges,” Communications of the ACM, vol. 57, no. 7, pp. 86-94, 2014. [OpenAIRE]

31 references, page 1 of 3
Abstract
A large number of services for research data management strive to adhere to the FAIR guiding principles for scientific data management and stewardship. To evaluate these services and to indicate possible improvements, use-case-centric metrics are needed as an addendum to existing metric frameworks. The retrieval of spatially and temporally annotated images can exemplify such a use case. The prototypical implementation indicates that currently no research data repository achieves the full score. Suggestions on how to increase the score include automatic annotation based on the metadata inside the image file and support for content negotiation to retrieve the imag...
Subjects
free text keywords: Information retrieval, Computer science, Information repository, Metadata, Image file formats, computer.file_format, computer, Content negotiation, Image retrieval, Data mining, computer.software_genre, Data management, business.industry, business, Data as a service, Data integration, Computer Science - Computers and Society
Related Organizations
31 references, page 1 of 3

[1] P. Ayris, J. Berthou, R. Bruce, S. Lindstaedt, A. Monreale, B. Mons, Y. Murayama, C. So¨ derga˚rd, K. Tochtermann, and R. Wilkinson, “Realising the european open science cloud,” First report and recommendations of the Commission High Level Expert Group on the European Open Science Cloud, 2016.

[2] L. Federer, “Research data management in the age of big data: Roles and opportunities for librarians,” Information Services & Use, vol. 36, no. 1-2, pp. 35-43, 2016. [OpenAIRE]

[3] M. D. Wilkinson, M. Dumontier, I. J. Aalbersberg, G. Appleton, M. Axton, A. Baak, N. Blomberg, J.-W. Boiten, L. B. da Silva Santos, P. E. Bourne et al., “The FAIR Guiding Principles for scientific data management and stewardship,” Scientific data, vol. 3, 2016.

[4] S. Cox and J. Yu, “ OzNome 5-start Tool: A Rating System for making data FAIR and Trustable (presentation given at the 2017 eResearch Australasia Conference),” Oct. 2017. [Online]. Available: https://conference.eresearch.edu.au/wp-content/uploads/2017/ 07/Simon-Cox.pdf

[5] M. D. Wilkinson, S.-A. Sansone, E. Schultes, P. Doorn, L. O. Bonino da Silva Santos, and M. Dumontier, “A design framework and exemplar metrics for fairness,” bioRxiv, 2017. [Online]. Available: https://www.biorxiv.org/content/early/2017/12/01/225490

[6] M. Wilkinson, L. O. Bonino, N. Nichols, and K. Leinweber, “FAIRMetrics/Metrics: Proposed FAIR Metrics and results of the Metrics evaluation questionnaire,” Mar. 2018. [Online]. Available: https://doi.org/10.5281/zenodo.1205235

[7] J. Boehmer, A. Dunning, and M. de Smaele, Are the FAIR Data Principles fair?, 1 2017.

[8] --, “Evaluation of data repositories based on the FAIR Principles for IDCC 2017 practice paper,” http://dx.doi.org/10.4121/uuid: 5146dd06-98e4-426c-9ae5-dc8fa65c549f.

[9] M. D. Wilkinson, R. Verborgh, L. O. Bonino da Silva Santos, T. Clark, M. A. Swertz, F. D. Kelpin, A. J. Gray, E. A. Schultes, E. M. van Mulligen, P. Ciccarese, A. Kuzniar, A. Gavai, M. Thompson, R. Kaliyaperumal, J. T. Bolleman, and M. Dumontier, “Interoperability and fairness through a novel combination of web technologies,” PeerJ Computer Science, vol. 3, p. e110, Apr. 2017. [Online]. Available: https://doi.org/10.7717/peerj-cs.110

[10] Members of the RDA Research Data Repository Interoperability Working Group, “Research data repository interoperability primer,” jun 2017, This document is a Research Data Alliance Supporting Output. [Online]. Available: https://doi.org/10.15497/RDA00020

[11] K. Gregory, P. Groth, H. Cousijn, A. Scharnhorst, and S. Wyatt, “Searching data: A review of observational data retrieval practices,” arXiv preprint arXiv:1707.06937, 2017.

[12] R. Devarakonda, G. Palanisamy, J. M. Green, and B. E. Wilson, “Data sharing and retrieval using OAI-PMH,” Earth Science Informatics, vol. 4, no. 1, pp. 1-5, 2011.

[13] H. v. d. Sompel, M. L. Nelson, C. Lagoze, and S. Warner, “Resource harvesting within the OAI-PMH framework,” D-Lib Magazine; 2004 [10] 12, 2004. [Online]. Available: http://www.sciencedirect.com/ science/article/pii/S0164121214002040

[14] M. Kindling, H. Pampel, S. van de Sandt, J. R u¨cknagel, P. Vierkant, G. Kloska, M. Witt, P. Schirmbacher, R. Bertelmann, and F. Scholze, “The Landscape of Research Data Repositories in 2015: A re3data analysis,” D-Lib Magazine, vol. 23, no. 3/4, 2017. [Online]. Available: http://www.dlib.org/dlib/march17/kindling/03kindling.html

[15] H. Jagadish, J. Gehrke, A. Labrinidis, Y. Papakonstantinou, J. M. Patel, R. Ramakrishnan, and C. Shahabi, “Big data and its technical challenges,” Communications of the ACM, vol. 57, no. 7, pp. 86-94, 2014. [OpenAIRE]

31 references, page 1 of 3
Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue
publication . Conference object . Preprint . 2018

How FAIR Can you Get? Image Retrieval as a Use Case to Calculate FAIR Metrics

Weber, Tobias; Kranzlmüller, Dieter;