Resources
The International Generic Sample Number (IGSN ID) is a globally unique and persistent identifier that can be assigned to any material sample resulting from research in any domain. Through a partnership between DataCite and the IGSN Organization (e.V.), DataCite DOI services for registering IGSN IDs are available to all DataCite Members and Consortium Organizations. But…how does an organization actually work with its researchers to create a sample management workflow that incorporates IGSN ID registration?
IGSN Wiki / Documentation
As part of the partnership between the IGSN Organisation and DataCite, IGSN IDs are now registered through DataCite services. Details on how to register and use IGSN IDs can be found on the DataCite support site. Our GitHub site has some additional technical documentation for using IGSN IDs.
FAIR WISH - FAIR Workflows to establish IGSN for Samples in the Helmholtz Association
IGSN resources in the IGSN and DataCite Zenodo community
IGSN Zenodo Community
DataCite Zenodo Community
IGSN-related DataCite blog posts
At this link: DataCite Blog
Research Data Alliance
Addink, W., Damerow, J., Donaldson, M., Edrington, C., Islam, S., Klump, J., et al. (2022). 23 Things Physical Samples (RDA Supporting Outputs). Research Data Alliance. https://doi.org/10.15497/RDA00067
IGSN Publications
Journal Publications
Conze, R., Lorenz, H., Ulbricht, D., Elger, K., & Gorgas, T. (2017). Utilizing the International Geo Sample Number Concept in Continental Scientific Drilling During ICDP Expedition COSC-1. Data Science Journal, 16(1), 1–8. https://doi.org/10.5334/dsj-2017-002
Klump, J., Lehnert, K. A., Ulbricht, D., Devaraju, A., Elger, K., Fleischer, D., et al. (2021). Towards Globally Unique Identification of Physical Samples: Governance and Technical Implementation of the IGSN Global Sample Number. Data Science Journal, 20(33), 1–16. https://doi.org/10.5334/dsj-2021-033
Klump, J., Fils, D., Devaraju, A., Ramdeen, S., Robertson, J. C., Wyborn, L. A. I., & Lehnert, K. A. (2023). Scaling Identifiers and Their Metadata to Gigascale: an Architecture to Tackle the Challenges of Volume and Variety. Data Science Journal, 22(5), 1–17. https://doi.org/10.5334/dsj-2023-005
Nordsiek, S., & Halisch, M. (2024). Making geoscientific lab data FAIR: a conceptual model for a geophysical laboratory database. Geoscientific Instrumentation, Methods and Data Systems, 13(1), 63–73. https://doi.org/10.5194/gi-13-63-2024
Ramdeen, S., Lehnert, K., Klump, J., & Wyborn, L. (2023). International Generic Sample Number. In B. S. Daya Sagar, Q. Cheng, J. McKinley, & F. Agterberg (Eds.), Encyclopedia of Mathematical Geosciences (pp. 656–660). Cham, Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-030-85040-1_162
Conference Papers and Abstracts
Klump, J., Fils, D., Devaraju, A., Ramdeen, S., Robertson, J., Wyborn, L., & Lehnert, K. (2023). Identifying and Describing Billions of Objects: an Architecture to Tackle the Challenges of Volume, Variety, and Variability. In EGU General Assembly 2023 (pp. EGU23-10223). Vienna, Austria: Copernicus Meetings. https://doi.org/10.5194/egusphere-egu23-10223
Klump, J. F., Devaraju, A., Fazio, V., & Golodoniuc, P. (2024). AuScope Sample Catalogue and IGSN Minting Service. In American Geophysical Union Fall Meeting 2023. San Francisco, CA: American Geophysical Union. Retrieved from https://agu.confex.com/agu/fm23/meetingapp.cgi/Paper/1332314
Klump, J., Edmunds, R., & Thomer, A. (2024). From Collection to Citation : The Diverse Actors and PIDs Needed for Comprehensive Material Sample Management. Conference Presentation presented at the PIDFest 2024, Prague, CZ: National Library of Technology. https://doi.org/10.48813/bdzr-e252
Lehnert, K. A., Vinayagamoorthy, S., Djapic, B., & Klump, J. (2006). The Digital Sample: Metadata, Unique Identification, and Links to Data and Publications. EOS, Transactions, American Geophysical Union, 87(52, Fall Meet. Suppl.), Abstract IN53C-07. http://abstractsearch.agu.org/meetings/2006/FM/sections/IN/sessions/IN53C/abstracts/IN53C-07.html
Lehnert, K. A., Klump, J., Ramdeen, S., Elger, K., & Wyborn, L. A. I. (2022). The critical role of unique identification of samples for the geoanalytical data pipeline. In EGU General Assembly 2022. Vienna, Austria: Copernicus Meetings. https://doi.org/10.5194/egusphere-egu22-13317
Ramdeen, S., Lehnert, K. A., Klump, J., & Wyborn, L. (2022). Progressing the global samples community through the new partnership between IGSN and DataCite. In EGU General Assembly 2022. Vienna, Austria: Copernicus Meetings. https://doi.org/10.5194/egusphere-egu22-10897
Wieczorek, M., Brauser, A., Heim, B., Frenzel, S., Baldewein, L., Kleeberg, U., & Elger, K. (2023). FAIR WISH project - developing metadata templates for IGSN Registration for various sample types. In EGU General Assembly 2023 (pp. EGU23-13514). Vienna, Austria: Copernicus Meetings. https://doi.org/10.5194/egusphere-egu23-13514
IGSN 2040
Defining the Future of the IGSN as a Global Persistent Identifier for Material Samples
IGSN 2040 was a project funded by the Alfred P. Sloan Foundation to re-design and mature the existing organization and technical architecture of the IGSN to create a global, scalable, and sustainable technical and organizational infrastructure for persistent unique identifiers (PID) of material samples.
Expected project outcomes:
Establish a solid, executable plan for the future of the IGSN.
Enable new organizations to participate easily and with confidence.
Create outcomes which will be applicable to other PID systems.
The key objectives of the IGSN 2040 project were to develop a strategic plan and a roadmap that will guide the IGSN system in its next chapter.
Lehnert, K., Klump, J., Ramdeen, S., Wyborn, L., & Haak, L. (2021). IGSN 2040 Summary Report: Defining the Future of the IGSN as a Global Persistent Identifier for Material Samples. Zenodo. https://doi.org/10.5281/zenodo.5118289
See Zenodo for presentations and outcomes related to this project.