The Persistent Identification of Instruments Working Group seeks to explore a community-driven solution for globally unique identification of measuring instruments operated in the sciences.
Measuring instruments, such as sensors used in environmental science, DNA sequencers used in life sciences or laboratory engines used for medical domains, are widespread in most fields of applied sciences. The ability to link an active instrument (instance) with an instrument type and with the broader context in which the instrument operates (including generated data, other instruments and platforms, people and manufacturers, etc.) is critical, especially for automated processing of such contextual information and for the interpretation of generated data.
The identification and description of instrument models and instances is gaining momentum. Several disciplines are using established controlled vocabularies (standardised terms) to identify devices. Advances in Semantic Sensor Web technologies (encodings of sensor descriptions that are machine-readable and interoperable) have resulted in new instrument metadata schemas. Some Persistent Identifiers (PIDs), such as Universally Unique Identifiers (UUIDs) or Digital Object Identifiers (DOIs) are already being utilised.
Our group aims to build on these developments and establish a cross-discipline, operational solution for the unique and lasting identification of measuring instruments actively operated in the sciences.
- Explore the use of a globally unique solution to persistently identify active measuring instruments
- Recommend a metadata profile to describe instruments that harmonises existing identification standards and complements existing metadata schemas
- Explore methodology/technology to register and resolve the new PID
- Operationalise the solution by engaging existing PID infrastructure providers, instrument developers and manufacturers, as well as instrument database providers
Collaborative Notes Link:
The WG collects use cases for persistent identification of instruments, aligns the collected metadata, and develops a metadata schema.
The schema is available on GitHub at https://github.com/rdawg-pidinst/schema and we encourage comments from the community.
So far, we have obtained the following use cases (Last update: March 2019).
- GEOFON by Javier Quinteros (November 2017)
- HZB by Rolf Krahl (November 2017)
- NIF by Veah Tapat et al. (December 2017)
- IREA-CNR by Alessandro Oggioni et al. (January 2018)
- SENSOR.awi.de by Ana Macario et al. (April 2018)
- Marine SWE by Robert Huber et al. (May 2018)
- ORCID by Tom Demeranville (May 2018)
- ICOS Carbon Portal by Claudio D’Onofrio et al. (June 2018)
- BODC by Louise Darroch et al. (July 2018)
- ESO by Dominic Bordelon et al. (August 2018)
- FZJ Central Library (JLSRF) by Claudia Frick (September 2018)
- PANGAEA by Anusuriya Devaraju et al. (September 2018)
- EuroGOOS/PSMSL/GLOSS by Louise Darroch (October 2018)
- LTER-Europe by Alessandro Oggioni et al. (October 2018)
- UK Polar Data Centre by Alex Tate (February 2019)