The UK's Joint Information Systems Committee (JISC) started a large-scale investigation into a national persistent identifier research strategy back in 2019, which included the development of a PID roadmap for open access to UK research, and more recently, a vision of PID-optimised research workflows. This showcases just how integral PIDs are to the evolving conversation on open science and reproducibility, and that this conversation is happening now!
While DOIs have been normalized for citable data and publications, the lack of PIDs for samples, temporary data, and referable data continues to be an issue. Ultimately, data should be discoverable, trusted, publicly accessible and persistent, and unambiguously and certainly identified. Persistent Identifiers can contribute to the fulfilment of all these requirements.
What is more, PIDs are a core element of open research as they can be used to locate, identify, and share information about digital objects. They can aid in data re-analysis, provide context for data, and reveal correlations between data and associated metadata.
That is why we are incredibly excited to be adding extensive support for PIDs to the RSpace digital research platform!
PID workflow within RSpace
On the 25th of January 2023, the new NIH policy on data management and sharing will come into effect in the US. Under this policy, all NIH grant applications that collect data will be required to submit a data management and sharing plan (DMSP) with their application.
Data Management Plans contain details on how the scientific data and metadata will be handled during the course of the grant: how will the raw data be shared and into what open repositories will it be deposited, what tools will be used for its analysis, and whether there are any points of consideration when it comes to distributing this data openly. You can learn more on NIH's Scientific Data Sharing website.
This policy indicates a massive culture change in grant applications and research practises, with a focus on FAIR principles and open sharing, and is the biggest NIH policy change in over a decade.
Thanks to RSpace's flexibility and rich ecosystem of integrations that support FAIR data principles, it is perfectly placed to support institutions with this transition.
We're excited to be taking part in various initiatives to increase PID usage and improve research workflows. By integrating RSpace with PID tools, samples will be able to support a variety of widely used identifiers, and experiments in the ELN will benefit from a similar upgrade.
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We are currently partnering with DataCite to provide support for the adoption, implementation, and utilization of International Generic Sample Numbers (IGSNs) and DOIs. Stay tuned for more information on IGSN ID use cases and incorporation into sample workflows, best practices, and more!
ORCID (Open Researcher and Contributor ID) provides a unique digital identifier to researchers, ensuring you get recognition for all of your contributions. In addition, by integrating ORCID into your workflow, your research and professional activities are automatically linked together.
The RSpace ↔ ORCID integration makes it easy for users to associate their research activities and outputs originating from RSpace with their ORCID ID, enabling compliance and increased visibility, reproducibility, and trust. What is more, the ORCID ID is included in the metadata of RSpace dataset exports to Dataverse and Figshare, as well as archive bundles, further increasing traceability.
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We are in conversation with the team developing Research Activity Identifier (RAiD), on how RSpace can support RAiD identifiers. The identifier service is under the auspices of Australian Research Data Commons (ARDC), with the goal of providing researchers and institutions with a way to identify research projects and their metadata, such as researchers involved, funders, outputs, and tools used for the project. RAiD will be delivered by ARDC, SURF in Europe, and various other organisations in their respective locations.
The Research Organization Registry (ROR) IDs enable persistent and unambiguous identification of research organisations, in order to reliably connect those organisations to researchers and research outputs. We are planning to incorporate support for RORs to enhance our PIDs offering.
PIDINST is a working group in the Research Data Alliance (RDA) that is developing a community-driven solution to uniquely identify measuring instruments used in research. Since RSpace Inventory can be used to record the location and properties of lab instruments, we are excited by the prospect of an integration with PIDINST.
You can hear more of our thoughts on PIDs for instruments by listening to our recap of the 1st FAIR Digital Objects Forum over at the FAIR Data Podcast:
In order to supercharge the benefits of using PIDs, we're focused on ensuring RSpace can integrate with data management software, so that managing and transferring metadata and data is streamlined and painless, by ensuring data remains structured and automating workflows is possible.
iRODS is an open-source data management software that virtualizes where data is stored, making links to resources more robust, and enabling access to data no matter where it is stored.
The RSpace ↔ iRODS integration provides methods to connect to an iRODS iCAT instance, and files are accessed and linked to in the same way as other file systems. This means that you don't need to worry about your links getting broken inside of RSpace, even if the resources are moved around on the file system.
We're also exploring the development of a deeper integration, that will fully leverage iRODS' metadata management capabilities.
FAIMS (Field Acquired Information Management System) was originally developed as a tool for archaeologists, and has since been adopted by researchers from a range of diverse fields. It provides researchers with a tool for offline data capture in a FAIR-compliant manner, and with useful features such as automatic sync and linked vocabularies, it is quickly becoming an indispensable tool for field research.
The RSpace ↔ FAIMS integration will enable researchers to import data collected using FAIMS directly into RSpace where it can be used to automatically populate sample data and metadata. What is more, it will be possible to leverage RSpace's integration with DataCite to ensure that samples imported from FAIMS will retain their IGSNs in RSpace as native metadata fields.
✔ The RSpace ↔ OMERO integration enables researchers to access their microscopy images and their associated metadata within RSpace, and directly link to images stored in OMERO:
The Research Data Alliance (RDA) is a global organization with over 12,800 members from 148 countries, and is built on principles that include openness, inclusivity, and transparency. Rory Macneil, CEO of Research Space, will serve as part of the Working with PIDs in Tools Interest Group which aims to provide:
✔ A place to address interoperability between tools/e-infrastructures, leveraging PID and metadata infrastructure
✔ A platform for research-supporting service providers and PID/open infrastructure organizations to outline use cases, explore challenges, and pool resources to provide reference and guidance to chart ways forward
✔ A forum for dissecting the interoperability challenges through discussion of concrete case studies involving application of PIDs to tools in multiple communities of practice
RSpace, in partnership with DataCite, have won a grant offered by the European Open Science Cloud (EOSC) and the Research Data Alliance (RDA) to investigate how interoperability between research tools can support PID workflows.
✔ The project will examine how DataCite DOIs and DataCite IGSNs can be integrated into RSpace ELN & Inventory as part of the research process
✔ Then, a working integration with DataCite IGSNs will enable identifying how to best approach the specification and development phase of an integration with PIDs
✔ A set of general guidelines and suggestions for incorporation of PIDs into research tools to enhance interoperability will be presented as a concluding project output
Sample metadata management within Inventory is both flexible and powerful:
✔ Users can export sample metadata from a database such as GenBank, or from Excel documents used in the lab, and directly import the metadata into RSpace. This automatically creates samples and corresponding sample templates within the Inventory system, based on the metadata structure
✔ With the help of sample templates, users can enable automatic population of metadata fields for samples that share a common set of fields, saving time and making the process of associating metadata with samples much easier
✔ Lists of Materials and hierarchical container view make it even easier to sort and work with large volumes of samples
At RSpace, 2023 is shaping itself as the "Year of Metadata", and we couldn't be more excited, as we are dedicated to advancing Open Science and FAIR initiatives. Alongside developing new metadata management solutions, we will attempt to tackle issues such as the lack of interoperability that detracts from research workflows, while pushing the envelope in terms of capabilities, features, and integrations.
Find out more about the work we're doing around Open Science:
On the 25th of January 2023, the new NIH policy on data management and sharing will come into effect in the US. Under this policy, all NIH grant applications that collect data will be required to submit a data management and sharing plan (DMSP) with their application.
Data Management Plans contain details on how the scientific data and metadata will be handled during the course of the grant: how will the raw data be shared and into what open repositories will it be deposited, what tools will be used for its analysis, and whether there are any points of consideration when it comes to distributing this data openly. You can learn more on NIH's Scientific Data Sharing website.
This policy indicates a massive culture change in grant applications and research practises, with a focus on FAIR principles and open sharing, and is the biggest NIH policy change in over a decade.
Thanks to RSpace's flexibility and rich ecosystem of integrations that support FAIR data principles, it is perfectly placed to support institutions with this transition.