Welcome to our first spotlight, where we shine a light on one of the many marvellous people who work with and on FAIRsharing. Today we’re focusing on our Community Curation Programme, where we create a collaborative environment where domain experts are selected to oversee certain areas within the FAIRsharing registry in return for a number of professional benefits such as attribution and visibility for their curation efforts. Detailed information on the programme is available at the FAIRsharing Community Curation homepage.
Lindsey Anderson, a staff scientist at Pacific Northwest National Laboratory (PNNL) is our FAIRsharing community curator for Omics. She has made over 500 record edits with us since the beginning of 2022. Lindsey is one of the early adopters of our Community Curation Programme, and has been instrumental in advancing the programme as well as in updating and enriching records within the Omics domain.
Are you an expert in the standards, databases and policies relevant to your research domain? We are actively seeking community curators across all subject areas (Engineering, Natural Sciences, and Humanities and the Social Sciences). If you are interested in joining our curation community, please read on. Details of joining the programme are at the end of this post, or jump straight to our joining page.
Lindsey has kindly provided the following answers to a few questions we provided. She describes, in her own words, the work she performs and the benefits she gains. Our thanks go to Lindsey for taking the time to both join the programme and provide such wonderful feedback on her curation so far!
What does PNNL gain from the programme, and why did you join?
The Community Curator Programme at FAIRsharing.org is a great working example demonstrating when data communities work FAIR together, they can sustain FAIR innovation together.
Lindsey Anderson
Pacific Northwest National Laboratory (PNNL) currently represents 1 of 17 U.S. Department of Energy (DOE) Office of Science National Laboratories, stewarding 19 designated DOE core science and technology capabilities, and home to over 5,000 scientific experts. PNNL’s collaborative and cross-disciplinary data portfolio, even with just a handful of high-throughput instruments alone, carries an expansive list of sponsor funded programs and community stakeholder requirements. Delivering innovative and “FAIRer data” (data of increased findability, accessibility, interoperability, and reusability) to effectively support policy compliance and data integrity measures, is no small task. Determining which standards, reporting guidelines, vocabularies, tools, and technologies are best suited to meet cross-directorate institutional needs, at a large government laboratory, can be an ambiguous and forensically daunting mission. To fully support innovation and data diversity, relevant to existing FAIR data community developments, PNNL domain expert curation efforts seek to implement and expand on existing best practices to ensure data quality with integrity through active practice, vigilance, and interdisciplinary teamwork. As a team of PNNL scientists, the research we do and the data we share enhances lives. Siloed efforts to enhance data integrity without diversity or inclusion will only serve to support a zero-sum game. The Community Curator Programme at FAIRsharing.org is a great working example demonstrating when data communities work FAIR together, they can sustain FAIR innovation together (however it may apply to each subject/domain or institution).
Joining allowed me to access and contribute to ongoing data standard developments and advancements most relevant to my field of study and research community of practice.
Lindsey Anderson
FAIRsharing.org is an actively curated systems knowledge resource that promotes the value of FAIR adoption and educational awareness across a large variety of subject domain data standards, repositories, and policies linking communities of discipline. As a scientist and
metadata integration engineer, creating policy compliant standards connections across data objects, data types, data operations (acquisition and informatics), and structured data formats is an essential part of harmonizing linked open data lifecycles for integration and reuse. Creating sustainable solutions to common data-driven challenges requires building trusted ecosystem partnerships (both internal and external to our institution). As an omics subject matter expert, joining the FAIRsharing Community Curator Programme was both an opportunity to enhance my scientific project FAIR curation abilities and to contribute to developer invested resources serving a greater data inclusive scientific audience. Here at PNNL we value collaborative partnerships. As a researcher, my focus is on bridging the gaps between research domain communities of practice and open systems knowledge experts, where shared and diverse perspectives work in unison to bring us closer towards a future of a cohesive open science research adoption. The FAIRsharing Community Programme is a great cross-organizational collaboration supporting both open science and domain expert global FAIR endeavors. Joining allowed me to access and contribute to ongoing data standard developments and advancements most relevant to my field of study and research community of practice.
What are your thoughts on cost vs benefit of the programme?
Being able to leverage trusted curated resources through FAIRsharing with technological flexibility provides a maximal return on investment (both in time and effort), providing a seamless end-user experience for continued adoption.
Lindsey Anderson
As a Scientist at PNNL I am a data producer, creator, consumer, and curator disseminating various large-scale integrated data types, vocabularies, and formats across a breadth of subject domain investigations (unbiased to taxonomy). Within one of my roles as a research project data asset manager, I routinely aggregate and integrate large amounts of complex omics data and relational metadata. By the time I am ready to put a DOI bow on a data package for delivery, I run through a series of data quality and compliance checklists, that would be without a doubt longer than Santa’s Xmas list without the ability to automate validations. Research data management and sharing activities, aka the magic behind wrangling the “data cats,” is a logistically labor-intensive role. Being able to provide access to actively curated FAIRsharing citation record APIs automation approaches for linked open data metadata standard supplementation can help alleviate some of pain points often experienced by data stewardship roles throughout the planning and dissemination process. This is where the cost/efficiency balance of early adoption curation effort may pay off for many. For diverse communities working with multiple datatypes and stakeholder sharing requirements, it can be a heavy upfront lift to identify and cross-link policy standards without a machine-actionable approach to both query and modify/update data standards simultaneously. Being able to leverage trusted curated resources through FAIRsharing with technological flexibility provides a maximal return on investment (both in time and effort), providing a seamless end-user experience for continued adoption.
How have you personally found the experience?
Overall, the curation experience has been fun and frictionless. The skills gained throughout my activities continue to provide critical insights for advancing existing institutional data asset forecasting and data preparedness mechanisms in supporting the many elements of FAIR.
Lindsey Anderson
The most rewarding experience thus far as an early adopter is knowing that with each new record addition or curated effort, I’m able to reach an even larger and more diverse FAIR landscape of researchers from all backgrounds and connect them to a stable and accessible trustworthy knowledgebase (I can trust the resource will live on). As an early adopter, having the ability to create/share/update record resources that apply across directorate science with a beneficial return to the overarching research community, is an easy buy-in for me. My personal experience as an early adopter in the FAIRsharing Community Curator Programme has been very rewarding on many levels. In addition to an open science infrastructure, the Programme itself promotes expert teaming, tractable curator attribution (ORCID), and encourages feedback on new embedded development features operating behind the seamless framework the FAIRsharing platform provides. During my curation time I have been able to remain current with ongoing and developing FAIR implementations of both domain and generalist scientific standards. Another indirect advantage of participation in community curation is an enhanced aptitude for cross-domain standard retention, increasing my ability to easily expand from current record standards, formats, and vocabularies in identifying and filling any gaps I may have in my own research data lifecycle procedures. Overall, the curation experience has been fun and frictionless. The skills gained throughout my activities continue to provide critical insights for advancing existing institutional data asset forecasting and data preparedness mechanisms in supporting the many elements of FAIR.
Would you recommend it?
I see the Curator Programme as being an outlet to support national and international FAIR data outreach in advocating the use and reuse of community-driven best practices.
Lindsey Anderson
FAIRsharing leverages crowdsourced scientific curation to promote trustworthy, consistent, and efficient ways to update important metadata about standards in real-time using DOI citation flexibility capturing a catalog of knowledge for reuse. The FAIRsharing Community Curator Programme provides a comprehensive opportunity for those looking to invest in existing knowledgeable FAIR resources to share their own work in support of both open science and domain communities seeking sustainable record standards for an inclusively larger stakeholder audience. FAIRsharing continues to preserve ongoing FAIR method and technological developments (both human-readable and machine-readable) as a stable resource for adoption, where expert curation efforts can strengthen the service provided. The Curator Programme and the FAIRsharing platform are great opportunities for researchers and digital data communities to identify and advance educational tools to comply with anticipated data sharing mandates. I see the Curator Programme as being an outlet to support national and international FAIR data outreach in advocating the use and reuse of community-driven best practices.
How do I get started?
We are looking for balanced representation across all disciplines, although we are particularly interested in applicants from the Humanities, Social Science, Engineering, and Physics. As a FAIRsharing community curator, you can help us help your community be more accurately and comprehensively represented with us. And in return, we have a lot to offer you.
Please read more about joining the programme, or go directly to this form to let us know you’re interested, and get in touch with us via email or Twitter if you have any questions. We’ll be in touch and, if successful, we’ll get you set up with the proper roles.
