Turning Outreach into Infrastructure: Community-Driven Inputs to Improve Data Discovery

For the past 5 years, the PDS has made a substantial effort to improve community outreach and relations using conference outreach presence. Through a combination of approachable, friendly staff, and fun innovative outreach activities, we have achieved this goal and become an organization people look forward to interacting with at community events. Now that this goal has been achieved, we turned our attention to how we can harness this new community engagement to improve the FAIR-ness of the PDS archives.

At EPSC 2025, we piloted an interactive outreach activity designed to collect structured information about researchers’ data practices and foster dialogue on metadata, archival standards, and search behaviors. The PDS Small Bodies Node (SBN) is using this to inform the development of a new discipline  dictionary focused on search/findability.

 

Participants completed a digital form to “Describe Your Data,” selecting scientific disciplines, targets, missions, techniques, and software relevant to their work. Responses were converted into custom stickers to be placed on a wearable badge with the header “My Data Is:” (Fig 1.), creating a thematic experience that encouraged networking and scientific exchange. The form balanced curated options for standardization with free-text input to capture underrepresented domains, generating a feedback loop for improving metadata assumptions and vocabularies.

 

The activity achieved substantial engagement: 422 participants contributed 2,349 items, representing 25% of the 1,659 in-person attendees. Figure 2 and Tables 1-4 show examples of the data collected.  These results demonstrate the effectiveness of interactive outreach for gathering actionable insights, strengthening PDS standards, and promoting FAIR principles.

 

The structured responses collected during this activity provides the initial inputs for enhancing PDS search capabilities. By identifying how scientists describe their data through disciplines, targets, and techniques, we can refine controlled vocabularies, improve metadata indexing, and support higher-level data search in terms that our users use, rather than just relying on observational metadata. This directly advances interoperability across PDS nodes and external archives, enabling users to transition seamlessly between observational and derived data products. These insights will inform future API enhancements and ontology-driven search strategies, ensuring that PDS remains a leader in FAIR-compliant data discovery. We present lessons learned for community-driven metadata development and strategies for scaling this model to other conferences, including LPSC, ACM, and again at EPSC 2026.