HDRL Staff Strategy Meeting Report

Technical Summary: HDRL Strategy Meeting 2026 Report

Problem Statement
The Heliophysics Digital Resource Library (HDRL), a federation comprising the Heliophysics Data and Model Consortium (HDMC), the Solar Data Analysis Center (SDAC), and the Space Physics Data Facility (SPDF), faces the challenge of aligning its strategic direction with the needs of its diverse stakeholder base. While stakeholders typically include the research community and NASA management, this report identifies a critical gap in understanding the specific perspectives of the HDRL technical workforce (staff and grantees). The organization required a mechanism to leverage this internal expertise to identify strategic gaps, prioritize operational improvements, and define a roadmap for modernizing data delivery, infrastructure, and community engagement in the face of increasing data volumes and evolving scientific requirements.

Methodology
To address this, HDRL convened its first organization-wide strategy meeting on January 21–22, 2026, at the Goddard Space Flight Center. The event was hybrid, hosting 47 registered participants (42 in-person, 5 virtual) drawn from member staff and selected grantees. The methodology followed a structured, participatory design:

1. Information Dissemination: The first day featured over 30 lightning talks covering current infrastructure, community operations, and data management, followed by a session defining strategic drivers (programmatic, policy, and community).
2. Idea Generation: Attendees utilized a Padlet platform to submit strategic topic ideas, focusing on challenges, pain points, and potential solutions.
3. Prioritization via Voting: Participants rated 53 submitted topic ideas on a 1–5 star scale. An "interest score" was calculated for each idea by multiplying the average rating by the number of votes received.
4. Breakout Analysis: Based on interest scores, attendees engaged in three breakout sessions to discuss selected topics. Groups were tasked with refining challenge descriptions, defining impacts, identifying necessary skills, and formulating pitches for adoption.
5. Synthesis: Post-meeting, the authors analyzed the 53 topic ideas and their associated comments. They employed a thematic grouping process, initially assisted by an AI model (ChatGPT) and subsequently refined by human review, to categorize the content into seven distinct themes. Statistical analysis was performed on the voting data to assess theme support and distribution.

Key Contributions
The report synthesizes the collective input of the HDRL workforce into a structured strategic framework. The primary contributions include:

• Thematic Taxonomy: The identification of seven core strategic themes emerging from the discussion:
  1. Metadata, Standards, and Semantics
  2. Discovery, Search, and Recommendation
  3. Modernizing HDRL Users' experience
  4. Modernizing HDRL Staff's experience
  5. Modernized, Scalable, and Dependable Infrastructure for Compute and Storage
  6. Metrics and Impact Assessment
  7. Community Engagement and Sustainability
• Prioritized Action Items: The distillation of the 53 initial ideas into 11 prioritized concepts, which were further synthesized into eight broader strategic areas for action.
• Statistical Validation: A quantitative analysis of the voting data, including the calculation of interest scores, average ratings, and survey margins of error, to validate the level of staff consensus and enthusiasm across different themes.
• Interdependency Mapping: A visual and descriptive mapping of how the prioritized ideas (e.g., "CME Tracker," "Formal Feedback," "Knowledge Graph") interconnect and support one another, highlighting infrastructure dependencies.

Results
The meeting successfully achieved its three primary goals: raising staff awareness, exposing attendees to strategic drivers, and leveraging staff ingenuity to identify solutions.

• Voting Statistics: 324 votes were cast across 53 topic ideas. The average rating was 3.87 stars (±1.00), and the average interest score was 24.08 (±13.41).
• Theme Distribution: Statistical analysis revealed that participants felt equally strongly about all seven themes, with no single theme dominating the others in terms of average rating. However, Theme 6 (Metrics and Impact Assessment) showed a broader, flatter distribution of ratings compared to the "right-leaning" (highly positive) distributions of other themes, suggesting mixed enthusiasm for specific metric-related ideas.
• Top Priorities: The highest-ranked topic ideas included the "CME Tracker" (Interest Score: 57), "Formal Feedback" (51), and "HDRL Workshops" (50). Notably, some high-rated ideas were not selected for breakout discussion due to the logistical constraints of the selection process, while some lower-rated ideas were discussed multiple times, indicating that the "interest score" alone was not a perfect predictor of discussion selection.
• Strategic Areas for Action: The report concludes with eight specific strategic directions:
  1. Improve the mission data delivery process to HDRL.
  2. Formulate and incorporate formal feedback methods (automated and manual).
  3. Develop a balanced outreach and engagement plan, including workshops.
  4. Investigate means to better capture useful metrics.
  5. Streamline and modernize operations using AI/ML approaches.
  6. Prepare solutions for serving big data (cloud and High-End Compute).
  7. Engineer a semantic framework for resource interlinking (HDRL data knowledge graph).
  8. Address gaps in Heliophysics data environment standards via the International Heliophysics Data Environment Alliance (IHDEA).

Significance and Claims
The paper claims that the meeting successfully leveraged the expertise of HDRL staff and grantees to produce a robust, community-driven strategic roadmap. The significance lies in the shift from top-down strategy formulation to a collaborative model that explicitly includes the technical workforce.

The authors modestly note that while the "interest score" was a useful initial filter, the statistical margins of error (ranging from ~25% for top-voted items to nearly 100% for lower-voted items) limit the ability to statistically distinguish between similarly rated ideas. Consequently, the final prioritization relies on a combination of voting data, breakout discussion frequency, and relevance to known challenges.

The report asserts that the identified strategic areas are strongly supported by staff interest and are directly relevant to existing challenges in data curation, delivery, and community engagement. As evidence of immediate impact, the report notes that work has already commenced on several fronts, including discussions with the NCCS for a HelioCloud instance, the implementation of AI tools for publication usage metrics, and the formation of new IHDEA working groups. The authors conclude that the meeting was a valuable use of time and recommend a repeat of the strategy session every two to three years, with logistical improvements to allow for deeper discussion and more flexible scheduling.