Lahiru Jayathilake created AIRAVATA-3975:
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Summary: Allocation Research Impact & Analytics Dashboard
Key: AIRAVATA-3975
URL: https://issues.apache.org/jira/browse/AIRAVATA-3975
Project: Airavata
Issue Type: Task
Components: Airavata System, Custos Airavata Integration
Reporter: Lahiru Jayathilake
h2. Summary
Build a research impact tracking pipeline and analytics dashboard for Custos
that connects compute allocations to their research outcomes (publications,
citations) and provides visual analytics on allocation distribution and usage
patterns. This becomes part of the Custos allocation management layer, giving
PIs and administrators visibility into how compute resources translate into
research output.
h2. Problem
HPC centers grant compute allocations to research projects through programs
like ACCESS-CI (Accelerate, Maximize, Explore, Discover) and internal
discretionary pools. These allocations consume significant resources (CPU
hours, GPU hours, storage), but there is limited visibility into the research
outcomes they produce.
PIs and administrators want to understand not just "how many credits were
consumed" but "what did those credits produce?" When a project uses 50,000 GPU
hours, what publications came out of that work? How does resource consumption
correlate with research output across different scientific domains? This kind
of traction data is valuable for reporting, future allocation decisions, and
demonstrating the value of the compute infrastructure.
At the same time, allocation analytics (resource distribution across sites,
comparison by scientific domain, usage patterns by allocation type) are useful
for understanding how resources are being distributed and consumed across the
system.
h2. Description
This project builds two connected components within the Custos allocation
management layer:
1. Research Impact Pipeline (primary focus)
Build a data pipeline that cross-references compute allocations with published
research outcomes:
* Publication discovery: Given an allocation project (PI name, institution,
project title/abstract, field of science), search external publication
repositories to find related publications. Sources to integrate with:
** Semantic Scholar API (free, structured, good coverage)
** Crossref API (DOI-based metadata, citation counts)
** ORCID API (if the PI's ORCID is known, pull their works directly)
** Google Scholar (broad coverage, limited API access)
** ACM Digital Library, IEEE Xplore, or other domain-specific repositories as
applicable
* Matching logic: Design a strategy to link publications to specific
allocations. This is not trivial since publications don't always cite their
compute allocation. Approaches to explore:
** Match by PI name + institution + time window (allocation period)
** Match by keywords from the allocation abstract against publication
titles/abstracts
** Match by acknowledgment text mining (some papers acknowledge allocation
grant numbers)
** Match by ORCID works if the PI's ORCID is linked
* Periodic sync: The pipeline should run periodically (configurable interval)
to discover new publications and update citation counts for previously matched
ones.
* Data model: Store matched publications with metadata (title, authors, venue,
year, DOI, citation count, match confidence, match method) linked to the
allocation project.
2. Allocation Analytics
Build analytics views that visualize allocation data:
* Resource distribution across HPC sites (e.g., which sites are getting the
most CPU, GPU, storage allocations)
* Allocation breakdown by scientific domain / field of science
* Comparison across allocation types (Accelerate vs. Maximize vs. Explore vs.
Discover)
* Top projects by resource allocation
* Trends over time
3. Dashboard UI (React/TypeScript)
Build a dashboard that brings both components together:
* Allocation detail view: When navigating to a specific allocation/project,
show:
** Allocation metadata (PI, institution, field of science, resources granted,
dates)
** Matched publications with citation counts, DOIs, and match confidence
** Resource usage summary (if usage data is available)
* Analytics views:
** Aggregated research impact metrics (total publications, citations across
projects)
** Allocation distribution charts (by site, by domain, by allocation type)
** Visual comparisons (scatter plots, bar charts, radar charts by scientific
domain)
* Role-based views:
** PI view: their own projects, publications, and resource usage
** Admin view: cross-project analytics, research impact overview, resource
distribution
4. Backend API (Go)
* REST endpoints to serve allocation data, publication matches, and analytics
aggregations
* Integration with the ACCESS-CI allocations API
(https://allocations.access-ci.org/) as a data source for project metadata
* Endpoints for triggering and monitoring the publication discovery pipeline
h2. Expected Deliverables
* Research impact pipeline that cross-references allocations with publications
from external repositories (Semantic Scholar, Crossref, ORCID, etc.)
* Publication matching algorithm with configurable strategies and confidence
scoring
* Allocation analytics backend with aggregation queries (by site, domain,
allocation type)
* React/TypeScript dashboard with allocation detail views (including matched
publications) and analytics visualizations
* Go REST API serving allocation data, publication matches, and analytics
* Documentation covering the matching strategy, data sources, and API
specification
h2. Required Skills
* Go (backend API and pipeline)
* React/TypeScript (dashboard UI)
* REST API design and integration with external APIs
* SQL / database modeling
* Data visualization (charting libraries)
* Familiarity with academic publication APIs (Semantic Scholar, Crossref), or
willingness to learn
h2. Resources
* Custos repository: github.com/apache/airavata-custos
* Allocation management module: allocations/ directory in the repository for
the existing ACCESS-CI integration and allocation data model
* ACCESS-CI allocations API: https://allocations.access-ci.org/ provides
current project data including PI, institution, field of science, resources,
and allocation type
* Semantic Scholar API: https://api.semanticscholar.org/ (free, structured
publication search and citation data)
* Crossref API: https://api.crossref.org/ (DOI metadata and citation counts)
* ORCID API: https://info.orcid.org/documentation/ (researcher works and
affiliations)
* Google Scholar: https://scholar.google.com/ (broad coverage, limited API
access)
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