Q-SPARC: An Interactive Chatbot for Exploring SPARC SCKAN Connectivity with Flatmap Visualization
<ns5:p>Background The SPARC program (SPARC Portal, RRID:SCR_017041; https://sparc.science) aggregates anatomy and connectivity knowledge across species. The SCKAN database (RRID:SCR_026088) provides structured connectivity relationships and an associated Natural Language Interface (NLI). However, the NLI currently supports only single-turn querying, lacks conversational memory, and does not integrate Flatmap visualization. Methods We developed Q-SPARC—a Python-based conversational system that integrates local or cloud-hosted LLMs (default: Qwen2.5-72B with optional GPT-4 support) with semantic retrieval, reranking, and Flatmap visualization. Results Users can submit queries such as “What are the input sources of the heart?” and receive a narrative summary, structured tables, and Flatmap anatomical diagrams. The system supports multi-turn conversational memory, allowing follow-up refinement and context- dependent queries. Conclusions Q-SPARC extends the SPARC ecosystem by enabling conversational exploration of SCKAN connectivity, integrating visualization, and improving usability and FAIRness.</ns5:p>
Authors
- Fangqiang Xu
- Dan Zhang (ORCID: https://orcid.org/0000-0001-8523-7944)
- Yun Gu (ORCID: https://orcid.org/0000-0003-4758-769X)
- Matthew French
- Huayan Zeng (ORCID: https://orcid.org/0009-0008-2289-083X)
Institutions
- Auckland Institute of Studies (NZ)
- University of Auckland (NZ)
- Auckland University of Technology (NZ)
Publication Details
- Journal
- F1000Research
- Published
- 2026-06-18
- DOI
- https://doi.org/10.12688/f1000research.178101.1
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00