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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Q-SPARC: An Interactive Chatbot for Exploring SPARC SCKAN Connectivity with Flatmap Visualization

Fangqiang Xu, Dan Zhang, Yun Gu, Matthew French et al.
F1000Research
Biomedical Text Mining and Ontologies
article

Q-SPARC: An Interactive Chatbot for Exploring SPARC SCKAN Connectivity with Flatmap Visualization

Fangqiang Xu, Dan Zhang, Yun Gu, Matthew French, Huayan Zeng
article en

Abstract

<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>

F1000ResearchVol. 15
Auckland Institute of Studies (NZ), University of Auckland (NZ), Auckland University of Technology (NZ)
Quality Education
Openalex Percentile: Top 10%
Biomedical Text Mining and Ontologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Q-SPARC: An Interactive Chatbot for Exploring SPARC SCKAN Connectivity with Flatmap Visualization — Fangqiang Xu, Dan Zhang, et al. · F1000Research (2026) | TGRS Research Map | TGRS