{"schema_version":"1.10","project":{"id":"research-atlas","slug":"atlas","title":"Research Atlas: Designing a visual search tool for interdisciplinary research","card":{"title":"Research Atlas","deliverable":"Independently researched, designed and built a visual research-navigation tool.","outcomes":"Users valued finding papers they would not have thought to search for.","outcomeLabel":"Evaluation"},"seo":{"title":"Research Atlas","description":"How I designed and built a graph-based research tool for exploring unfamiliar academic domains and finding unexpected connections."},"canonical_url":"https://laurence-peberdy.com/w/atlas","markdown_url":"https://laurence-peberdy.com/w/atlas.md","project_context":{"type":"academic_project","name":"Master's capstone","institution":{"name":"London Interdisciplinary School","url":"https://www.lis.ac.uk"}},"project_date":{"precision":"year","value":"2025"},"published":"2026-08-05","updated":"2026-09-06","role":["Designer","Engineer"],"responsibility_summary":"I independently researched, designed and built Research Atlas as my Master's capstone at the London Interdisciplinary School.","description":"Entering a field is difficult before you know its terminology. I independently built and evaluated a visual tool for finding the topics, papers and relationships that help establish that context.","summary":["A researcher entering an unfamiliar field often starts with only a rough question. Conventional search immediately asks for keywords, but the useful keywords, authors and concepts are often exactly what the researcher is trying to discover.","I built Research Atlas to start from that rough question, retrieve relevant papers, and show the topics and relationships between them. The point is to help a researcher learn what to search for next, not just rank a list of papers."],"problem":"**Search assumes you already know the language of the field.** Effective queries depend on terms users may still be trying to discover. **A ranked list hides the shape of the literature.** Long result lists make it hard to see clusters, relationships or how papers connect. **Useful work can sit outside the discipline where the search starts.** Relevant papers may use different terminology or belong to another field. **The reason a result appears is hard to see.** Conventional ranking gives users little visibility into the relationships behind a result. **Understanding builds across sessions.** Researchers need to keep useful papers, topics and maps rather than restart each time.","constraints":["The product also has three hard limits:","**It was a solo capstone.** The scope had to fit research, product design, engineering and evaluation into one project.","**Research Atlas depends on OpenAlex.** It can organise and relate the works and topics OpenAlex exposes, but cannot control the source's coverage.","**The graph has to stay readable.** Adding works can reveal useful connections and add noise at the same time, so broad maps are capped at about 200 works and Analysis at about 100 per topic."],"hypotheses":["If the tool turns a rough question into a visible map of papers and topics, reveals relationships progressively, and saves useful connections, users should find unfamiliar fields easier to navigate and discover work they would not have thought to search for."],"interventions":["I tested the relevance of OpenAlex search results using 30 queries across different subject areas. Those checks helped me decide how much material the maps could show before useful connections were lost in noise: about 200 works for broad exploration and 100 per topic in the more focused Analysis flow.","I built the application with Next.js. Neo4j stores the network of papers and topics; Supabase handles accounts and saved content; D3 draws the maps; and Vercel hosts the application."],"technologies":["Next.js","D3","OpenAlex","Neo4j","Supabase","Vercel"],"competencies_demonstrated":["Independent research-to-product design","Graph-based information visualisation","Full-stack engineering across a graph, relational, and search data layer"],"outcomes":["research-atlas-user-discovery","research-atlas-visits","research-atlas-real-experience-score"],"case_study":{"id":"research-atlas","title":"Research Atlas: Designing a visual search tool for interdisciplinary research","card":{"title":"Research Atlas","deliverable":"Independently researched, designed and built a visual research-navigation tool.","outcomes":"Users valued finding papers they would not have thought to search for.","outcomeLabel":"Evaluation"},"seo":{"title":"Research Atlas","description":"How I designed and built a graph-based research tool for exploring unfamiliar academic domains and finding unexpected connections."},"projectContext":{"type":"academic_project","name":"Master's capstone","institution":{"name":"London Interdisciplinary School","url":"https://www.lis.ac.uk"}},"projectDate":{"precision":"year","value":"2025"},"published":"2026-08-05","updated":"2026-09-06","blurb":"Entering a field is difficult before you know its terminology. I independently built and evaluated a visual tool for finding the topics, papers and relationships that help establish that context.","role":["Designer","Engineer"],"responsibilitySummary":"I independently researched, designed and built Research Atlas as my Master's capstone at the London Interdisciplinary School.","decision":"Represent relationships between topics and papers, rather than produce another ranked list of search results.","summary":["A researcher entering an unfamiliar field often starts with only a rough question. Conventional search immediately asks for keywords, but the useful keywords, authors and concepts are often exactly what the researcher is trying to discover.","I built Research Atlas to start from that rough question, retrieve relevant papers, and show the topics and relationships between them. The point is to help a researcher learn what to search for next, not just rank a list of papers."],"heroImage":{"src":"/images/research-atlas.png","alt":"Research Atlas displaying an interactive map of academic topics and connected works.","caption":"A map of academic topics and the works connecting them."},"problem":{"intro":[],"items":["**Search assumes you already know the language of the field.** Effective queries depend on terms users may still be trying to discover.","**A ranked list hides the shape of the literature.** Long result lists make it hard to see clusters, relationships or how papers connect.","**Useful work can sit outside the discipline where the search starts.** Relevant papers may use different terminology or belong to another field.","**The reason a result appears is hard to see.** Conventional ranking gives users little visibility into the relationships behind a result.","**Understanding builds across sessions.** Researchers need to keep useful papers, topics and maps rather than restart each time."]},"constraints":{"intro":["The product also has three hard limits:"],"items":["**It was a solo capstone.** The scope had to fit research, product design, engineering and evaluation into one project.","**Research Atlas depends on OpenAlex.** It can organise and relate the works and topics OpenAlex exposes, but cannot control the source's coverage.","**The graph has to stay readable.** Adding works can reveal useful connections and add noise at the same time, so broad maps are capped at about 200 works and Analysis at about 100 per topic."]},"hypotheses":{"intro":["If the tool turns a rough question into a visible map of papers and topics, reveals relationships progressively, and saves useful connections, users should find unfamiliar fields easier to navigate and discover work they would not have thought to search for."],"items":[]},"interventions":{"intro":["I tested the relevance of OpenAlex search results using 30 queries across different subject areas. Those checks helped me decide how much material the maps could show before useful connections were lost in noise: about 200 works for broad exploration and 100 per topic in the more focused Analysis flow.","I built the application with Next.js. Neo4j stores the network of papers and topics; Supabase handles accounts and saved content; D3 draws the maps; and Vercel hosts the application."],"items":[]},"walkthrough":{"intro":["The product has three workflows:"],"items":[],"groups":[{"heading":"01 — Search from a question","intro":["Start with a keyword or phrase. The Search flow retrieves relevant works and maps the topics and relationships within them, providing a view beyond a ranked list."],"items":[]},{"heading":"02 — Analyse a paper","intro":["Start with a paper's title and abstract. The Analysis flow identifies its core topics and surfaces related research around each one."],"items":[]},{"heading":"03 — Keep useful connections","intro":["The Archive saves works, topics and maps for later sessions."],"items":[]}]},"technologies":["Next.js","D3","OpenAlex","Neo4j","Supabase","Vercel"],"competenciesDemonstrated":["Independent research-to-product design","Graph-based information visualisation","Full-stack engineering across a graph, relational, and search data layer"],"links":[{"label":"Open Research Atlas","href":"https://www.researchatlas.app"}],"outcomes":{"intro":["I evaluated the tool with an academically oriented group and recorded usage and performance over a 30-day period."],"items":[{"id":"research-atlas-user-discovery","kind":"qualitative_outcome","claim":"Structured feedback repeatedly identified **unexpected discovery** as the strongest source of value.","measurement":{"source_type":"user_research","status":"author_reported"}},{"id":"research-atlas-visits","kind":"measured_outcome","claim":"The application recorded **115 visits**.","metric":"visits","value":{"value":115,"unit":"visit"},"measurement":{"source_type":"product_analytics","status":"author_reported","comparison_period":"30-day evaluation period"}},{"id":"research-atlas-real-experience-score","kind":"measured_outcome","claim":"Vercel Speed Insights reported a **96/100 Real Experience Score**.","metric":"vercel_real_experience_score","value":{"value":96,"unit":"/100"},"measurement":{"source_type":"product_analytics","status":"author_reported","comparison_period":"30-day evaluation period"}}],"outro":["Users described finding connected research areas and papers they would not have thought to explore.","The evaluation also highlighted areas to improve: map readability, relevance controls, source coverage, exports and the explanation of the tool's exploratory purpose."]},"evidenceScope":"An academic product evaluation. Search-result relevance was checked using 30 queries across different subject areas; user feedback came from an academically oriented group. Product analytics cover a 30-day evaluation period. Queries, visits and participants are different measures.","limitations":["I did not test willingness to pay or institutional demand, so commercial viability remains an open question."]},"content_hash":"sha256:d52b45d0e18656942a865dc1e75875a2bd8d7c1d97db31be3b8e1e5a24f52ebb","evaluation_scope":"An academic product evaluation. Search-result relevance was checked using 30 queries across different subject areas; user feedback came from an academically oriented group. Product analytics cover a 30-day evaluation period. 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