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How to organize a research project in WebSnips — a practical guide for researchers, analysts, and professionals who want to structure, annotate, track
A research project — whether it's a market analysis, a policy brief, a thesis chapter, or a competitive landscape report — has specific organizational requirements that differ from a general knowledge library:
WebSnips' Collections, tags, Connections, and Creator Studio each serve specific functions in a research project workflow. This guide shows how to combine them into a system that handles a research project from kickoff through final output.
Every research project needs a primary Collection and, for larger projects, secondary Collections for sub-topics or phases.
Primary Collection:
Name it clearly: [Project Name] Research or Research: [Topic]
Examples:
Secondary Collections (for larger projects with 25+ sources):
Organize by sub-topic within the project:
For a market analysis:
For a policy review:
Sources can belong to multiple Collections: an article about a competitor's battery technology strategy belongs in both "Technology Landscape" and "Competitor Analysis."
Create a tag taxonomy for the project before you start capturing. The three categories most useful for research projects:
Status tags (where is this source in the workflow):
rp-to-read — captured, not yet readrp-reading — currently reading / partially readrp-annotated — fully read and annotatedrp-to-cite — will be cited in the outputrp-background — informative but not directly citedrp-excluded — captured but determined to be out of scopeSource type tags:
primary-source — original data, first-hand accounts, official documentssecondary-source — analysis, commentary, synthesis of primary sourcescompany-data — reports, filings, announcements from the companies you're researchingexpert-opinion — interviews, quoted experts, commentary from practitionersquantitative — sources with data, statistics, market size numbersqualitative — case studies, interviews, descriptive accountsQuality/confidence tags:
high-confidence — vetted sources, authoritative dataverify-needed — useful but needs cross-referencingsingle-source — claim appears in only one source; note the single-source riskCreate Smart Collections for each status layer so you always know where things stand:
tag:rp-to-read AND collection:[Project Name] Research → Reading queuetag:rp-annotated AND collection:[Project Name] Research → Processed sourcestag:rp-to-cite AND collection:[Project Name] Research → Sources being used in outputtag:rp-annotated NOT tag:rp-to-cite NOT tag:rp-background AND collection:[Project Name] Research → Annotated but not yet allocatedThese Smart Collections give you a live dashboard of the project's source state without maintaining a separate spreadsheet.
In a focused research project, resist capturing everything tangentially related. Ask before each capture: "Will this help me answer the project's core questions?" If you're unsure, use the rp-to-read tag and include a brief note about why it might be relevant — this lets you decide later without having lost the source.
For each source:
rp-to-readThe relevance note is important even before you've read the full source — it documents your hypothesis about relevance, which you can evaluate after reading.
Annotation happens during or immediately after reading each source. Update the status tag from rp-to-read to rp-annotated after completing annotation.
For each source, write:
Research question answered: Which of the project's core questions does this source address? Be specific ("This answers: What is the current price per kWh for solid-state batteries at scale?").
Key finding: The one-sentence answer the source provides.
Supporting evidence: The specific data, quote, or argument. Include page numbers or section headings for precise reference later.
Source credibility assessment: Who published this? What's their methodology? Any potential bias or limitation?
Connections to other sources: Does this source agree with, contradict, or extend another source in the project? List by name.
Draft notes: If you can already see how this finding will appear in the output ("This will go in the Supply Chain section, as evidence for the cost reduction trend"), note it here.
Example annotation for a market research report:
Research question answered: What is the projected market size for solid-state
batteries through 2030?
Key finding: Global solid-state battery market projected to reach $8.4B by 2030,
CAGR 38.2% from 2024 baseline of $0.9B.
Supporting evidence: "The global solid-state battery market size was valued at
USD 0.94 billion in 2024 and is projected to reach USD 8.44 billion by 2030,
exhibiting a CAGR of 38.2% during the forecast period." (p.4)
Source credibility: MarketsandMarkets report. Methodology: primary interviews
with industry executives + secondary analysis of company filings. Standard
market research methodology — projections should be treated as directional,
not precise.
Connections: Goldman Sachs analysis (separate clip) projects $6.1B by 2030 —
more conservative. Toyota IR presentations align with the higher estimate.
Draft notes: Use the $0.94B → $8.4B CAGR figure in the Market Opportunity
section opener. Note the Goldman/MarketsandMarkets divergence as a range.
Connections in WebSnips are especially valuable in research projects because research has inherent structure: sources support each other, contradict each other, cite each other, and address the same question from different angles. Making these relationships explicit transforms a pile of sources into a structured body of evidence.
Creating connections between research sources:
After annotating each source, create connections to the sources mentioned in your "Connections" annotation field:
The graph view for research projects:
Filter the Connections graph to the project Collection. The resulting graph reveals:
For a research project, the graph view at the mid-point of the project is a useful audit: isolated sources should either be connected to others or flagged as single-source claims.
A research project needs to know not just what you've read but what the coverage gaps are.
Research coverage audit (mid-project):
Questions answered by only one source → flag for additional research. Questions with no sources at all → either add to the capture list or explicitly note as out of scope.
Source balance audit:
Review the distribution of source types:
Tags make this audit fast: filter by tag:primary-source to see primary source coverage, tag:expert-opinion to see expert coverage, etc.
When the research is captured, annotated, and connected, synthesis happens in Creator Studio.
Opening the project for synthesis:
rp-to-cite Smart Collection)The synthesis workflow:
Generate an outline from the project Collection → review and edit to match the output's intended structure
For each section of the outline:
Complete the draft
Export the reference list (filtered to rp-to-cite clips)
The annotation note as draft material:
Your "Draft notes" field from each annotation is the pre-organized material for each section. Before writing a section, filter to the relevant sources and read through their "Draft notes" annotations — these are the sentences and data points you already identified as going into the output. Writing becomes assembly.
When the output is complete, close the project in WebSnips:
Archive the project Collections:
Rename the project Collection: "COMPLETE: [Original Name] [Date]" — this signals it's closed without deleting the research.
Export a final source list:
Generate the project's citation list (all rp-to-cite clips) as a formatted reference list. Save it alongside the output document as the project's source record.
Tag cleanup:
Review clips tagged rp-background and rp-excluded — some of these may be worth retaining in your general library with different tags. Remove project-specific tags from clips you want to keep as general reference.
Handoff (if sharing):
If the project is being handed off to a colleague or client, WebSnips' Collection sharing features let you share the project Collection with all annotations intact. The recipient sees your full research and annotation work, not just the output document.
Setup: A policy analyst at a think tank is producing a 25-page brief on the evidence base for four-day work week policies. She needs to review academic research, survey data, employer case studies, and counterarguments. Output is due in 6 weeks.
Week 1-2 (Capture): She creates 5 Collections:
She captures 45 sources over two weeks — academic papers from PubMed and Google Scholar, employer case study write-ups, survey reports, and skeptical commentary from management researchers. Each capture gets her relevance note and status rp-to-read.
Week 3 (Annotation): She annotates 7-8 sources per day using the research annotation protocol. By end of week: 45 sources annotated. She updates all tags to rp-annotated.
Week 4 (Connections + Coverage Audit): She creates 55 connections between sources — academic studies that inform the employer case studies, survey data that contradicts the case study evidence, the meta-analysis that synthesizes 11 primary studies. The coverage audit reveals: the counterarguments Collection only has 5 sources vs. 40 supporting sources — she adds 8 more counterargument sources before drafting.
Week 5 (Synthesis in Creator Studio): Outline generated from the primary Collection. She drafts the brief section by section, using the rp-to-cite Smart Collection as her research panel. Her annotations' "Draft notes" fields provide the core claims for each section.
Week 6 (Review and Export): Review and edit the draft. Export citations (APA format) from the rp-to-cite clips. Archive the project Collection.
A research project in WebSnips is organized around the same structure as the project itself: a defined scope (project Collection), a source lifecycle (status tags + Smart Collections), an evidence network (Connections), and a synthesis environment (Creator Studio). The system is designed so that the organizational work done during capture and annotation — tagging, annotating with protocol, creating connections — directly accelerates the synthesis and drafting stages. The research project workflow described here converts what is often a chaotic, multi-tool, spreadsheet-dependent process into one integrated environment from first capture through final output.
See also: Clip Articles for Later Reading.
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