Research & structured collection

MakeBeacon gathers information against agreed criteria and organizes it into a consistent, reviewable dataset. Each project defines what to collect, which sources to use, how to record evidence, and how to flag information that is missing or uncertain.

Research is easier to use when the question, collection criteria, and source requirements are clear. MakeBeacon works with your team to define the fields and inclusion rules, then gathers information from agreed public or client-authorized sources. Collected records are structured consistently, with source references and notes where needed to support review. The work can include deduplication, basic completeness checks, and flags for entries that need verification. The final format and collection method are agreed before work begins, based on the scope and source availability.

Problems this solves

• Information needed for a decision is spread across multiple sources.
• Teams need records collected against consistent criteria.
• Research findings are stored in notes that are difficult to compare or reuse.
• A dataset lacks source references or collection notes.
• Different people record the same information in different formats.
• Missing or uncertain entries are mixed in with verified records.
• A one-time research task needs a clear, reusable collection structure.

What is included

• Definition of the research question, fields, and inclusion criteria.
• Agreement on sources and collection format.
• Structured collection from agreed public or client-authorized sources.
• Consistent formatting of collected records.
• Source links or references and collection notes, as scoped.
• Basic checks for duplicates and missing required fields.
• Flags for uncertain or incomplete information.
• Handover notes describing the collection method and limitations.

Typical deliverables

• Structured dataset in an agreed format.
• Field definitions and collection criteria.
• Source references for collected entries, where available.
• Notes on incomplete, uncertain, or excluded records.
• Summary of the collection method and scope.
• Handover instructions for reviewing or extending the dataset.

Technologies & tools

• Excel and CSV data formats
• Google Sheets
• Python
• pandas