Natural history collection management

Manage, assess and benchmark your natural history collection

CollMan is free museum collection management software for natural history, built for museums, universities and researchers. It combines a specimen database with a scientific value assessment: 20 transparent, peer-reviewed collection assessment criteria produce a reproducible rank, while curatorial activities, loans, publications and permits stay in one place — with anonymous peer benchmarking and biodiversity data published to GBIF as a Darwin Core Archive.

Plate from Ernst Haeckel’s Kunstformen der Natur (1904) — Discomedusae
Ernst Haeckel, Kunstformen der Natur (1904) · Public domain

Open knowledge base

Explore the public data behind CollMan

Two open-data products are freely browsable — no login required: the Atlas of Invertebrate Distribution in Poland and the registry of Polish forms of nature protection.

Atlas of Invertebrate Distribution

A growing public Atlas of invertebrate species recorded in Polish protected areas. Built from museum collections and peer-reviewed sources, with Darwin Core compatibility for GBIF.

3,168
species
7,356
occurrence records
323
protected areas
Browse the Atlas →

Polish Forms of Nature Protection

Reference of all protected areas registered in Poland: national parks, reserves, landscape parks, Natura 2000 sites, and other forms. Data sourced from CRFOP.

12,902
protected areas
9
form types
Open the registry →

Five valuation tiers

Each collection receives a numeric score and a rank, based on 20 weighted criteria.

Unique
Very valuable
Valuable
Moderately valuable
Average

Everything around the collection, in one place

Each collection record is split into focused tabs you can fill in over time.

Assessment

20 weighted criteria — taxonomic composition, conservation status, historical significance and more — producing a transparent, reproducible score and rank.

Profile

Type, scope, storage form, status, country list and links to external catalogues. Shared across every assessment version of the collection.

Data metrics

Upload a Darwin Core Archive from Specify, Symbiota, Arctos or an IPT and CollMan measures georeferencing, dating, attribution and identification depth — evidence that backs the assessment instead of self-declaration.

Curatorial activities

Plan, assign and complete work — digitisation, conservation, accessioning, research — with deadlines, overdue flags, a personal task list and an upper-bound forecast of the next score.

Loans

Inbound and outbound specimen loans with expected return dates, status tracking, and overdue flagging.

Publications

Cite-tracking with DOI auto-lookup via CrossRef. The citation index aggregates papers, monographs and theses across the collection.

Permits

Collecting, import, export and Nagoya-ABS permits — including PIC, MAT, IRCC and benefit-sharing details — with PDF storage and expiry-soon warnings.

Benchmark

Opt in to an anonymous distribution of scores across peer collections of the same type — see where you stand without revealing identity.

External visibility

Buttons to GBIF, BOLD and AMUNATCOLL, plus live GBIF record counts, and a Latimer Core export of the whole collection description for GBIF GRSciColl.

Citable published record

Give a collection a permanent web address, frozen at publication so later edits cannot rewrite what someone cited. The description and the score are published separately, each states the method version that produced it, and corrections are announced rather than made silently.

What a spreadsheet cannot give you

A collection can be assessed in a spreadsheet. What it cannot do is tell you where you stand, prove its own numbers, or produce something a grant panel can cite.

A position, not just a number

Anonymous peer benchmarking places your score in the distribution of comparable collections. Data-quality metrics are benchmarked across everyone who has uploaded an archive, while scores are compared only within the same method version — so a percentile always means something specific.

Evidence instead of self-declaration

Upload a Darwin Core Archive and CollMan computes the data-integrity part of the assessment from the records themselves — georeferencing, dating, attribution, identification depth — with the counts shown next to every rate, so a reviewer can audit them.

A record that can be cited

Publish a collection to a permanent address in Latimer Core, the TDWG standard whose unit is the collection rather than the specimen. The snapshot is frozen, the assessment method is versioned, and if a scoring correction lands the affected records say so instead of changing quietly.

Individually, some of these exist elsewhere. The combination — collection-level scoring, peer benchmarking, computed evidence, a ratified collection-level standard, and citable records with correction semantics — is what CollMan is for.

Use cases for the management of natural history collections

What curators, collection managers and institutions get out of CollMan.

Justify funding for your collection

CollMan generates a documented, reproducible scientific value score based on 20 peer-reviewed criteria. Use the PDF export to support grant applications, institutional reporting and natural history collection funding justification — a transparent number replaces "trust me, it's important".

Benchmark against peer collections

Opt in to anonymous museum collection benchmarking: compare your collection's score against the distribution of similar collections worldwide. Understand where you stand on each criterion and identify the lowest-cost improvements to climb the rank.

Plan curation work systematically

Track collection curation planning as discrete actions — digitisation, conservation, accessioning, identification — each linked to the criteria it would improve. CollMan shows an upper-bound forecast of your next score, so curatorial effort is steered toward impact.

Make your collection visible in GBIF

Connect your collection to its GBIF dataset and CollMan surfaces live GBIF collection metrics — record counts, last update date, direct dataset link — on every show page and PDF. Visibility becomes part of the collection's scored profile.

How it works

1

Create the profile

Name the collection, set the owner and date, classify the type and scope, and paste links to external catalogues.

2

Answer 20 evaluation criteria

From taxonomic composition to conservation status — the form guides you through each one. The score and rank are computed server-side.

3

Track activities and outputs

Record curatorial work, loans, citing publications and permits as they happen — each on its own tab.

4

Share, benchmark, revise

Download a tailored PDF, send a read-only share link, opt in to the anonymous benchmark, or save a new assessment version when things change.

Who is it for?

Museum curators

Document the relative scientific value of holdings to support funding, conservation, and acquisition decisions.

Field researchers

Catalogue and rank specimens collected during fieldwork, with reproducible criteria.

Natural history collectors

Understand the scholarly significance of private collections beyond market valuation.

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