Aquatic facility software: which records should connect?

A management system should reconstruct a history

When an experimental result changes, staff may need to recover a group’s parents, age, movements and housing conditions. If those details are divided between notebooks, spreadsheets and personal memory, installing new software will not resolve the underlying problem. The requirement is a set of connected records whose meaning remains clear to someone reviewing them later.

Wilkinson and colleagues’ 2016 FAIR principles describe data that are Findable, Accessible, Interoperable and Reusable. Bedell and colleagues’ 2025 “Zebrafishology” guidelines identify information needed for rigorous, reproducible zebrafish studies. These references can inform requirements for an aquatic research facility. Neither compares commercial management packages nor certifies a particular product or implementation.

Distinguish the animal, the group and the line

A genetic line, a group occupying a tank and an individual fish are different entities. A management system needs to distinguish them while retaining relevant relationships. A tank move should not erase the group’s origin, and a new clutch should not inherit an identifier whose earlier meaning has become unclear.

Genotype records describe genetic information, whereas phenotype records describe observed characteristics. A line label does not replace documentation of a genotyping method or an observation. Bedell and colleagues discuss the importance of genetic context and its reporting when interpreting zebrafish results. A management record should preserve the distinctions required to understand that context.

Vetofish’s proposed approach is to define what each identifier represents before entering large volumes of information. Relationships between parents, clutch and offspring group should remain retrievable after movement. Unknown information should also be distinguishable from information awaiting entry, so that an empty field does not acquire an unintended meaning during analysis or export.

Connect observations to housing conditions

A temperature value is difficult to interpret without knowing when, where and how it was measured. The same applies to a clinical observation, feeding change or technical incident. Units, location, timing and observer should accompany a record whenever they are needed to understand what the entry describes and how it can be compared with other entries.

The 2025 guidelines ask researchers to report relevant husbandry conditions, including lighting, feeding and water conditions. Their purpose is study design and reporting. Translating these needs into management fields is an organisational decision: software should help recover important information without making routine entry so burdensome that staff stop maintaining it consistently.

One useful test is to ask which groups occupied a water circuit during a particular incident. The records should help reconstruct possible exposure and subsequent observations. They should not turn a shared time and place into evidence of causation. Accurate relationships support a scientific investigation, while interpretation still requires an appropriate comparison and understanding of alternative explanations.

Test data export before committing the records

FAIR gives identifiers, metadata, shared vocabularies and provenance a central role. It does not prescribe a particular technology. An export becomes useful when column meanings, units and relationships between files remain documented. Being able to download a file is therefore only part of being able to reuse its contents.

Before choosing a system, a facility can request an example export containing a simple pedigree, tank movements and observations. Another team member should be able to reconstruct the sequence from those files. This tests whether information survives outside the original interface, rather than judging the system only by its screens or advertised feature count.

Accessibility under FAIR does not require unrestricted public access. The principles allow authentication and authorisation where necessary. Facilities need to define permissions according to responsibilities and decide what should be shared with researchers, veterinarians and authorised collaborators. Clear access rules support appropriate use without confusing data stewardship with universal disclosure.

Make corrections traceable and recovery testable

Entry errors must be correctable without obscuring the history. For information that can affect interpretation, requirements can include who changed a value, when it changed and why. This operational recommendation follows the need for provenance; it does not establish that a system meets a specific regulatory certification or legal requirement.

Backups also need a practical test. Holding a copied file does not demonstrate that records can be restored within an acceptable period. An exercise agreed with the information technology team can check recovery of both data and their relationships, clarify responsibilities and establish how essential work would continue during an outage.

Testing should include ordinary events that expose weaknesses in rules: a user leaving, an origin being corrected, groups being combined or a display name changing. The objective is a dependable history that remains compatible with daily work. If staff routinely work around the system, a technically sophisticated database may still contain incomplete or misleading records.

Conclusion: start with the questions records must answer

Choosing management software is easier when a facility first defines the decisions it needs to document. Identity, pedigree, husbandry context and observation provenance provide a starting point to adapt to its projects. FAIR and zebrafish reporting guidance offer useful principles; consistent entry rules, everyday use and practical verification determine whether those principles become useful records.

Defining requirements with Vetofish

Our advice and support service can help identify priority health and husbandry information and develop test scenarios with the facility team. For research institutions, this supports requirements matched to actual decisions and responsibilities. It provides a basis for evaluating a tool without endorsing a product solely on the strength of a commercial demonstration.