BF Workbench is a restricted scientific system. Records are available only to registered, authorised accounts.

What the workbench is and how work is organised

Records, projects and datasets, evidence files, analyses and statements, and how they fit together.

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The workbench is the part of BOLD Forensics you sign in to. It holds specimen records, the DNA sequences and evidence files that belong to them, and the analyses run on them, and it keeps track of who did what. It is built for laboratories and agencies whose identifications may be challenged, so everything on it is organised around one question: can this result be traced back to the specimen and the material it came from?

This page explains the handful of ideas the rest of the documentation relies on. If you understand these, the screens will make sense.

Records

A record is one specimen and everything known about it: where and when it was collected, who collected it, what it was identified as, its DNA sequences, and the files that document it. Every record has a process ID, a code the platform assigns when the record is created, which is the identifier everything else refers to. The sample ID is your own laboratory's identifier for the same specimen; the two sit side by side on the record.

A record is made up of groups of fields: the specimen itself, the collection event, taxonomy, sequence data, and the forensic fields that tie a sample to physical evidence such as seal and bag numbers. The groups follow a community standard, the Barcode Core Data Model, extended for forensic handling. What a record holds walks through them.

Projects and datasets

Records are never loose. Each belongs to exactly one project, and a project is also the unit of access: a project has a list of people who can see it, each at a named access level. A dataset is a second kind of container that can gather records from one or more projects, for example to assemble the material for a case or a reference collection, without moving them out of their project.

Projects and datasets are referred to together as recordsets, and the recordset console is where most work starts: it shows counts and coverage, lets you open individual records, and is the launching point for uploads, downloads and analyses. See Projects and datasets explained and Sharing a project or dataset.

Evidence files

Photographs, chain-of-custody documents, permits, chromatograms and other files are attached to records but are not stored in the record itself. They go to BioStor, the platform's file store, which keeps the original, records a checksum, generates previews, and links the file to the record by process ID. From your point of view they appear as tabs and galleries on the record and the project; behind the scenes they take a different route from record data, which is why uploads of files and uploads of specimens are tracked separately. How data gets in explains the two routes.

Analyses

An analysis is a job you run on a chosen set of records: identification against the platform's reference database, distance summaries, barcode gap, diagnostic characters, tree construction, sequence composition, and exports. You choose the records, pick a method, set its parameters and submit. The job runs in the background, usually within minutes, and returns a report page with tables, charts and a package of files to download. The same framework runs every method, which is why they are configured and tracked the same way. Start with Running an analysis; the methods themselves are described in layer 2.

Statements

An expert statement is a document generated from a record for use as evidence: it draws on the record, the analysis results and the registered qualifications of the person swearing it, the deponent. Statements go through a review step before they are approved, and the signed copy is uploaded back to the record. See Statements and deponents.

How the pieces fit together

Work usually follows the order in which evidence is produced:

  1. Register the specimen, one at a time or from a spreadsheet, creating the record.
  2. Attach evidence files: photographs, custody documents, permits.
  3. Add sequence data as it comes off the sequencer: sequences, trace files, reads.
  4. Run analyses on the records that now have sequences.
  5. Prepare a statement from the record and its results.

Each step adds to the same record, so the chain from statement back to specimen is intact without anyone having to maintain it by hand.

Who does what

Everyone signs in with an invited account and a two-factor code. What you can then see and do depends on the access list of each project and dataset, not on a single global role. A platform administrator additionally creates accounts, maintains reference lists such as taxonomy and institutions, and oversees uploads, analyses and statements across the platform; that side is covered in layer 4.

Good to know: access works at the level of a whole project or dataset. There is no way to hide an individual record or field from someone who can see the recordset it is in.