Data Model

Entity Types and Ontology

Loosely following "Functional Requirements for Bibliographic Records" (FRBR), but removing the "manifestation" abstraction, and favoring files (digital artifacts) over physical items, the primary bibliographic entity types are:

  • work: representing an abstract unit of creative output. Does not contain any metadata itself; used only to group release entities. For example, a journal article could be posted as a pre-print, published on a journal website, translated into multiple languages, and then re-published (with minimal changes) as a book chapter; these would all be variants of the same work.
  • release: a specific "release" or "publicly published" (in a formal or informal sense) version of a work. Contains traditional bibliographic metadata (title, date of publication, media type, language, etc). Has relationships to other entities:
    • "variant of" a single work
    • "contributed to by" multiple creators
    • "references to" (cites) multiple releases
    • "published as part of" a single container
  • file: a single concrete, fixed digital artifact; a manifestation of one or more releases. Machine-verifiable metadata includes file hashes, size, and detected file format. Verified URLs link to locations on the open web where this file can be found or has been archived. Has relationships:
    • "manifestation of" multiple releases (though usually a single release)
  • creator: persona (pseudonym, group, or specific human name) that contributions to releases have been attributed to. Not necessarily one-to-one with a human person.
  • container (aka "venue", "serial", "title"): a grouping of releases from a single publisher.

Note that, compared to many similar bibliographic ontologies, the current one does not have entities to represent:

  • funding sources
  • publishing entities
  • "events at a time and place"
  • physical artifacts, either generically or specific copies
  • sets of files (eg, a dataset or webpage with media)

Each entity type has it's own relations and fields (captured in a schema), but there are are also generic operations and fields common across all entities. The process of creating, updating, querying, and inspecting entities is roughly the same regardless of type.

Identifiers and Revisions

A specific version of any entity in the catalog is called a "revision". Revisions are generally immutable (do not change and are not editable), and are not usually referred to directly by users. Instead, persistent identifiers can be created, which "point to" a specific revision at a time. This distinction means that entities referred to by an identifier can change over time (as metadata is corrected and expanded). Revision objects do not "point" back to specific identifiers, so they are not the same as a simple "version number" for an identifier.

Identifiers also have the ability to be merged (by redirecting one identifier to another) and "deleted" (by pointing the identifier to no revision at all). All changes to identifiers are captured as an "edit" object. Edit history can be fetched and inspected on a per-identifier basis, and any changes can easily be reverted (even merges/redirects and "deletion").

"Staged" or "proposed" changes are captured as edit objects without updating the identifiers themselves.

Fatcat Identifiers

Fatcat identifiers are semantically meaningless fixed-length random numbers, usually represented in case-insensitive base32 format. Each entity type has its own identifier namespace.

128-bit (UUID size) identifiers encode as 26 characters (but note that not all such strings decode to valid UUIDs), and in the backend can be serialized in UUID columns:

work_rzga5b9cd7efgh04iljk8f3jvz
https://fatcat.wiki/work/rzga5b9cd7efgh04iljk8f3jvz

In comparison, 96-bit identifiers would have 20 characters and look like:

work_rzga5b9cd7efgh04iljk
https://fatcat.wiki/work/rzga5b9cd7efgh04iljk

A 64-bit namespace would probably be large enough, and would work with database Integer columns:

work_rzga5b9cd7efg
https://fatcat.wiki/work/rzga5b9cd7efg

Fatcat identifiers can used to interlink between databases, but are explicitly not intended to supplant DOIs, ISBNs, handle, ARKs, and other "registered" persistent identifiers.

Entity States

Internal Schema

Internally, identifiers are lightweight pointers to "revisions" of an entity. Revisions are stored in their complete form, not as a patch or difference; if comparing to distributed version control systems (for managing changes to source code), this follows the git model, not the mercurial model.

The entity revisions are immutable once accepted; the editing process involves the creation of new entity revisions and, if the edit is approved, pointing the identifier to the new revision. Entities cross-reference between themselves by identifier not revision number. Identifier pointers also support (versioned) deletion and redirects (for merging entities).

Edit objects represent a change to a single entity; edits get batched together into edit groups (like "commits" and "pull requests" in git parlance).

SQL tables look something like this (with separate tables for entity type a la work_revision and work_edit):

entity_ident
    id (uuid)
    current_revision (entity_revision foreign key)
    redirect_id (optional; points to another entity_ident)
    is_live (boolean; whether newly created entity has been accepted)

entity_revision
    revision_id
    <all entity-style-specific fields>
    extra: json blob for schema evolution

entity_edit
    timestamp
    editgroup_id (editgroup foreign key)
    ident (entity_ident foreign key)
    new_revision (entity_revision foreign key)
    new_redirect (optional; points to entity_ident table)
    previous_revision (optional; points to entity_revision)
    extra: json blob for progeny metadata

editgroup
    editor_id (editor table foreign key)
    description
    extra: json blob for progeny metadata

An individual entity can be in the following "states", from which the given actions (transition) can be made:

  • wip (not live; not redirect; has rev)
    • activate (to active)
  • active (live; not redirect; has rev)
    • redirect (to redirect)
    • delete (to deleted)
  • redirect (live; redirect; rev or not)
    • split (to active)
    • delete (to delete)
  • deleted (live; not redirect; no rev)
    • redirect (to redirect)
    • activate (to active)

"WIP, redirect" or "WIP, deleted" are invalid states.

Additional entity-specific columns hold actual metadata. Additional tables (which reference both entity_revision and entity_id foreign keys as appropriate) represent things like authorship relationships (creator/release), citations between works, etc. Every revision of an entity requires duplicating all of these associated rows, which could end up being a large source of inefficiency, but is necessary to represent the full history of an object.

Controlled Vocabularies

Some individual fields have additional constraints, either in the form of pattern validation ("values must be upper case, contain only certain characters"), or membership in a fixed set of values. These may include:

  • subject categorization
  • license and open access status
  • work "types" (article vs. book chapter vs. proceeding, etc)
  • contributor types (author, translator, illustrator, etc)
  • human languages
  • identifier namespaces (DOI, ISBN, ISSN, ORCID, etc; but not the identifiers themselves)

Other fixed-set "vocabularies" become too large to easily maintain or express in code. These could be added to the backend databases, or be enforced by bots (instead of the core system itself). These mostly include externally-registered identifiers or types, such as:

  • file mimetypes
  • identifiers themselves (DOI, ORCID, etc), by checking for registration against canonical APIs and databases

Global Edit Changelog

As part of the process of "accepting" an edit group, a row is written to an immutable, append-only table (which internally is a SQL table) documenting each identifier change. This changelog establishes a monotonically increasing version number for the entire corpus, and should make interaction with other systems easier (eg, search engines, replicated databases, alternative storage backends, notification frameworks, etc.).