Specify Institutional Scopings

Institutional Scoping in Specify

Specify supports data from multiple collections within a single database. For example, specimen records for fish and birds are combined within the same data tables of the database. For institutions with multiple collections, this storage model enables but does not grant access to data across multiple disciplines for most users. Users can have login and access privileges only for their collection data. Access to data across collections, disciplines, or divisions is an important capability for museums with centralized registration, accession, or conservation activities. It also allows others with a legitimate interest in the institution’s complete holdings, such as research directors, to analyze and report on the institution’s entire holdings.

In Specify, there are data tables and data entry forms for entering Institution and Division-level information, where a Division, usually, but not always, represents a single taxonomic discipline as a museum would treat it. Each division or discipline may have multiple collections, for example, Ichthyology may have a voucher and tissue collection; Ornithology may have voucher, tissue, and egg Collections.

Schema Configuration Scoping

The Schema Config (sometimes referred to as the ‘interface schema’) is scoped to the Discipline. This means that field and table labels are specific to each discipline.

Pick lists are specific to the collection. This means that each collection can have a unique pick list assigned to a field, but the field label would be the same for the entire discipline.

Example Collection Hierarchy:

For a Specify user, data elements have visibility or scope relative to other data elements and with respect to the administrative context of a Collection.

There are data elements that are unique to a discipline, but are visible to all the collections within that discipline; for example, taxonomic names are shared across all Ichthyology collections.

Other data elements are scoped only to a single collection; for example, preparation types are typically unique to a particular kind of fish collection, tissues might have ’tissue’ and ‘DNA’ as preparation types, whereas a voucher (or main) collection, might have EtOH and C&S as prep types.

These preparation types can be easily duplicated across collections as desired, but typically they correspond to the type of collection (wet, dry, pollen, fruit, frozen, tissue, etc.).

It is important to note that Specify accommodates multiple Collections within a particular Discipline, like Ichthyology shown above, but the Specify schema also allows collections to be combined into a single database for common management, for example, a Specify herbarium database might include preparation types: sheets, fruits, seeds, type photos, etc. How you choose to set up your Specify database at the Collection level depends on your curatorial practice and historical preferences.

Table Scoping Hierarchy

The figure below shows an overview of the “scope” of various records in Specify. As we move left to right in the figure the scope is reduced. The data types shown in the Discipline column are scoped to that Discipline, to all Collections defined under it. All Collection Objects in those Collections can access those data items. Put another way, all Collections within a Discipline share the same Taxonomic Tree, Localities, Collecting Events, etc. One level down each Collection has its own set of Collection Objects, Preparation Types, Pick Lists, etc.

Given the earlier example involving the Ichthyology Discipline, both the Wet and Dry Collection would share a Taxon Tree, Geography Tree, Agents (e.g. collectors, authors, annotators), etc.

The Wet Collection would have its own set of preparation types and pick lists, which would be different from the Dry Collection’s preparation types and pick lists. Again, some values for the pick lists and prep types could be duplicated across collections, the point is that each collection has the capability to hold custom values for pick list fields and for the Preparation Type fields, but there is no barrier to having the same values for those things in two or more Collections.

Agents, which includes individuals or groups acting in whatever role, in the Specify data model are shared within the Division, but not across Divisions at the Institution level. That means that there will be times when a collector of two or more biological specimen types (Vertebrate Zoology and Botany) will be duplicated at the Institution level. We implemented this to accommodate the needs of Divisions to annotate addresses or personal information about people with information that was unique or perhaps sensitive to their Division. Collecting Events, Collecting Trips, and Localities are scoped to Discipline.

In summary, Specify supports data from multiple collections within a single database, allowing for a hierarchical structure where collections can be organized under disciplines, which in turn are organized under an institution. Each collection has its own set of data elements that are unique to that collection, while some data elements are shared across all collections within a discipline. Specify also allows for custom values for pick list fields and preparation type fields for each collection. However, agents are shared within the division, but not across divisions at the institution level, and collecting events, collecting trips, and localities are scoped to the discipline.


Should I have multiple collections in the same database?

One Database, One Division, One Collection:

Pros:

  • All data is unique to the collection
  • Scoping is no longer a concern
  • ​Queries can return all records in the database at once​
  • Database is compartmentalized
    • Backups can be made and restored per collection
    • Audit log is specific to the single database
  • Actions are limited to the specific collection and do not risk affecting other data in other collections

Cons:

  • Records cannot be shared with other collections or divisions in other databases
    • That means that all Accessions, Agents, Collecting Events, Loans, Gifts, Taxa, Localities, and more exist and can only be referenced within the single collection.

One Database, One Division, Multiple Collections:

Pros:

  • User accounts are shared between all collections (permissions are set by collection)
  • Records can be shared between multiple collections according to the scoping hierarchy in this document
    • This is most important when you have the following records that you want to share between collections:
      • Within the same discipline: Accessions, Agents, Collecting Events, Loans, Gifts, Taxa, Localities, and more
    • Within the same collection: Pick lists, forms, and preparation types
  • Database contains several collections within the same discipline
  • Setups that include several collections in the same division allow for great flexibility in pairing observations with specimens, tissues with vouchers, and much more

Cons:

  • Scoping must be considered when creating records
  • Queries include only objects from the current collection’s scoping (including Collection Objects)

One Database, Multiple Divisions, Multiple Collections:

Pros:

  • User accounts are shared between all collections (permissions are set by collection)
  • Records can be shared between multiple collections in the same division according to the scoping hierarchy in this document
    • This is most important when you have the following records that you want to share between collections:
      • Within the same discipline: Accessions, Agents, Collecting Events, Loans, Gifts, Taxa, Localities, and more
  • Database contains several collections, requiring you to set up only one deployment
  • Setups that include several collections in the same division allow for great flexibility in pairing observations with specimens, tissues with vouchers, and much more

Cons:

  • Scoping must be considered when creating records
  • All of Specify is contained in one deployment
    • If an issue that requires a restore occurs in one collection, all other collections would be affected
    • Audit log contains data from every collection, making it particularly difficult

Contact us to discuss the relevant issues for your collection.


Full Table Scoping

In Specify, many tables are scoped to a specific parent table and are organized under it. The Institution table, which contains information about the entire institution, is at the top of the hierarchy. The Division-level tables, which contain information about the divisions within the institution, are under the Institution-level tables. The Discipline-level tables, which contain information about the taxonomic disciplines within each division, are under the Division-level tables. The Collection-level tables contain information about the collections within each discipline and are under the Discipline-level tables. The Collection Object table contains information about individual specimens within each collection under the Collection-level tables. This hierarchy allows for a logical organization of data and enables the management and retrieval of information at different levels of granularity.


Displayed below are the parent tables listed along with the tables that are scoped to each respective level (based on this code):

Institution

  • Accession*
  • Journal
  • Permit
  • Reference Work
  • Storage
  • Division

    • Accession*
    • Agent
    • Collector
    • Exchange In
    • Exchange Out
    • Funding Agent
    • Group Person
    • Repository Agreement
    • Discipline

      • Attribute Def
      • Collecting Event
      • Collecting Event Attribute
      • Collecting Trip
      • Collecting Trip Attribute
      • Exchange In Prep
      • Exchange Out Prep
      • Field Notebook Page
      • Field Notebook Page Set
      • Gift
      • Gift Agent
      • Gift Preparation
      • Loan
      • Loan Agent
      • Loan Preparation
      • Loan Return Preparation
      • Locality
      • LocalityCitation
      • LocalityNameAlias
      • PaleoContext
      • Shipment
      • Sp Export Schema
      • Sp Locale Container
      • Taxon
      • Geography
      • Geologic Time Period
      • Lithostratigraphy
        • Collection

          • Field Notebook
          • Pick List
          • Prep Type
          • Sp App Resource Dir
          • Sp Task Semaphor
          • Collection Object

            • Collection Object Attachment
            • Collection Object Attr
            • Collection Object Citation
            • Collection Object Property
            • Conserv Description
            • DNA Sequence
            • Determination
            • Exsiccata Item
            • Other Identifier
            • Preparation
            • Treatment Event
            • Voucher Relationship

*Accession can be set to be global or scoped to the division when the database is created

Trees :trees_:

Storage – Institution
Geography – Discipline
Geologic Time Period / ChronoStrat – Discipline
LithoStrat – Discipline
Taxon – Discipline

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