Databasing Overview from Digitization Workshop ASIH 2016
Contents
Statement of Purpose
These links and documents contain information about databasing as relevant to natural history collections.
Introduction
Contributors
Content generated during The American Society of Ichthyologists and Herpetologists (ASIH) Annual Joint Meeting - 2016, during an iDigBio sponsored workshop by the following individuals participating in the "Museum Logistics" working group of the aforementioned workshop:
- Andy Bentley - University of Kansas, Collection Manager - Fishes
- Brian Sidlauskas - Oregon State University, Curator of Fishes
- Caleb McMahan - The Field Museum, Collection Manager of Fishes
- Norma Salcedo - College of Charleston, Professor
- Dean Hendrickson - The University of Texas at Austin, Curator of Fishes
- Alexandra Snyder - Museum of Southwestern Biology - Fishes, Collections Manager
Database choice and formatting
Database systems - Arctos, CollectionsSpace, KE-Emu, Specify etc.
Considerations when selecting a database system:
Relational structure of multiple tables connected through varied relationships of one-to-many, many-to-one and many-to-many so as to negate redundancy of data entry and linking of data. This normalized and extensive data model should adhere to natural history collections standards of practice and cover all aspects of digital collections management functions - data entry, interactions (loans, gifts, accessions), queries. User friendly user interface (UI) that assists with efficient and complete data entry and digitization workflows. Multi-discipline capable to be able to handle varied data composition and relationships of natural history disciplines. Feature rich - georeferencing and data visualization (mapping), web and IPT capable and compatible, web links to external resources, taxonomic and geographic authority files, pick lists, Linking of products - tissues to vouchers, hosts to parasites etc. Import capabilities for batch entry of records from Excel/CSV spreadsheets Report printing - labels, loan forms, accessions, reports Expense (software and maintenance). The expense of the software should be compared to the maintenance costs associated with data hosting - server and infrastructure cost and maintenance Operational costs Support
Link to Erika’s report (Power Point)
Security: cyber and building/facilities. Depending on the institution.
Morris 2005 - Relational database design https://www.dropbox.com/s/cwjl8u6e06a9upw/Morris%202005%20-%20Relational%20database%20design%20and%20Biodiversity%20informatics.pdf?dl=0
