Metadata and Taxonomy Maturities
Metadata constitutes a concept that applies to electronically archived or presented data and describes the definition, structure and administration of data files with all contents in context, thus enabling the ready access and use of the captured and archived data.
Digital asset metadata provides information about one or more other aspects of a digital media file, such as its
- Means of creating the digital media file
- Purpose of the digital media file
- Time and date of its creation
- Creator or author of the digital media file
- Placement in a database
- Insertion into a compound document of rich-media object
Metadata typically entails structured and defined schema that may include metadata standards, metadata models, and tools such as controlled vocabularies, taxonomies, thesauri, data dictionaries and metadata registries.
Metadata types
No broad consensus exists as to types of metadata; however, most DAM practitioners accept the following types a workable guideline:
- Structural metadata that describe the structure of computer systems such as tables, columns and indexes.
- Guide metadata that help humans find specific items, usually expressed as a set of keywords in a natural language.
- Technical metadata that correspond to internal contents of the digital files
- Business metadata that correspond to external information.
- Process metadata that correspond to workflow and the status of a project or job
- Descriptive metadata is the information used to search and locate an object such as title, author, subjects, keywords, publisher
- Structural metadata that describes of how the author or composer organized the components of media object
- Administrative metadata that refers to intellectual properties, rights management, preservation, and records management
Evolving Maturity Model for Metadata and Taxonomy
The table below depicts a preliminary, still-evolving metadata maturity model and calls attention to the most common use of DAM systems, delivering a curated collection of digital assets.
Six Basic Types of Digital Asset Collections
Basic Collections | Identified Collections | Curated Collections | Faceted Collections | Componentized Collections | Semantic Collections |
|---|---|---|---|---|---|
| Entail file-folder hierarchies and pre-assembled collections using file manager of a desktop PC or server; meaning comes from the structure; uses infer meaning from project file folder and non-standardized file names | Represent categorized and tagged group of reusable files, generally finished digital goods or renditions of varying size or resolution; collections resemble "buckets" of potentially useful items with little ability to cull contents into more granular and relevant sets | Represent meaningful collections organized for known types to users to access; curation emphasizes quality-assured files and task-based use scenarios; most but not all curated collections manage vetted and approved finished goods and not work in process | Represent often sizeable groups of diverse sets of files, templates, reusable assets, and business records, optimized for a large, geographically distributed and diverse group of users to access; more than just a collection, this level integrates schedules and release calendars across many project teams, surfacing "coming soon" items | Organize an "atomized" set of media components, templates, and approved copywritten text, using XML standards for workflows (ADSL, XBRL, XPDL) to drive automated multichannel publications and outputs; often this requires a consolidated information repository for all business data or communications | Enable personalized presentations and user experiences, using customer personas and microformats to assemble and bind media and content components into personalized finished digital goods; semantic collections include assets residing in other DAMs, content managers, and social networking platforms |
In this model, Faceted Collections represent the a multi-dimensional view of digital assets, enabling very diverse groups of users to search and quickly find desired content or assets. Facets represent a role-, theme-, or function-based way of accessing a large collection and supports search optimization.
Review the Maturity Model for Metadata and Taxonomy of Digital Assets (new window)