Assessment Framework (Start)

	A	B	C	D	E	F	G	H	I	J	K
1		Definition (loose) of Assessment Case Area	Recommendations on how/why to assess the following metrics:	Completeness (obligations of fields; required or recommended; data retrieval)	Accuracy (correct use of the field; appropriate values captured; correctness of the data)	Conformance to expectations (use of standards and standard data formatting; obligations for fields are fulfilled)	Consistency and Coherence (field values are normalized as applicable; fields are used consistently across instance data)	Accessibility (metadata allows multiple access points vis-a-vis language, shared understanding of concepts, indication of accessibility standards followed, or other)	Timeliness (Currency of the data captured)	Normalization and Enhancement	Provenance

2	Migrations or Data Sharing	Assessment work done to support or enable the sharing, lossless conversion, or migration of metadata and data between data systems, standards, and repositories.
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4	Validation	Work to support the process of checking that data and metadata, determined or indicated to follow a certain standard, profile, schema, or other meta-vocabulary, conforms to the defined structure, usage, and expectations. This work can be used as part of assessment for a variety of purposes.
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6	Targeted Enhancement	Given that many data and metadata projects have a large number of cleanup needs, but also limiting staff time, expertise, or availability, this area of work covers the assessment cases that support targeted metadata and data enhancement work. This includes assessing metadata for areas of work that are at the intersection of the most impactful according to the needed repository, but also the most efficient to perform normalization or enhancement work on given the resources available to do so.
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8	Profile Generation	A Metadata Application Profile is a resource that defines the expected, recommended, and optional fields, as well as their proposed values sources and standards, for metadata and data used in a particular data application - whether it be a repository, an aggregated service, a data pipeline, or other. The generation of such a profile makes clear for internal and external users (machine and human) of the data and metadata what is captured, what is described, how it is described, and what should be expected - all important questions for assessment work of instance data.
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10	Standards Choice	Assessment of existing metadata and data can lead to work on normalization, enhancement, capturing data expectations through profiles, or trying to target particular areas for further work. A key question through all of this is the decision of which standards - metavocabularies, controlled vocabularies, encoding options, formats, or other - best fit the current needs, the proposed needs, and the existing and proposed instance data.
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12	Handling Emerging Object Types	Assessment of data and metadata often leads to surfacing the needs of special or unique types of materials that either are not sufficiently captured for current data usage, do not fit well within existing profiles, normalization efforts, and chosen standards. This work area is for assessment to move forward on better choices for handling unique items or object types.
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14	Impact of Metadata Work	This is a broad area to both measure the impact of metadata in discovery or other systems (through analytics or other), as well as to link metadata assessment to other areas of work, such as training/reskilling.
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