**[NIH BISTIC Definition of Knowledge Environments]{.underline}**

Knowledge environments form the informational infrastructure necessary
for computation upon data. Such computation includes organized storage,
querying, federation, sharing, analysis, modeling, visualization, etc.

***A knowledge environment comprises the entire set of formalisms,
explicit definitions, and their relationships related to the data
computed upon.*** This includes, but isn't limited to: what the data
represent in the real world and what they are termed (vocabulary), how
those terms relate to each other (ontology), as well as models,
schemata, formats, and relationships among them.

Knowledge environments are important because digital data, tools, and
resources can interact and interoperate only when their knowledge
environments are shared, or when their knowledge environments can be
mapped (translated) among the different datasets, tools, and resources.

**[NIH BISTIC Strategic Principles for Developing Knowledge Environments
for Biomedical Research]{.underline}**

-   KEs should be developed for circumscribed, coherent research
    communities (e.g., communities defined by data types or other
    data-related aspects) -- not for all of biomedical research

-   The size of the community (and its information, data, and tool
    space) for which KEs are developed should match the resources
    available

-   KEs would be most useful to a research community that meets three
    criteria:

    -   It is well-poised to benefit by KEs (e.g., the community
        commonly uses digital data acquisition, uses informatics and
        computational tools, wants to share or rigorously compare data)

    -   There is a clear need for KEs in that community (e.g., as
        identified by the community at-large over time, by significant
        position papers, by funding agency)

    -   It is able and willing to participate in the development of KEs

-   KE development and implementation requires participation by domain
    scientists, tool and resource developers, professional societies and
    similar organizations, the publication enterprise, and the funding
    agency. Roles for these sectors may include:

    -   Domain scientists are the knowledge experts

        -   Provide leadership

        -   Senior thought leaders to identify key issues

        -   Junior substantive experts to work out details, curate, etc.

    -   Tool and resource developers

        -   Work with the domain scientists to implement KEs in software

        -   Work among developers to identify technical solutions and
            common conventions to improve compatibility and
            interoperability

    -   Professional societies

        -   Engage the research community

        -   Identify senior and junior domain scientists

        -   Solicit broad community input on KEs, their implementation
            and evolution

    -   Publication enterprise

        -   Encourage the compliance of publications with KEs

        -   Adopt conventions of the common KEs for publication-based
            resources (e.g., databases, etc.)

    -   Funding agency

        -   Provide organizational and logistical framework

        -   Provide funds for incidental activities

        -   Provide sanctions for use of KEs within a research community

        -   Promote the use of KEs across subdivisions of the agency and
            across agencies that are relevant to the research community

-   KE development and implementation are ongoing, long term, dynamic,
    and cross-cutting processes that should be resourced and managed in
    appropriate ways that provide ongoing evaluation, means for
    correcting direction, and support from across relevant funding
    units.