Add release and licensing policy page, adjust refs accordingly (#15)

New header with subpage for this page as project lifecycle will also go here

Author: egrace479

docs/wiki-guide/DOI-Generation.md

@@ -21,7 +21,7 @@ This is the simplest method for generating a DOI for a model or dataset since [H
     Though it is a very simple process, it is not one to be taken lightly, as there is no removing data once this has been done--any changes require generation of a ***new*** DOI for the updated version: the old version will be maintained in perpetuity!
 
 !!! warning "Warning"
-    As stated in the [Imageomics Data Policy](../Data-Policy.md), DOIs are not to be generated for Imageomics Organization Repositories until approval has been granted by the Senior Data Scientist or Institute Leadership.
+    As stated in the [Imageomics Digital Products Release and Licensing Policy](Digital-products-release-licensing-policy.md), DOIs are not to be generated for Imageomics Organization Repositories until approval has been granted by the Senior Data Scientist or Institute Leadership.
 
 Hugging Face allows for the generation of a DOI through the settings tab on the Model or Dataset. For details on _how_ to generate a DOI with Hugging Face, please see the [Hugging Face DOI Documentation](https://huggingface.co/docs/hub/doi).
 

docs/wiki-guide/Digital-products-release-licensing-policy.md

@@ -0,0 +1,39 @@
+# Digital Products Release and Licensing Policy
+
+To further the goals and motivations of the NSF grant supporting the Imageomics Institute, and to fulfill the requirements from the Data Management Plan (DMP) associated with the grant, all data, model, and code products generated or augmented under the auspices and support of the Institute should adhere to [FAIR principles](https://www.go-fair.org/fair-principles/). Datasets that include Indigenous data should also adhere to [CARE principles](https://www.gida-global.org/care).
+
+This means the following policy applies for digital products of the Imageomics Institute:
+
+1. All digital products (code, data, models, documentation, tutorials, etc) are to be released such that they are accessible to the public, at the latest by the time of associated paper publication, under an [Open Content](https://en.wikipedia.org/wiki/Free_content) license or terms of use.
+
+    - Educational materials are outside of the scope of this policy, but are encouraged to follow these guidelines nonetheless.
+
+2. Code is to be released under an [OSI-approved open source license](https://opensource.org/licenses/), or to the public domain (for example, by applying a [CC-Zero](https://creativecommons.org/publicdomain/zero/1.0/) waiver).
+
+    - This should be in a well-documented GitHub repository that follows the format specified in the [Institute GitHub Repo Guide](GitHub-Repo-Guide.md). 
+
+    - If associated with a publication, code should be versioned with a release linked to a DOI that can be referenced in the publication.
+
+3. Data, documents, tutorials, etc are to be released either to the public domain (for example, by applying a [CC-Zero](https://creativecommons.org/publicdomain/zero/1.0/) waiver), or under terms no more restrictive than requiring attribution (such as [CC-BY](https://creativecommons.org/licenses/by/4.0/)).
+
+    - For image and video datasets, this only applies to items that are not already licensed by (and thus used under license from) a third party.
+
+    - For datasets that include Indigenous data, see [Carroll *et al* (2020)](https://doi.org/10.5334/dsj-2020-043) and [Carroll *et al* (2021)](https://doi.org/10.1038/s41597-021-00892-0) for reconciling FAIR and CARE principles for scientific data.
+
+    - Datasets collected in whole or in part from regions that harbor Indigenous researchers are to at least adhere to the Collective Benefit principle (the *C* in CARE), even if they have been expressly released from or are otherwise entirely unencumbered by Indigenous rights. Specifically, at a minimum they are to be made available to respective Indigenous researchers with the least obstacles possible.
+
+    - For ML-ready datasets, for storage, version control, and sharing we recommend using [Hugging Face Dataset Hub](https://huggingface.co/docs/hub/datasets-overview), which provides for rich metadata description in the form of a [Dataset Card](HF_DatasetCard_Template_mkdocs.md). (See [Imageomics datasets](https://huggingface.co/imageomics) published there as examples.)
+
+    - Refer to the Imageomics [Hugging Face](Hugging-Face-Repo-Guide.md) and [Metadata](Metadata-Guide.md) guides for best-practices and further guidance.
+
+4. ML models are to be released under an [OSI-approved open source license](https://opensource.org/licenses/) or to the public domain (for example, by applying a [CC-Zero](https://creativecommons.org/publicdomain/zero/1.0/) waiver). In the case of potentially sensitive models or data (e.g., endangered species information), an Open [Responsible AI License](https://www.licenses.ai/ai-licenses) ([Open RAIL-M](https://www.licenses.ai/blog/2022/8/18/naming-convention-of-responsible-ai-licenses)) may be considered.
+
+    - For further guidance, consider the chapter on [Machine Learning Model Licenses](https://the-turing-way.netlify.app/reproducible-research/licensing/licensing-ml.html) from The Turing Way.
+
+    - For storage, version control, sharing, and publishing (including DOI provision), we recommend using [Hugging Face Model Hub](https://huggingface.co/docs/hub/models), which provides for rich metadata description in the form of a [Model Card](HF_ModelCard_Template_mkdocs.md). (See [Imageomics models](https://huggingface.co/imageomics) published there as examples.)
+
+    - Refer to the [Imageomics Hugging Face Guide](Hugging-Face-Repo-Guide.md) for best-practices and further guidance.
+
+5. All code, data, and models published on the Imageomics Organization ([GitHub](https://github.com/Imageomics) or [Hugging Face](https://huggingface.co/imageomics)) must be reviewed and approved by the Senior Data Scientist or Institute leadership prior to [DOI generation](DOI-Generation.md).
+
+    - Further guidance and resources to best adhere to Institute standards can be found in the [Imageomics Guide](../index.md).

mkdocs.yaml

@@ -111,6 +111,8 @@ nav:
       - "Model Card Template": wiki-guide/HF_ModelCard_Template_mkdocs.md
   - Command Line Cheat Sheet: wiki-guide/Command-Line-Cheat-Sheet.md
   - Code of Conduct: CODE_OF_CONDUCT.md
+  - Digital Product Policy: 
+      - "Release and Licensing Policy": wiki-guide/Digital-products-release-licensing-policy.md
   - Other Resources:
       - "Technical Infrastructure": wiki-guide/Technical-Infrastructure.md
       - "Virtual Environments": wiki-guide/Virtual-Environments.md