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Copy file name to clipboardExpand all lines: CONTRIBUTING.md
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## How to Contribute
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This project constitutes a collaborative work ("open source"). Federal employees and members of the public are encouraged to improve the project by contributing. For more information, please see [the faq](faq.md)
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This project constitutes a collaborative work ("open source"). Federal employees and members of the public are encouraged to improve the project by contributing. For more information, please see [the faq](/faq/)
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Contributions can be made, primarily in two ways:
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## Licensing
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By contributing to this project, you grant a world-wide, royalty-free, perpetual, irrevocable, non-exclusive, transferable license to all users under [the same terms under which the project is licensed](readme.md#licensing).
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By contributing to this project, you grant a world-wide, royalty-free, perpetual, irrevocable, non-exclusive, transferable license to all users under [the same terms under which the project is licensed](README.md#licensing).
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## Privacy
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All comments, messages, pull requests, and other submissions received through official White House pages including this GitHub page may be subject to archiving requirements. See the [readme](readme.md#privacy) for more information.
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All comments, messages, pull requests, and other submissions received through official White House pages including this GitHub page may be subject to archiving requirements. See the [readme](README.md#privacy) for more information.
Copy file name to clipboardExpand all lines: api-basics.md
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Since REST takes advantage of the same Internet mechanisms that are used to view regular web pages it has many advantages, resulting in faster implementations and easier for developers to understand. REST APIs allow you to take data and functionality available on your website and make these resources available through a Web API. Then, instead of returning HTML to represent these resources, the API returns data in one of two possible formats:
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*[Extensible Markup Language (XML)](http://apievangelist.com/buildingblocks/extensible_markup_language_(xml)
Developers can then take this data and use in web and mobile applications. However XML and JSON are easily consumed by spreadsheets and other tools non-developers can use as well, making APIs accessible by anyone.
Copy file name to clipboardExpand all lines: glossary.md
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### Parameter
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A special kind of variable, used in a subroutine to refer to one of the pieces of data provided as input to the subroutine. The semantics for how parameters can be declared and how the arguments get passed to the parameters of subroutines are defined by the language, but the details of how this is represented in any particular computer system depend on the calling conventions of that system. —*[source](http://en.wikipedia.org/wiki/Parameter_(computer_science))*
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A special kind of variable, used in a subroutine to refer to one of the pieces of data provided as input to the subroutine. The semantics for how parameters can be declared and how the arguments get passed to the parameters of subroutines are defined by the language, but the details of how this is represented in any particular computer system depend on the calling conventions of that system. —*<ahref="http://en.wikipedia.org/wiki/Parameter_(computer_science)">source</a>*
Copy file name to clipboardExpand all lines: implementation-guide.md
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## 1) Create and maintain an enterprise data inventory
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*[Due by 11/9/13]*
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*\[Due by 11/9/13\]*
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Maintain a complete listing of all datasets owned, managed, collected, and/or created by your agency, described in a common format.
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* Develop and communicate a clear path for listing newly created or acquired datasets into the enterprise data inventory.
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* The more employees who can contribute to the enterprise data inventory, whether by submitting feedback or by actually being able to log in and update listings in the agency DMS, the more accurate and complete your metadata will be.
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* While it may initially seem that maintaining your agency data inventory in a single spreadsheet is the simplest solution, this is often not the case. A central spreadsheet is difficult for more than one person to maintain, easily leading to errors and omissions.
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* In addition to the required [common core metadata](/schema), work with your agency and topical experts to develop an expanded set of metadata fields that make sense for your vertical. Many already exist; explore [Schema.org](http://www.schema.org) as a starting point.
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* In addition to the required [common core metadata](/schema/), work with your agency and topical experts to develop an expanded set of metadata fields that make sense for your vertical. Many already exist; explore [Schema.org](http://www.schema.org) as a starting point.
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* Your agency can and should use this central inventory listing as an internal search tool to increase awareness of data collections already in existence and to prevent duplicative research efforts. For example, a search of this inventory may reveal that the combination of two existing datasets could produce the results sought by a proposed new collection.
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## 2) Create and maintain a public data inventory
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*[Due by 11/9/13]*
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*\[Due by 11/9/13\]*
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Maintain a publicly accessible listing of all datasets maintained by your agency for harvesting by a central Data.gov search engine and the public at large.
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Document any datasets or metadata in your enterprise data inventory that your agency does not believe can be made publicly available, in consultation with your Office of General Counsel or its equivalent.
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Publish your agency’s enterprise data inventory, with the aforementioned information removed, to a file located at [agency].gov/data.json and described using (at minimum) the [common core metadata](http://project-open-data.github.io/schema/). This file itself must be listed as a dataset within itself (see [an example of format](http://project-open-data.github.io/examples/catalog-sample-extended.json) ); if you have multiple data.json files across your agency, include all of them in the top-level data.json at agency.gov/data.json.
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Publish your agency’s enterprise data inventory, with the aforementioned information removed, to a file located at \[agency\].gov/data.json and described using (at minimum) the [common core metadata](http://project-open-data.github.io/schema/). This file itself must be listed as a dataset within itself (see [an example of format](http://project-open-data.github.io/examples/catalog-sample-extended.json) ); if you have multiple data.json files across your agency, include all of them in the top-level data.json at agency.gov/data.json.
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While you could manually create this file in a text editor, it is recommended that you use one of the tools provided to generate this file automatically from your existing DMS or enterprise inventory file.
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### C) Best Practices and Examples
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* Using the [common core metadata](http://project-open-data.github.io/schema) to describe your enterprise data inventory makes it very simple to use that inventory for your public inventory.
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* Using the [common core metadata](http://project-open-data.github.io/schema/) to describe your enterprise data inventory makes it very simple to use that inventory for your public inventory.
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* A detailed and descriptive title, description, and set of keywords for each dataset is the difference between customers finding your data and no one finding your data. Since agency data catalogs are harvested and searchable on Data.gov, accurate and thorough metadata is the best way to connect customers with your data.
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* Consider including restricted and non-public datasets in your public data inventory listing. Remember that this file contains metadata about the data and not the data themselves.
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* When you include restricted datasets in your public data inventory, include specific information on how customers can request and qualify for access to those data.
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* Integrate your public data inventory with a tool for soliciting feedback from customers to avoid duplicative effort. For example, the [Kickstart WordPress plugin](https://github.com/project-open-data/kickstart) can automatically generate a voting and commenting mechanism from your data.json file.
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### D) Resources
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*[Common Core Metadata](/schema)
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*[Common Core Metadata](/schema/)
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## 3) Engage with customers to help facilitate and prioritize data release
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*[Due by 11/9/13]*
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*\[Due by 11/9/13\]*
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### Minimum Required for Compliance
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## 4) Clarify Roles and Responsibilities
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*[Due by 11/9/13]*
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*\[Due by 11/9/13\]*
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### A) Minimum Required for Compliance
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* Collect data electronically whenever possible.
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* Choose or build data collections tool that:
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- Export data in machine-readable formats. Consult [this list](faq.md) for suggested machine-readable formats.
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- Export data in machine-readable formats. Consult [this list](/faq/) for suggested machine-readable formats.
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- Use existing open data standards, if available.
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* Apply an open license, in consultation with best practices, to information as it is collected or created so that if data are made public there are no restrictions on the use or re-use of these data.
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* Collect the minimum amount of data needed to achieve your stated goals, in order to avoid having to remove additional personally-identifiable information later in the collection or release process.
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### A) Minimum Required for Compliance
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* Review information for privacy, confidentiality pledge, security, and other restrictions to release.
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* Make the data available in a machine-readable format. See [this list](http://project-open-data.github.io/faq.md) of commonly accepted machine-readable formats. Where appropriate, provide access to the data via an API.
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* Make the data available in a machine-readable format. See [this list](/faq/) of commonly accepted machine-readable formats. Where appropriate, provide access to the data via an API.
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* Post the data files in an Internet-accessible location, listing this location the dataset’s entry in your agency inventory listing.
Copy file name to clipboardExpand all lines: index.md
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Implementation guidance for open data practices.
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3-1 [U.S. Government Policy on Open Data](policy-memo/) - Full text of the memorandum.
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3-1 [U.S. Government Policy on Open Data](/policy-memo/) - Full text of the memorandum.
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3-2 [Implementation Guide](implementation-guide/) - Detailed descriptions and guidance for each step of implementing the policy.
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3-2 [Implementation Guide](/implementation-guide/) - Detailed descriptions and guidance for each step of implementing the policy.
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3-3 [Public Data Listing](catalog) - The specific guidance for publishing the Open Data Catalog at the agency.gov/data page.
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3-3 [Public Data Listing](/catalog/) - The specific guidance for publishing the Open Data Catalog at the agency.gov/data page.
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3-4 [Frequently Asked Questions](faq) - A growing list of common questions and answers to facilitate adoption of open data projects.
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3-4 [Frequently Asked Questions](/faq/) - A growing list of common questions and answers to facilitate adoption of open data projects.
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----------------
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6-7 [National Renewable Energy Laboratory API program](http://developer.nrel.gov/api-case-study/) - An agency perspective on developing APIs for general use and in particular building the case for the internal re-use of the resources.
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6-8 [USAID Crowdsourcing to Open Data](http://transition.usaid.gov/our_work/economic_growth_and_trade/development_credit/pdfs/2012/USAIDCrowdsourcingCaseStudy.pdf) - A case study that shows how USAID invited the "crowd" to clean and geocode a USAID dataset in order to open and map the data.
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6-8 [USAID Crowdsourcing to Open Data](http://transition.usaid.gov/our_work/economic_growth_and_trade/development_credit/pdfs/2012/USAIDCrowdsourcingCaseStudy.pdf) - A case study that shows how USAID invited the "crowd" to clean and geocode a USAID dataset in order to open and map the data.
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**For Developers: [View all appendices](http://github.com/project-open-data/) (and source)**
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