# Engaging Partners We designed the Civic Switchboard project around two strong convictions: First, **cultivating a healthy local civic data ecosystem depends upon the coordinated efforts of a variety of data intermediaries**. In other words, no single entity can effectively cover all of the necessary roles. Cultivating and strengthening data intermediary partnerships is a core objective of this project. Secondly, we believe in **the importance of local context. The variety of local civic data landscapes means that no single model can be made to fit every city or region**. This can be seen, for example, across the network of [National Neighborhood Indicators Partnership data intermediaries](https://www.neighborhoodindicators.org/partners/about-our-partners). Because each community’s civic data ecosystem is unique, the structure of local data intermediaries take different shapes. Proposing models for library involvement in civic data at the national level involves capturing a wide variety of successful local practices. Driven by these values, we begin our guide with a section to help you establish relationships that will lead to action. One of the first engagements you may need to make is with your own organization, about the relevancy and value of library involvement in civic data work. We offer strategies and examples of what has been successful in other places. Next, we encourage you to build on your ecosystem mapping to identify potential civic data partners for libraries. We give you a list of people and groups to look for, and guidance on how to talk with them about developing partnerships. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://civic-switchboard.gitbook.io/guide/engaging-partners.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.