About Radian

Radian is a collaborative space for discovering, reusing, and remixing content related to data management, data visualization, data science, and data for the public good.

Using the PressForward Plugin, community editors will aggregate, curate, and discuss curriculum materials, research, best practices, and current events related to these themes. Radian will illuminate the data landscape by facilitating discovery and community building for researchers, librarians, data scientists, students, policy makers, publishers, and activists as they work to harness the power of open data.

The Radian community will be open and inclusive, with a diversity of voices reflected in the content we highlight. This vision will be realized through a global community of Editors-at-Large representing different perspectives, interests, and expertise, and the diverse venues of content we aggregate.

Our Team

Sara Mannheimer


Robin Champieux


Ryer Banta

Community Manager

Danielle Robinson

Community Manager

Scott W. H. Young

Web & UX Designer


We’re looking for experts and learners just like you to increase the discovery of the awesome content that you use and create. The workflow is straight-forward and built to leverage your existing browsing, publishing, and reuse practices.

Become an Editor-at-Large

Who: Individuals that are currently engaged with, creating, and “curating” content related to Radian’s content interests. This role is open to anyone that wants to participate, though we will have a plan recruit our base community, and a plan to grow and sustain its membership. Members will not be assigned to any particular theme, but we work to ensure that membership is representative across Radian’s content interests.

What: Editors-at-large will nominate connect for “publication” on Radian using the Press Forward bookmarklet and WordPress plugin dashboard. We want to leverage the browsing and curation individuals are already doing to inform themselves, demonstrate their expertise, and connect with peers. Editors-at-large will curate their nominations with Radian content categories and user generated tags that best describe the content. Editors-at-large can also nominate RSS content sources for Radian to ingest.

When: There will be no scheduled periods of commitment for Editors-at-large.

Nominate Great Content

Use the PressForward “Nominate This” bookmarklet to tell us about the great data related content you’ve read, used, or created.

Step 1. Install the PressForward Bookmarklet

  1. Log into the Radian site (which runs off of WordPress and may look familiar to some)
  2. From the left-side menu, select PressForward
  3. From the PressForward sub-menu, select Tools
  4. Drag the Nominate This button into your browser’s bookmarks toolbar.

Step 2. Find Great Content

Radian is community-curated hub for all things data.  We’re using the Nominate This bookmarklet to make it easy for you to tell us about the open access resources you’re using as librarians, researchers, data scientists, students, and activists.  Radian is cross-disciplinary, international, and multilingual.

Any open access, high-quality, and useful research, blog post, educational resource, news story, or other items related to data science, data visualization, data management, data policy, and applications of data for the public good are appropriate for Radian.

Content should be freely available to anyone worldwide, and ideally be licensed to allow for unmitigated reuse.  Note:  We’ll confirm the openness and licensing associated with nominated content before publishing your post.

Step 3. Nominate It!

  1. With your browser open to the content you wish to nominate, click on the Nominate This bookmarklet and a popup window will appear with both the title and copied content.
  2. If you are logged out of radiandata.org, you will first be prompted to login.
  3. Some sites will block PressForward and will not populate the textbox. In these cases add your editorial comments and we will select a small amount of text from the original to preview the content.
  4. At the top of the main content box, add a section entitled Editorial Comments and tell us why you think the content is noteworthy. Please include your comments in quotes.
    What do we want to know?  We’re interested in a few sentences that describe your take on the content’s significance, quality, and the kinds of communities that will find it most useful (e.g. students, librarians, researchers, community activists, etc).  Your comments will be published and attributed on Radian. Please don’t worry about updating the content or bibliographic data the bookmarklet generates, we’ll finalize this and format the content before the post is published.
  5. Optional:Check the box for “Nominate feed associated with this item” to nominate future posts from the item’s site to be considered for inclusion in Radian.
  6. Choose the Categories that apply – Data Management, Data Science, Data for the Public Good, and Data Visualization.
  7. Add or edit relevant Tags to describe the content and facilitate browsing.
    Separate tags with commas.  The following types of tags are highly recommended: language, keywords, and output type (e.g. article, book, data set, figure, tutorial, etc).
  8. Click on the Nominate button in the top right of the window.

That’s it, you’re done!

Tips on Choosing Content

Radian Themes

We are looking for great content related to these core themes:

  • Data Management
  • Data Science
  • Data for the Public Good
  • Data Visualization

Types of content

We want to amplify a wide variety of content types, including published articles, blog posts, technical tutorials, data sets, open educational resources, scholarship opportunities, job postings, and more.

Accessing and Licensing

Content should be freely accessible and ideally licensed for others to share and adapt, such as with an Creative Commons Creative Commons 4.0 International license. Note: We’ll confirm the openness and licensing associated with nominated content before publishing your post, so don’t worry too much about hunting these details down.

Credit: Information in this guide was adapted from the Idealis and Digital Humanities Now.

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