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About projects

Projects bring datasets together with documentation and analysis. This is where work and collaboration happen. A project, as the name implies, likely has a beginning and an end. Data in it is shared and analyzed, and insights are derived from the analysis and written up in the project.

Projects are where all querying, analysis and discussion of data takes place. Data in different datasets can be used for many different projects, but each project contains all and only the data that is relevant for that project. The information in a project can come from datasets, files attached directly to the project, insights written by the project's team members about the data and the project, and discussions about the project.

The biggest difference between a dataset and a project is that datasets can be linked to and included in projects, but projects cannot be linked to or included in other projects or datasets--nor can the files that are added directly to a project. With a project you can run queries against the data, analyze it, share it and create charts and visualizations from it.

Although you get an option to add files directly in a project, as a best practice, it is recommended that you create datasets and add files in them and not directly in a project. The datasets can then be linked to the projects.

Start with a question or task

Through hundreds of interviews with people who work with data, we have found that most work stems from a question rather than a particular set of data. It is the question that drives the search for relevant data, generating insights, and presenting reproducible findings, yet there hasn't been a great way to keep all your work in one place--not to mention collaborate easily with others on the project.

Projects help you to capture and share the most important aspects of your work as the project unfolds, even across multiple datasets, from question to conclusion.

With data projects you can:

  • Keep all project data in a single place by linking datasets or adding data directly in the project

  • Add people as contributors or viewers to your project and see the project activity stream.

  • Use the workspace to document, explore, query and chart any of the local or linked data and files.

  • Share and discuss insights

Sample projects on data.world community

Check out some of the following sample projects: