Contribute Data

upload
dataset
register
repository
Contribute Data icon

Intent

Enables users to upload their work and data to a community managed repository.

This type of Task Flow promotes community sharing of research data / knowledge and is essential for growth & promotion of open science.

Overview

Guidelines for adapting the Task Flow

  • Determine the primary information required to identify a contributed dataset, and use this to display the contribution table to the user

  • Define the process of data contribution and the stages involved in the verification and acceptance of submitted data.

  • Group the data required from users into relevant categories and split the process into a small number of steps to keep the flow simple.

  • Give a progress indicator showing users where they are at in the overall flow.

  • The first step of collecting meta data and uploading files could get complex. Users may need to work on the this step over multiple sessions and would need a ‘Save as draft’ option.

  • Uploading files could take long time and running in the background should be supported.

  • Provide a review step to confirm user submission details.

  • Provide a status indicator to show users where they are in the contribution lifecycle (i.e. draft, in review, etc) and whether their dataset is currently public or private.

  • A dataset submitted to a community repository will need to be verified for quality control and it will likely take some time before it is published. Associate statuses with every submission to show users what stage the submitted dataset is at in the process.

  • Consider offering an automated validation step to check file formats, sizes, and any other basic data checks which can save time during further manual verification work.

Related Task Flows

Questions? Ideas? Looking to stay up to date?

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STRUDEL is an effort of the Lawrence Berkeley National Lab Scientific Data (SciData) Division UX team.
The project is generously funded by the Alfred P. Sloan Foundation, Liz Vu & Josh Greenberg Program Officers, grants #10074 and #10572