The feedback loop is a process of collecting user feedback continuously and improving your product or service based on their opinions. In an open data context, we aim to establish effective connections between those working with the data (e.g. to reproduce the research), and those producing or entering the data at its origin (e.g. experimental setting). Connecting the data value chain may help to address some of the causes of poor data quality in the long-term.

Many feedback channels exist online: by publishing data on a platform like GitHub, users can request to update or make changes to the data to enhance the quality. Seeing who forks and contributes to the data provides better understanding of who is using data and how. Using bug tracking or forums, users can also submit requests for specific datasets. For example, see Project Open Data or COVID-19 Fallzahlen.

◎ Brainstorm

  1. Suggest one or two strategies for setting up feedback loops
  2. Discover and explore a new channel for engaging with data users
  3. Engage in at least one existing open data publication with a question or suggestion

Making the Most of Interim Assessment Data. Jolley Bruce Christman et al 2009

Contributed 3 years ago by oleg for Ready, Data, Open!
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