Organization Specific Journeys
You can also choose predefined journeys for these specific organizations
Civil Society Organization
Do you support data collaboration for an international, national, or community-level civil society organization? These questions and considerations will be most useful for you.
Humanitarian or Development Organization
Do you use data to achieve humanitarian or development objectives? These questions and considerations can help support your work.
Do you lead a data collaboration portfolio at a large business or corporation? Your data responsibility journey starts here.
Do you help to drive data projects in the public sector, e.g. at a national statistical office? Start here to see the data responsibility questions and considerations most relevant to your work.
Are you the resident data steward at your small business or startup? Start your data responsibility journey here.
I do not wish to customize my journey.
Choose a Stage
Alternatively, you can also choose just specific stage of the joinery
In the planning stage, the project’s intended and expected value are identified. Goals and evaluation metrics are defined. Partners are identified and vetted. An adaptable plan is created to govern implementation of the data collaborative.
In the collecting stage, data is collected and verified according to needs of the data collaborative while protecting data subject privacy and adhering to regulations.
In the processing stage, data is stored, accessed, aggregated, and taxonomized for analysis and use according to the needs of the data collaborative.
In the sharing stage, operational aspects between partners are coordinated, trust is established and maintained, third parties are engaged if necessary, and data and/or knowledge is transferred.
In the analyzing stage, exploratory and targeted data analyses are conducted, algorithms are applied, and quantitative results are developed.
In the using stage, findings are framed and released to the public, actionable recommendations are developed, plans are implemented to retain or destroy data, and data collaborative performance is reflected upon.