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Open dataset

As explained in Data for All

Open data is data made available for public access, use, and reuse under stated terms.

Looking for a place to eat outside? A city’s public dataset might help you find one. An open dataset makes information available for others to access, use, and share, rather than keeping it within the organization that collected it. Openness is about the terms of reuse, not just whether a file can be viewed: a broad definition also allows people to modify the data, with requirements such as preserving attribution. section 6.5.5 section 6.5.1

Government data is an important source, but not the only one. Companies, individuals, and research organizations can also make data open. Public datasets can help people understand services, support research, and give businesses material for new applications. Transport for London, for example, provides feeds and guidelines covering travel and other city concerns; an estimate put the annual benefits and savings from its open-data releases at up to £130 million in 2017. section 6.5.1 section 3.6

Making data useful also means deciding what should not be opened:

  • Public-sector candidates include information about roads, jobs, building permits, and school lunch programs. section 6.5.4
  • Personal identity information, national-security data, and information that could disadvantage people or groups are excluded from the proposed government releases. section 6.5.4
  • Someone’s posts, transactions, or travel records do not become open simply because they exist. Whether data can be shared responsibly, and who can designate it open, matter. section 6.5.3

From a dataset to a decision

Chicago published a map of establishments offering outdoor dining. For someone choosing lunch, a government dataset becomes a practical guide. US government data.gov also links to open-data resources across different levels of government. section 6.5.5

Open data grew alongside open-source software and draws on ideas about managing shared resources. Its next question is one you can ask of any proposed dataset: who benefits from access, who decides what is shared, and how are people protected? Data commons and emerging approaches to individual data control extend that conversation beyond publishing public files. section 6.5 section 6.0 section 6.5.3

How Data for All covers it

How deep it goes
Defines access and reuse, then surveys sources, benefits, and exclusions without teaching dataset publication procedures.
Examples
Uses Chicago’s outdoor-dining map, government data portals, and Transport for London feeds as concrete cases.
What it assumes
Introduces openness through a plain-language definition and everyday examples rather than code or specialist techniques.
What you can do after
Evaluate/understand it by asking whether data permits reuse and whether its release protects personal information.
How it connects
Connects open datasets to open-source software, common resources, data commons, personal information, and individual data control.

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This explainer was generated by Manning's knowledge graph from the text of Data for All. The section links point to the parts of the book it draws on.