Open Data

Structured data, and machine readable, publically accessible
Dan Monafu
February 10, 2016

Open data is data that is structured and machine-readable, freely shared, used and built on without restrictions (open.canada.ca). As a building block of open knowledge, open data promotes a robust and accessible commons, and interoperability is maximized by allowing for efficient combination or “crosstalk” of multiple datasets from multiple sources.

Releasing open data can produce results like increased accountability and more efficient reporting, and using open data can lead to impact by:
  • Deepening understanding of issues through combining datasets and visualization relationships (e.g. LuminoCity; Landscape; Use of CRA's T3010 datasets, Ofsted Dashboard).
  • Motivating the skills exchange and collaboration processes amongst open data generators and/or users like government, stakeholders and interested parties (e.g. Opendatabook.club; ConnexitéMontreal; Challenge.gov; CODE).
  • Enabling innovative solutions that can enhance government service delivery and people’s lives (e.g. SkillsRoute; MoveMaker).

Advantages

  • Generates insights that otherwise require significant coordination between many stakeholders (e.g. data visualization engines facilitate pinpointing and findings of interest).
  • Low barrier for use given proliferation of open source tools allows for this data to be rapidly used, leading to unpredictable, unforeseen results.
  • Multi-purpose value leads to different insights depending on the user/reader (e.g. insights provided by use of CRA’s T3010 datasets vary in value between non-profit sector, government and other funders).
  • Creates feedback loop to understand demand for different datasets and re-use patterns.
  • Small businesses and citizens can develop resources which make crucial improvements to their communities (Open Data Institute).

Limitations

  • Won’t solve problems directly, but it will connect the dots to identify gaps and opportunities - a follow-through plan is necessary to reap benefits.
  • Can’t replace service delivery though the development of application programming interfaces (APIs), but instead can enhance services and fill gaps.
  • Without a follow-through plan, don’t rely on in-person collaborative gatherings (e.g. unconferences, hackathons, design-jams) to have long-lasting outcomes that are any different from information exchange conferences.

Policy Opportunity

  • Advances collaborative problem-solving by empowering public participation and insight.
  • Streamlines information availability for internal policy-makers by reducing, which reduces internal workload as internal information requests are fewer.
  • Better-informed stakeholders lead to better-informed stakeholder consultations.
  • Cross-sectoral collaboration and external thinking can generate unexpected, but resilient solutions that can’t be pre-empted.
  • Brings together the tech, design, community and policy sectors to collaborate and build new solutions together (e.g. hackathons or appathons).
  • Leverages existing data, design and IT expertise to build innovative tools that roll-up and visualize data in specific, and/or across complementary, knowledge domains (e.g. funding data for youth programs).

Considerations

  • Requires staff with moderate digital skills to manipulate and transform data into new information tools (e.g. data management; data visualization).
  • Leadership’s willingness to open up datasets that are high-value for stakeholder communities.
  • Viable apps, tools or prototype product built from a development challenge (e.g. hackathon; appathon) will require follow-through support to meet their potential (e.g. access to public servants for further development; funding).
  • Willingness to accept role as informant to activities being pursued by others, rather than as funder, convenor, decision-maker, etc.
  • A life-cycle approach will need to applied for any data released, i.e. open data needs to be refreshed periodically, any errors in the dataset need to fixed, etc.

Government of Canada

  • Landscape hosts some federal departments' Proactive Disclosure of funding data for ease of access to funding information, and informs policy development and prototyping options.
  • Open Data for Development Challenge (Department of Foreign Affairs, Trade and Development) was a two-day event, part codefest and part policy conference, designed to attract programmers, policy makers and subject matter experts to explore questions around open data and international development.
  • Canadian Open Data Experience (CODE) (Treasury Board Secretariat) is a 48-hour appathon, inviting developers, graphic designers, students, and anyone interested at trying their hand at coding to use open data from the Government of Canada Open Government Portal. Using open data sets, participants developed app prototypes, including these ideas for 2014 and 2015.
  • Brainstorming Settlement Solutions (Immigration, Refugee and Citizenship Canada) brought together newcomers, experts in information and communications technology, the settlement sector, and policymakers to discuss barriers to settlement; learning lunch on open data and data visualization for new skill introduction; co-design potential solutions as “pitches”; and published information used by attendees on padlet.

Best in Class

  • Data.gov is a U.S. federal open government data site. While Data.gov/impact maps out and demonstrates how using open data can produce impact on particular issues, Data.gov/applications helps people make informed decisions (e.g., choosing financial aid options for college, finding the safest consumer products and vehicles).
  • Data USA (Deloitte, Datawheel, and Cesar Hidalgo, Professor at the MIT Media Lab and Director of Macro Connections) seeks to understand critical issues facing the United States, and to inform decision making among executives, policymakers and citizens. It gathers detailed information about towns, cities and states; occupations; industries; and education and skills.
  • Ushahidi has designed platforms for users to create open source crisis maps after a disaster. For instance, it was used by rescue teams during the 2010 Haiti earthquake to identify where help was the most needed, based on mainstream and social media, including tweets and SMS texts from people in Haiti.
  • In Nepal, data can be used as a tool to enable governments, donors and other actors to allocate financial resources more effectively to improve development outcomes.
  • Landscape by PoweredbyData /AJAH organizes open funding data from funders into a searchable and mapped website; allowing for governments and community organizations to better understand what is (and is not) being funded.
  • Le Connexité, led by OpenNorth, uses a collaboration process and data to develop projects to respond to real local challenges.
  • Citymapper takes data from transit authorities and the public sector around the globe to make cities easier to use and ‘reinvent the transport app for the world’s most complicated cities.

Sources

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