Principles of Open Data Governance

It’s almost impossible to imagine modern life without data sharing. Big data is big business; data is at your fingertips every second of the day, with just a few short clicks on your smartphone or laptop. The World Economic Forum estimates that by 2025, 463 exabytes of data will be created daily.

Businesses and organizations need data strategies to properly manage their valuable data. Executive leadership teams use data to make important business decisions. Governments harvest data constantly and must manage who has access to it. But how is all this data managed, and what data standards are there?

The push for open data introduces more questions about privacy and security into the mix. As more data migrates to the cloud, businesses and governments must manage and regulate data, its security, and its accessibility. Open data governance (PDF, 3 MB) attempts to regulate these issues as society strives to build a more equitable world through access to information.


What Is Open Data Governance?

Data governance is the systematic management of public data from its creation to its storage, use, and disposal.

Open data governance has different meanings. Generally, it is a public operation overseeing data that is freely available to any user, anywhere. It takes this public data and determines a data governance framework for who has access to it.

Sometimes that means all the data is visible, while sometimes it means data access is individualized. And sometimes it means data is individually controlled. The scope of open data governance can change, depending on what people are using the data for.

How Open Data Governance Works

Open data governance operates within data governance frameworks designed by business units or governments. The frameworks include

  • processes to manage quality of data and mitigate any problems with the data,
  • identifying who owns the data,
  • creating a catalog of data,
  • protecting privacy of data,
  • enforcing an entity’s data policies, and
  • delivering data freely to the end user.

The frameworks help monitor and optimize data usage for individual privacy and information protection.

The Principles of Open Data Governance

In 2015 the International Open Data Charter wrote a guide on open data principles. The six principles are as follows:

  • Open by default: Valuable government information should automatically be accessible to everyone without compromising the privacy of individual citizens.
  • Timely and comprehensive: High-quality data should be released quickly in its original form.
  • Accessible and usable: Data should be easily searchable, without paywalls and in multiple formats.
  • Comparable and interoperable: Data should be available in globally standardized data formats with accompanying metadata.
  • For improved governance and citizen engagement: Freedom of speech and freedom of information must be protected so citizens can obtain data about government institutions.
  • For inclusive development and innovation: Data should be an equitable resource to aid in solving global challenges.

These aspirational norms form the basis of open data governance.

Why You Should Know about Open Data Governance

Open data governance is at the forefront of the third wave of open data, and using it responsibly is extremely important. Any mishandling of personal data could create privacy violations. Concerns about confidentiality breaches may lead organizations and individuals to fear sharing any data at all.

Data privacy norms, which have historically been understood as a sort of gentleman’s agreement between businesses and nations, morph and change. Privacy agreements vary among nations and cultures as well.

The enactment of the European Union’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) have heightened global awareness of the risks of personal data leaks. Stiff fines may be imposed for GDPR violations, running into millions of euros.

New developments in smart cities (PDF, 4 MB) offer a prime example. As city organizations and governments collect data from citizens going about their everyday lives, it’s increasingly clear that privacy and personal data may be at risk of misuse. This is especially true of data collected from surveillance and predictive policing (PDF, 869 KB).


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Open Data Governance Models

There is no single formalized open data governance model. Many international groups, think tanks, and governments have proposed models. Each has slightly different goals.

Different Open Data Governance Models

Among the myriad open data governance models, one model, advanced by the Web Foundation, starts with an overall management layer responsible for decision-making and funding of open data initiatives. This encompasses a legal layer operating within existing frameworks such as the GDPR and other freedom of information laws.

Next comes a technical and standards layer responsible for data infrastructure. Finally, there is a capacity-building layer in which officials and personnel make decisions about open data management.

Another example is the Open Data Model (PDF, 1 MB), which focuses on reestablishing and organizing lost institutional knowledge. All company data is then indexed to determine what data is available, where it is stored, how it got there, and how it is used.

Some governments, like the government of New South Wales (NSW) in Australia, create their own models of data governance. The NSW model relies on basic data management functions at the base. Pillars of leadership, a data-driven culture, workforce capability, and technology inform an overall data management strategy.

Commonalities among Open Data Governance Models

All these models require heavy buy-in from leadership to ensure organization-wide establishment of good data management practices. It’s critical that good data management practices filter down through the entire organization, potentially starting with a chief data officer.

Each model focuses on creating good infrastructure to track and manage data. And they take into account the end goals of how the information is disseminated and used.

Pros and Cons of Open Data Governance Models

An obvious benefit of open data governance models is that when everyone has access to the same high-quality, accurate information, they can make better decisions. Accessible data opens up new opportunities for economic and social advancement. Organizations can also be held accountable based on the data they output.

However, users can also misuse or misinterpret data. Governments including Greater Manchester (PDF, 964 KB) in the United Kingdom note that organizations have no control over what users do with open data once they access it. Additionally, more transparent information theoretically helps reduce corruption but also risks privacy breaches.

The cost of an open data project is another drawback. Starting an open data program could cost as much as €20,000 to €100,000, according to a report by Frederika Welle Donker. Plus, entire teams or organizations may need to be restructured to build a proper data governance workflow.


Open Data Governance Standards

While open data governance standards may vary depending on what group you are talking to, standards include providing high quality data and ensuring it is available to all. Different groups espouse best practices, but you must understand the ultimate goals of the organization first.

Key Goals of Open Governance Standards

The main goal of any open governance standard should be to hold the operation accountable. Did the data owner give carte blanche access to a certain subset of data? Then, what actually happened with the data? Did the user view it once, or did they copy it onto their computer? Were there any negative consequences?

Open data governance is how groups attain accountability and prevent privacy breaches and other unintended consequences. This continues to be a challenge as 5G applications develop.

Who Sets Standards for Open Data Governance

Standards differ between governments, businesses, organizations, and cultures. In the United States, for the most part, organizations have the right to collect data. In the European Union, data is owned by the data subject. This led to the development of the GDPR in the EU on data protection and privacy. Many Asian cultures may see data as belonging to society overall, and national privacy standards may be nonbinding (PDF, 5 MB).

It’s important to determine not only who sets the data standards but how neutral they are and whether they are tied to special interests.

Making data decisions public is a way to mitigate this problem. Persons with administrative access or super user authority should be scrutinized and their actions made public for everybody to see.

The Best Structures for Data Governance Programs

According to a white paper from the Data Administration Newsletter, the best overall structure for a data governance program consists of ten steps:

  • Determining a strategy (charter) for the team
  • Choosing a model for the data governance team
  • Choosing the decision-making hierarchy for the organization
  • Selecting a steering committee to direct data governance organization-wide
  • Creating a data governance office
  • Choosing a data governance working group
  • Choosing a data governance support team (data analysts and data owners)
  • Developing policies and how to enforce them
  • Establishing business and IT experts who know how the data is being used
  • Establishing an IT team to manage the data

Similar structures exist in various industries, including health care.


Open Data Governance Initiatives

There are many open data governance initiatives underway all across the tech landscape, from businesses to governments.

Responsibility for Current Open Data Governance Initiatives

In the public sector, providing open government data (such as census data) is a major data governance initiative. In 2019 the United States passed the Open, Public, Electronic, and Necessary (OPEN) Government Data Act regulating government data. The law requires that all nonclassified government data be automatically published under an open license.

Other international governments have similar laws, including the European Union.

In the private sector exist organizations such as OpenStreetMap. This group publishes maps showing not only street and location information but information critical to water and electrical boards and other utilities.

Stakeholders engaging in big data (PDF, 1 MB), including engineering firms, power utilities, and educational institutions, are also leading the charge on open data governance.

Goals of Open Data Governance Initiatives

The main goals of any open data governance initiative should be

  • accountability,
  • compliance with laws and regulations,
  • better data quality standards (making sure data is accurate and usable), and
  • transparency around what data is used for and why.

Initiatives should also follow the FAIR principles (findability, accessibility, interoperability, reusability). Each initiative must ensure the accuracy of the data available and present the distributor of the data as a trustworthy source.

Data should always be stored securely, and companies should have mechanisms in place to track who is accessing the data and how it is being used. Data quality can be cross-checked and made more accurate and consistent over time.

The ultimate goals should be for the quality of the data and its security to improve and lead to faster automation and accessibility of the data.

Factors Leading to Open Data Governance Initiatives

Today’s digital economy is one of the main factors leading to adoption of open data government initiatives. The Digital Economy Partnership Agreement (DEPA) signed by Singapore, Chile, and New Zealand in June 2020 is one of the first agreements tackling issues in digital trade. It expands the use of open government data to create new opportunities for small- and medium-sized businesses in these countries.

Other groups may struggle with knowledge silos. Establishing open data initiatives will eliminate these silos by making data readily available to all stakeholders.

Before undertaking any open data movement, organizations must consider security concerns and the potential for data breaches. Groups must consider how to sustain open data portals as well as ongoing data analytics (PDF, 382 KB).



In many cases, the open data movement produces more transparent governance and bolsters innovations in public information management. Open data governance produces long-term value for nations wishing to engage with citizens and improve socioeconomic conditions.

Yet there is still much work ahead to properly manage and regulate data assets and protect individual privacy as the world strives to make information accessible to all.

Interested in joining IEEE Digital Privacy? IEEE Digital Privacy is an IEEE-wide effort dedicated to champion the digital privacy needs of the individuals. This initiative strives to bring the voice of technologists to the digital privacy discussion and solutions, incorporating a holistic approach to address privacy that also includes economic, legal, and social perspectives. Join the IEEE Digital Privacy Community to stay involved with the initiative program activities and connect with others in the field.


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