What Is Open Data and What Are Its Benefits?

Jul 16, 2021 Ver este post en Español

Updated May 13th, 2022

Open Data is data that is available for everyone to access, use, and share. Moreover, it should be easy to share, as Open Data is only useful if distributed in ways that everyone can understand.

The concept of Open Data is not new, but it has become increasingly important to focus on making it accessible to everyone. This article discusses the benefits of Open Data and what makes data open (including discrepancies regarding Open Data). You’ll also see examples of Open Data and arguments for and against it. To conclude, we’ll also highlight how Orvium makes Open Data easily accessible.

Open Data Benefits

Open Data has many benefits when shared freely. Benefits can be specific and pertain to a particular category (cultural, scientific, environmental, governmental). Good Open Data:

  • Is available in a standard and structured format, so it can be easily processed
  • Can be linked to, allowing it to be easily shared and talked about
  • Has guaranteed consistency and availability, so others may rely on it
  • Is traceable back to where it originated, so others can know whether they can trust it.

If these requirements are met, benefits for researchers include:

  • Greater access to data - openly sharing research data provides benefits to the entire scientific community, academic circles, librarians, and more
  • The ability to build upon and create new research from publicly accessible data, enhancing the visibility of one’s research - sharing detailed research data has been linked to increased citation rates
  • The ability to verify and reproduce experiments - raw data can be used to explore new hypotheses, especially when combined with other readily available data sets (it becomes indispensable when developing and investigating research methods, software implementations, and analysis techniques)
  • Increased researcher authenticity and reduced academic fraud - data sharing not only encourages new perspectives but also helps identify researcher errors, discourages fraud, and is helpful in training new researchers.
  • Compliance with funding agency mandates and journal publishing policies - journal repositories, such as OpenAIRE, encourage submitting complete and detailed scientific data while abiding by the FAIR principles to ensure a standard structure. Additionally, these No-fee Open Access journals allow researchers to publish free-of-charge if an Open Access journal charges a fee too large.

The use of Open Data and Open Access is an integral part of Open Science.

What Makes Data Open?

Open Data is essentially research that is clearly communicated in a way that allows others to contribute, collaborate, and add to it all kinds of data and results made freely available at different stages of the research process.

The three most important characteristics of Open Data are:

  1. Availability and access - data must be available conveniently and modifiable, as a whole, and at a sensible reproduction cost (preferably downloadable over the internet).
  2. Re-use and distribution - data must be machine-readable and provided under terms that allow re-use and re-distribution, including the intermixing of different data sets.
  3. Universal participation - everyone must be able to use, re-use, and re-distribute the data. There should be no discrimination against fields, groups, or people.

Discrepancies Regarding Open Data

While there is a lot of excitement surrounding Open Data initiatives and their potential to transform modern society, an important distinction to make is that the currently available Open Data is only a fraction of what is needed. There is a discrepancy between the Open Data that exists, for example, in government portals, and public data. Governments need to start making more of their public information open. After all, it’s all of us who are paying for it.

In cases such as these, a significant limitation of Open Data is that it has not lived up to its potential because it only represents a small portion of what is available. The same issues exist for the scientific community as well. For Open Data to be as effective as predicted, the distinction between open and public data needs to disappear. Researchers and scientists should be further encouraged to share raw data, not succumb to the myths and fears associated with scientific data sharing, and follow the three characteristics of Open Data. Unfortunately, this isn’t always the case, further complicating Open Data initiatives in many sectors.

Examples and Uses of Open Data

Open Data initiatives are present at different levels. The total number of initiatives runs well into the hundreds, but below is a (small) list of the types of Open Data regarding specific subjects:

  • country-level open data,
  • city- and subnational- level open data,
  • Open Data by sector or topic (agriculture, environment, health, education, etc.)

You can find more examples here.

An example of open government data is the GotToVote tool. Initially started as an experiment, this data-driven tool sought to make data, otherwise government-locked, beneficial to the general public. Citizens could decipher and act on news-related stories by showing how national events, such as elections, affect them personally.

Read these Open Data essentials for more examples and uses regarding the environment, health, education, and more.

An example of an excellent resource for collaboration across multiple disciplines is Socrata, from Tyler Technologies. Socrata is a data platform that enables governments to use data as a strategic asset in the design, development, and implementation of programs. This enhances the flow and quality of Open Data, increases transparency, and encourages collaboration. Check out the extensive list of solutions for the different sectors of: public administration, courts and public safety, health and human services, education, and technology.Another example of a resource for Open Data is the UMMS digital repository and publishing system that offers worldwide access to scholarly work, research, and expertise from the University of Massachusetts Medical School. These data files include dissertations, theses, journal articles, and scholarly publications that must meet strict requirements for the dissemination of data. Benefits of sharing your data here include:

  • it’s free to use,
  • it supplies useful metrics to measure research impact,
  • includes sufficient metadata to enable discovery and re-use.

You can find more research resources here.

Arguments For and Against Open Data

There is a growing debate on the pros and cons of Open Data. The arguments made for and against Open Data depend highly on the type of available data and its potential uses.

Arguments for include:

  • public money was used to fund the research, so data (and results) should be made universally available,
  • Open Data allows for a smooth process of communal human activities and is an important enabler of socio-economic development (such as health care, economic productivity, education, etc.),
  • the rate of discovery in scientific research is accelerated by better access to data,
  • opening government data is a starting point to improving education, governments, and other real-world problems.

Arguments against include:

  • Open Data may lead to the exploitation of data in developing countries by rich and more well-equipped research institutes without further involvement or benefits to local communities,
  • privacy concerns may require limited access to data for specific users or data subsets,
  • sponsors do not receive full value if their data is misused, requiring quality management, dissemination, and branding efforts that often charge fees to users for best results,
  • there is no control over the aggregation of Open Data.

Summing Up

Open Data comes with its plethora of benefits and its fair share of challenges and limitations. We have discussed the benefits of Open Data, solutions (such as Open Data initiatives and engagement strategies), discrepancies, examples, and arguments for and against it.

Open means much more than being able to have access and read data and information. You know this from our data sharing article. Open means data has:

  • the right context to understand it,
  • the resources to replicate it,
  • the tools to collaborate and make data more useful.

Hopefully, we realize that Open Data plays a crucial role in economic growth, social development, cultural enrichment, and democratic empowerment. To read more about Orvium’s involvement in a more collaborative and Open Data future, take a look at our platform.


Antonio Romero

Led several big-data and ML projects for the R&D between CERN and multiple ICT market-leaders. His work accelerating predictive-maintenance and machine-learning solutions at CERN