Written in Livemark
(2022-06-27 03:36)

What is open?

“Open means anyone can freely access, use, modify, and share for any purpose (subject, at most, to requirements that preserve provenance and openness).” (The Open Definition)

The Open Definition makes precise the meaning of open with respect to knowledge, promoting a robust commons in which anyone may participate, and interoperability is maximized.

Openness means permission in advance

Openness ensures people don’t need to ask/request first.
Free as in freedom; not just free food.
Openness means using an open license.

Un-examples of open data

An agency says they practice open data but you need to send a signed request letter first before getting access to the data.
An agency has an open data portal but the datasets aren't downloadable.
An agency releases open data but it can only be opened or used with proprietary software.
An agency releases open tabular data but in PDFs.

Does open mean free?

Yes but it may not be the kind of free that you are thinking of.

Free as in Freedom

The Open Definition matches that of open with respect to software as in the Open Source Definition and is synonymous with free or libre as in the Free Software Definition and Definition of Free Cultural Works. When we talk about free and open data, we talk about free as in freedom not just the free in free food.

Data is free and open because it gives you:

Freedom to access the data
Freedom to use the data
Freedom to modify the data
Freedom to share the data

One of the common misconceptions about open data is the fear that when an organization opens their data then it means people are free to modify that data and use it to misrepresent their organization. The freedom to modify data refers to a user editing a copy of the data to suit their needs (e.g. removing fields that aren't needed, adding new fields, computing averages, etc.). It does not refer to a user being able to modify the original copy of the data managed by the data source.

In fact, having the data open makes it easier to verify if someone is misrepresenting it because others can easily refer to the original data source for verification.

The Free and Open Adobo

The Free and Open Adobo is a common analogy I use in order to talk about freedom and openness. If you are given a Free and Open Adobo, it not only gives you the freedom to eat the adobo but also the freedom to study how the adobo is made, the freedom to modify the adobo to suit your taste by adding seasoning or changing the recipe, and the freedom to share the adobo with your neighbor. Your neighbor also gets the same freedoms as you and they will be able to change the adobo to suit their taste.

Imagine if we we aren’t allowed to change adobo but merely eat what is given to us. How boring would life be?

Why is openness important?

There are a variety of reasons why openness in data is important—from the philosophical to the practical and economic. Some of these reasons include:

Transparency - Data or it didn't happen. Open data can help fight misinformation by making sure that information that can be used to verify or debunk claims are readily available.
Accountability - Similarly, open data can help keep people and organizations honest and accountable to the claims and promises that they make. Open data can help build trust between different data actors.
Ease of use and innovation - It is easier to work with data that is already open than it is with closed data where the process of obtaining and securing the necessary permission to use the data is time-consuming. Open data also gives permission in advance to use the data which allows users to focus more on innovating and creating value from the data.

Data should not be thought of as a zero-sum game. More data for others does not mean less data for you.

How about you? What is other reasons can you think of?

Is it enough that data is open?

Although there are several ways to ensure that we make the most of the data that we open and share, most data practitioners will tell you that simply having open data is not enough. There are a lot of external factors that can affect how useful open data is and how much actual impact it has.

Additionally, our understanding of how data is used or can be used has evolved over the years and it is clear that open data is both simple and complex which poses unique challenges depending on the context where the concept of open data is used. In response to these challenges, we now have things like the FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective Benefit, Authority to Control, Responsibility, Ethics) principles of working with data and technologies such as Frictionless data that go beyond just open data.

Beyond open data »

« Data standards