2.1 Data as anti-rival

As we discussed in chapter one, digital goods are one of the best examples of anti-rivalry. Remember, for a good to be anti-rival, it must increase in value the more it is used. This means data is not always anti-rival!

Digital scarcity

Before we talk about how data can be anti-rival, lets briefly discuss digital scarcity. Digital scarcity refers to limiting who has access to digital information, goods or services. This is often done through software, subscription models, or access codes.
These are often artificially imposed limitations – a company puts a limitation on a digital good in order to increase their profit. For example, a video game may require an access code so that the company receives profit for its use. A statistics database may require fees to download the data, rather than making that data open-access.

Now let’s look at some examples of data as anti-rival.

Example 1: Industrial dataset
Fresh Food Inc. is a food production company that collects data on a number of factors throughout the food production process, from planting to final transportation to the grocery store. They decided to gather some of this data and sell it to Trucking All Day, a company that provides transportation services to a variety of industries. This interaction increases the value of the dataset for both Fresh Food Inc (who now has increased revenue) and Trucking All Day (who can combine the dataset with their own data for more informed decision making).

Example 2: USGS National Map
The United State Geological Survey is a scientific body of the US government that studies and collects data related to the United State’s landscape, natural resources, and threats to the environment. The National Map is a set of “public domain geographic base information” that provides information on boundaries, elevation, geographic names, land cover, structures and more. It relies heavily on data uploaded by civilians and universities.
Travis is a university student with an interest in geography. He decides to gather data on manmade structures in his small town in Arkansas. This data on its own is not very useful to Travis, but he uploads it to the National Map. Dr. Perez is a researcher at a university in California who studies the effects of air pollution on student achievement. Now that she has access to Travis’s data, she can see where schools are located and can analyze a new region. In Kentucky, Michael works for the headquarters of a restaurant company deciding where to place new Burger Huts. He uses Travis’s data to find the best location for a Burger Hut in his town.
These two very different uses show the value brought by sharing this data. For Dr. Perez, more value is brought by contributing to scientific understanding. For Michael, more value is brought to his company in terms of potential revenue.

Exchange vs. Sharing

When it comes to anti-rivalry, it is perhaps more helpful to think of value sharing rather than value exchange. In an interaction or transaction with rival goods, the limited availability of the resource often requires an exchange. I give you money, and in exchange I get a cup of coffee.

In an anti-rival system, we consider how the resource, and therefore the value, can be shared. By sharing data on a platform, the potential value is now available to everyone on that platform. We will discuss this concept a bit more in the next section.