Crowdsourced Databases

adding economic incentives to data sets

Rlay adds economic incentives to databases to collaboratively work with others on datasets to improve their quality (data coverage, consistency, and accuracy).

Rlay is database-agnostic, so it works with postgres, blockchains, Neo4J, excel sheets, and most other ‘data storage’ formats that come to mind.

Why is this interesting?

Let’s look at Wikidata as an example. Wikidata is a public database that contains facts about our world, which are seen by millions of people, but struggles to monetize it as it rejects displaying promotional ads.

Rlay can enable Wikidata to capture the value it creates, by providing a read and write API to Wikidata, which the Wikidata team can control by defining rewards or costs for them.

In this example, reading is free while writing may return positive or negative ROI, based on the assigned function f( … )

Wikidata may choose, that reading is free for everyone (or only free for Wikipedia, etc), but establishes a market for writing. Everyone who wants to write has to pay — Wikidata’s income — while only some receive rewards — Wikidata’s expenses.

Now Wikidata can pay people who corrected misinformation, provided a substantial amount of new facts, or did other deeds Wikidata deems beneficial, by redistributing the income from people who wrote misinformation or other actions Wikidata deems not rewardable.

Maybe Wikidata may even take a cut to finance the operating costs of its database that way.

We refer interested readers who would like to know more how ‘misinformation’ can be detected, how exploitations can be prevented, and other important details that this simple example omitted, to our theoretical paper, which outlines general ways to solve these problems.

By creating a market, people have an economic incentive to improve Wikidata’s data quality, and as more people have an interest of providing more facts and correct mistakes, more readers will come and use it as a valuable, reliable information source.

Now writers would pay even more to insert their facts into Wikidata, as they can reach more people with their facts, such as ‘Company XYZ is operating in industry ABC’, which brings in more income through write-charging, which in return means, higher incentives for people to improve the quality even further.

Higher data(base) value, leads to more readers, leads to higher values for writers who want to reach the audience with their data.

In summary, Rlay is an early-stage open source project, developing an incentive layer and associated tooling, which enables new monetarization strategies for producing, improving, and maintaining the most valuable asset of our century: data.

If this sounds interesting for one of your products, please reach out, we are interested to hear how Rlay could help.

To get in touch, find out more, or contribute to it, refer to the following resources:

• m [ät] rlay’s website
• Rlay’s Website
• Theoretical Paper
• Documentation
• Github
• Twitter
• Use-Cases

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