Data Communities defines a community as a social, religious, occupational, or other group sharing common characteristics or interests and perceiving itself as distinct in some respect from the larger society in which it exists. Communities are often associated with physical locations such as neighborhoods, cities, or states. However, societal structures can also create the common interest that binds the members of the community. For example, college alumni associations, political parties, or religious affiliations can also serve to define a community that transcends geographical borders. For that matter, a company’s network of suppliers and their network of partners/integrators serve as two distinct communities that serve different purposes within each community bound by a common interest. The operational rules that define the community can be quite loose (e.g. Red Sox Fans) or they can be quite stringent and tightly managed (e.g SAG-AFTRA). However, seldom is the word “Community” utilized to refer to a network of data producers and data consumers even though the data usage does create communities of interest-based on the nature of the data.

Data communities are specialized communities made up of organizations that have data and organizations that want data tied together based on an intent-driven use of the data. A data community can exist within an organization, for example, there can be teams of data producers and data consumers that want to simplify the way they locate each other, exchange data, and utilize the data to increase data effectiveness within the organization. Data communities can be formed by peer organizations that both produce and consume data in different areas so those insights can be drawn by comparing or aggregating data to uncover a macro-level view of the data. Data communities can also be created that link suppliers and subcontractors of a larger company or the distribution and reseller chains that carry products to market. Data communities can even be formed based on a data marketplace where buyers and sellers come together to utilize data that can answer ad hoc or sustainable data needs.

For these data communities to thrive, there must be a sustained level of trust between the parties. Trust is not something that can be mandated by a higher authority and it is not something that can be purchased. Yes, management may be able to dictate that parties exchange data, or incentives can be attached to encourage the exchange of data but these measures are never sustainable. Communities are not just bound together by the exchange of data but by the trust that binds the participants together. Trust must be earned. One of the best methods to create an environment of trust is through transparency and choice. Transparency requires that both parties understand the motivations of the other party. For example, in a data community, the party receiving the data must understand the data they are being given; and the party transmitting the data must understand how the data will be utilized by the other party. The parties also need to be cognizant of the fact that any exchange of data can be terminated by either party if that party feels let down by the other party. Such disappointments may be based on data that is of lesser quality than expected, if one party is perceived as being less than forthcoming in describing the use case, or a party fails to accurately disclose the level of protection the receiving party provides the data.

In business school, students are taught that to maximize the value of a relationship between two members of a community, the parties must be candid, honest, and willing to share relevant information. The same is true in a data community – benefits are maximized when data is shared freely between partners. Unfortunately, not all partnerships live up to these expectations. As a result, there is often a reluctance to share data between partners because fear of failure often outweighs the desire to maximize benefits. What is needed is a way to clearly document expectations while providing an easy way to rescind established agreements when the terms and conditions are not being adequately met. These are core concepts that drove much of the work of the I3 Consortium and led to the formation of I3 Systems.