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What is

Data Collaboration?

Collaboration where it is needed most

In today’s workplace, collaboration is quickly becoming a routine part of business. Google Docs enable us to co-write blog posts, Asana allows team members share tasks, and Jira helps developers work on code. 

 

In fact, collaboration seems to be happening everywhere except on the operational data that powers the apps and systems that support billions of people and millions of organizations worldwide. 

 

But why is collaboration not happening on data? 

Data: trapped in silos

Modern organizations use hundreds or even thousands of apps to maintain their operations. However, the challenge with apps is that each of them maintains a separate database (also known as a data silo) and so when we want to incorporate data from old apps when we build new apps, bots, and dashboards, we need to swap copies.

 

These copies are not only made between apps that a service provider manages directly, but throughout what could be described as a "data supply chain" of third party apps which can span multiple regulatory jurisdictions.

Data: fragmented by integration

The copying of data is known by IT teams as data integration, and it has become a time-consuming tax that is now carried out by virtually every organization in the World, including those that collect healthcare, location, and financial information.

 

Most technology leaders now consider data integration a necessary evil - it's an"innovation tax" that adds no value to employees or customers and only gets more complex with every new app that is bought or built.

For the people and organizations who contribute data to this process the real problem is that integration erodes the controls that protect data. This means that data is routinely exposed to people and systems that were never intended to gain access. This poses a huge challenge to the data governance policies and data protection regulations meant to prevent this from happening.

So what's the answer?

 

it is Mother Nature that provides us with the inspiration.

In nature, data is managed as a network

The design of the brain provides us with an architectural template for how we can collaborate on data while preserving ownership and control.  This miracle of nature not only enables each of us to manage more data than even the largest company on Earth but it does this without making copies of information. That's because the brain organizes information as a network.

 

In the brain, information is stored as a network of neurons and axons that allow us to manage a huge amount of information. This design, which is the result of millions of years of evolution, has recently been replicated in digital form as 'Dataware' technology which is already in use by some of the World's largest organizations.

 

By using this design approach, organizations are able to plug in data from their existing apps, databases, spreadsheets, machine learning tools, and IoT devices into a centralized network. Once connected, the data is instantly inter-connected, so that columns of data can be linked (much like the internet is used to hyperlink content between websites). 

 

This ability to link data has been the missing piece of the puzzle that was needed in order to support collaboration on operational data.

Networks support collaboration

As it grows, an organization's Data Collaboration network becomes a shared digital space where people, systems, and algorithms can all work simultaneously on real-time operational data that spans the entire organization and even its supply chain partners.

 

The primary benefit of collaboration is to accelerate the creation of data models that solve problems and power new experiences (browser-based, smart speaker-based), real-time systems, and automations. And because they are built without adding new databases or performing copy-based data integration, they can be delivered much faster and at far less cost.

 

This efficiency is the carrot for the adoption of Data Collaboration by service providers, but the real prize for consumers, citizens, and organizations is CONTROL.

Networks offer CONTROL

So how exactly does Data Collaboration support meaningful data ownership?

 

Well, when you think about it, eliminating unrestricted copies is already how we protect the value of things of value to society like business ideas (via intellectual property laws), currency (via anti-counterfeiting laws), and personal identities (via anti-fraud and identity theft laws). The same principles should apply to personal and organizational data.

Because there are no copies, every employee, partner, supplier, or end user who contributes data to a Data Collaboration network is able to set universal access controls which determine which 3rd party groups and apps within the network can view, edit, or query their information.

These access controls are embedded in the data itself rather than individual apps, systems, and automations, making these controls meaningful and universal in nature. 

 

True data ownership like this is only possible when we eliminate copies as the basis for data integration.

Data is a universal language

Building new digital services via Data Collaboration is a data-centric approach, and unlike code, data is a universal language. This means that a more diverse groups of people can start contributing to the solutions development process. 

 

In fact, with a bit of training in the Data Collaboration methodology and relatively simple data management languages like SQL we can unlock the potential of entire armies of students and mid-career professionals.

Data ownership: a work in progress

While the potential for Data Collaboration to advance control, efficiency, and inclusivity is incredibly exciting, it would be a mistake to assume that the shift from data silos to data networks will happen overnight. 

 

Similarly, it would be naive to assume that the citizens, nonprofits, and businesses who contribute data to digital service ecosystems have the time or inclination to manage access requests for the personal data which they can now control in a meaningful way.

 

Imagine if every digital service required its data contributors to set unique access controls - it wouldn't be long before they'd be setting hundreds (or even thousands) of such controls.

 

Perhaps the answer will be 3rd party "data access service providers", or ML algorithms that will adopt the role of "robotic custodian", or maybe organizations will use the Data Collaboration approach to earn enough trust to take on the role of our data guardian.

 

Either way, a lot of work remains to figure out exactly how data ownership will work in the real world.  As the futurist William Gibson once observed, "The future is already here, it's just not very evenly distributed." 

 

At the Data Collaboration Alliance, we're up for the challenge of making data ownership and inclusive innovation the new normal. 

 

Are you?