Connecting Data for Student Success
By 2020, some estimates place the total size of the digital universe at 44 zettabytes or 44 trillion gigabytes.
A small but significant fraction of all of this growth can be attributed to higher education, especially as more students enroll in online programs and administrative systems migrate to the cloud.
Locked inside that massive stream of data could be secrets to improving student outcomes, but some of the basic building blocks needed to help extract those secrets are missing.
The potential promise in all that data is enough to convince leading national higher education organizations to encourage greater collaboration around its use, and it is prompting efforts to revisit a federal ban on compiling student unit record information. It’s drawing the attention of major software providers, as well as prompting a veritable swarm of startups to dedicate time and resources to finding new and novel ways to tap into the flood of data.
The sheer volume of the data isn’t the only challenge, however. Tapping into data streams is much easier than it once was. Tools like IBM’s Watson are helping to make sense of all the ones and zeroes, but it’s still not as simple as snapping your fingers or clicking your heels three times.
Connecting data streams at the code level is an unsung skill that may not be sexy but is essential in the increasingly interconnected world.
To use an admittedly unartful example, suppose you live in a typical community with a typical set of fire hydrants in front of rows of typical houses. When needed, a call to the fire department will summon a solution to an evident problem — a fire.
However, for the fire department to effectively solve your problem, several conditions need to be present. Water needs to be flowing to the hydrants, hoses need to be equipped and perhaps most importantly, all of the pieces need to connect.
If the fire department shows up and needs to attach a hose to the hydrant to fight a fire, the connection at the end of the hose needs to match up with the attachment at the hydrant.
In digital terms, the problem is substantially more complex, in part because there isn’t a single type of hydrant with a single type of connection. There are thousands of types of hydrants with thousands of potential types of connection points, all of which need to be tapped to draw out relevant data.
A number of organizations, such as IMS Global, are working on standardizing the output formats, which is a critical part of the solution but just one part. Another critical component is the adapter — the part of the hose that attaches the hydrant.
These often overlooked elements can make all the difference between a successful data strategy and a complicated implementation and possible development failure. A robust library of adapters and connectors that support the quick transmission of data between systems could drive considerable efficiencies for institutions.
But these aren’t necessarily easy to build or maintain, and there currently is not a community dedicated to this specific challenge.
The DXtera Institute builds on the work of the National Digital Integration Advisory Consortium (NDIAC), convening like-minded institutions around the challenge of data integration while also providing a formal entity to coordinate the work of building an open-source library of connectors and adapters to support the easy exchange of data.
The DXtera Institute will also serve as a clearinghouse for information to support institutions in the use of the software as well as training and capacity-building for institutions looking to implement their own solutions.
In the rapidly expanding data ecosystem, the DXtera Institute may not be everything necessary to tap into the surge of data that’s already engulfing colleges and universities, but it may at least provide the right connections to take advantage of it.
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