In this era of information sharing and building collaborations through social technologies, learning environments are more “open” than ever before. The idea of openness as sharing and expanding resources has brought about a paradigm shift in many parts of society and especially in higher education. The last 10 years have seen significant advances, including such innovations as open educational resources and massive open online courses abound.
The movement has launched innumerable projects, with global implications.
George Siemens, a professor at the University of Texas at Arlington, created the idea of “connectivism,” a theory of learning that explains how internet technologies have opened up new opportunities for people to learn and share information across the web and among themselves. He argues we should pay more attention to managing knowledge and learning and emphasizes the importance of understanding where to find what we need to know rather than memorizing or otherwise attaining specific knowledge. Learning, connectivism says, is about connecting specialized nodes or information sources, and Siemens describes the flow of information within an organization as the equivalent of “the oil pipe in an industrial economy.”
Despite the analogy, the energy industry hasn’t embraced that flow of information. Across sectors – traditional oil and gas, electric generation and distribution, alternative and renewable energy and energy storage – the industry continues to treat its data as prized, and proprietary . It has not necessarily embraced the concept of data sharing.
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And energy is increasingly a data-intensive industry, reliant upon advances in artificial intelligence, robotics, data analytics and other techniques and technologies for everything from seismic analysis and subsea safety to carbon management and grid management.
With the proliferation of digital devices and sensors, IoT, or the internet of things, and devices across the value chain, data is being collected at an astounding rate in all aspects of the energy industry. For instance, a single producing oil or gas well generates over 3 terabytes, or 3000 gigabytes of data a day.
Sharing that data, in some form, could lead to increased efficiencies, improved safety and other benefits across the industry.
That’s not to say there aren’t legitimate business, regulatory and litigation risks associated with broad sharing of data. There are, and they have to be addressed. But an industry-accepted agreement about best practices from affiliated high-risk industries – including aerospace, automobile and health, in addition to energy – could identify mechanisms to share data without compromising the corporate entity.
Education and training is an obvious place to start. A recent report from DNV GL, an international risk-management company working in the global oil industry, found that the biggest challenge the energy industry faces in the coming digital transformation will be to find employees with domain expertise and digital skills.
So far, however, aside from a smattering of niche corporate-owned training systems, education and training in the energy field remain separate from the advancements in open educational resources (OER) and the proliferation of massive open online courses (MOOCs). Clearly, we need to bridge that disconnect, creating an alternate paradigm to advance education in energy-related topics that can rely on real-world examples and data.
That applies to in-house training, as well as both industry-specific certificates and general STEM disciplines delivered in universities and other institutions of higher education. As STEM educators get on board with data-sharing and open educational resources, or OERs, they can begin to develop a new cadre of digital native workforce, who will not only transform the energy industry but also be charged with advancing sustainable energy development globally.
That includes ensuring graduates have a broad understanding of how data is used, with deeper dives into discipline-specific areas.