Knowledge Engineering: Discovering Knowledge in a Sea of Information

Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information?

T.S. Eliot first posed these questions when The Rock debuted on stage in 1934. Nearly a century later, this quote remains applicable as we shift from the era of big data into the era of knowledge. We have more data at our disposal than ever before — and data growth is exploding. IDC suggests the global datasphere will grow to 163 zettabytes by 2025 — ten times the zettabytes generated in 2016.¹ Because of this, new engineering approaches are necessary to learn, infer, and reason about data without getting lost in the chaos.

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How to define knowledge engineering How recent advancements in artificial intelligence will facilitate knowledge engineering What this could look like when put into practice for publishers and those in the life sciences industry