Knowledge Engineering and the Digital Transformation Journey – Part 2

Continuing our journey in knowledge engineering and digital transformation, we return to the Frankfurt Book Fair and Ixxus and Copyright Clearance Center’s discussion on the subject. Moving on from the factors leading to knowledge engineering success, they chatted about the next step in the process – creating a supply chain of information. Knowledge Engineering and the Digital Transformation Journey – Part 2

As companies start their journey to unearth value from their data and create a web of knowledge, they are embarking on a voyage of enterprise data science.

In the past, knowledge management efforts were focused on identifying what the data told us and its connections.

This still needs to happen, but today we no longer have to rely on databases or multiple ERP systems. Instead we now have multiple data sources and use abstracts of text. In publishing, the majority of data comes in this format – being able to mine, interpret and represent that is very powerful.

We also have the benefit of technologies such as machine learning and cloud computing. The former allows us to create systems that produce their own high level abstractions about the data they process, the latter allows us to build a wide range of systems and solve a variety of problems on demand.

Thanks to key market conditions, we are able to create a digital transformation program featuring key functions:

  • Information acquisition modules: absorbing information into the system
  • Analysis and semantic enrichment: identifying what the data says, how the data are connected and creating summaries of information from multiple sources
  • Integration: creating a continuous feedback loop to maintain quality of information (and an element of probability)

Probability may not sound great, but there’s nothing in life we can know with 100% certainty. In knowledge engineering terms, what we end up with is a probabilistic web of knowledge – not just looking at what the web of data tells us, but what it could tell us.

As companies invest more in value creation, enterprise data science will be the single most important differentiator between the leaders and laggards over the next 10-20 years. And most would agree, that’s a voyage worth making.


Date Published : 08th of November 2017

Steve Odart

Published by : Steve Odart

About the Author : Steve Odart is the founder of Ixxus, with 28 years experience in the publishing industry. He started life at the London College of Printing, following his grandfather into the printing industry. He spent many years working with Quark through its launch of Quark XPress, and the Quark Publishing System, before setting up a publishing division within one of the UK’s largest Sun Microsystems Resellers. He then joined Oracle, as EMEA Business Development Director – Publishing and Media, prior to founding Ixxus in 2004. Steve has an extensive knowledge of publishing past, present and future, and has worked with the majority of the largest global publishers in his career to date.