When Content Strategy Met The Semantic Web: Wolfram Leitner’s Work On Elevate Festival Media Archive

In a recent podcast with Joe Hiltzer of EK on the merger between Ontotext and Semantic Web company – passionate pioneers in the field of knowledge graphs and semantic technologies (https://open.spotify.com/episode/2f4VFlyABDvE3joQqbmeXm ), asked about what’s next in the field of knowledge graphs built with semantic technology and AI, Andreas Blumaer was laconic and determined: “We need to start cooking.” 

“There is no next big thing, there is the need to digest what’s hapenning and learn, and again understand what is content, what is knowledge, what is data? 

Andreas Blumauer

I liked that call to cooking by Andreas (who is now leading the department in Graphwise where I will work to help building the Graphwise Knowledge Hub) as this is enough said about digesting what we have been touting for so many years about the Semantic Web and enteprise data and content and rolling up our sleeves and getting to work. 

And this is exactly what Wolfram Leitner did. 

In this edition of the newsletter, I want to share about an envisioned Content Knowledge Graph, which goes from theory into the messy, challenging, and rewarding work of implementing Semantic Web principles within a real-world content strategy project.

The thesis is available here:  Leitner, Wolfram. Elevating Content : Examining the Concurrence of Metadata, Semantic Technologies and Content Strategy to Make Elevate Festival’s Media Archive Discoverable for the Public. 2024. 

Daring to Explore: Content Strategy Meets the Semantic Web

Wolfram’s research took on a bold challenge: bridging the gap between content strategy and Semantic Web technologies. His focus was solving a specific problem—making Elevate’s media archive easy to find, search, and access through their website.

To solve Elevate’s website content conundrum Wolfram chose to examine the intersection of content strategy and Semantic Web technologies and the potential application of interoperable metadata for content strategy technical challenges such as visibility and discoverability of content. 

Formally his research aims to find possible solutions for making Elevate media archive easy to search, find, access and discover through Elevate’s website. 

Throughout his work, Wolfram introduced and examined the field of the Semantic Web research and practice in order to find potential solutions to make Elevate’s content visible on the Web and more discoverable in the internal search of Elevate’s website.

“Throughout the 20 years of the existence of Elevate – Festival for music, art and political discourse, the hosted lectures, panels, interviews and performances from the event have been documented in the form of video recordings. These videos have been published on video sharing platforms, and could be either accessed from there, or could be viewed embedded in the respective event page in the archived version of each year’s festival website. Since a recent update, there are only a few selected videos available from each year’s edition. The extensive content of the festival’s history and the broad range of topics discussed in the discourse section cannot be searched for, found, accessed or discovered on the Elevate website. This thesis examines possibilities and potential solutions to utilize metadata and semantic technology to make the topically rich and important content of the media archive of the Elevate festival accessible and discoverable for the public. ”

Metadata and Findability: Connecting the Dots

Wolfram explored the basics of content strategy with a special focus on metadata. From there, he connected these principles with Semantic Web practices, illustrating how the two can come together to make content more accessible and easier to find.

His thesis also highlighted the importance of schema.org, showcasing how its vocabulary can improve content discoverability—not just within an organization but across the Web, of course.

Empirical Adventures: Building Practical Solutions

In theory, the link between content strategy and knowledge management with semantic technology is obvious. 

Yet in practice, every case is unique. As always.

For Knowledge Graphs to seamlessly power content operations we need more than creating the perfect design for content or for a knowledge Graph on paper. What comes into play are the practices of navigating legacy systems, persuading stakeholders, and building solutions when tools are missing—all while fostering an interconnected mindset.

Here’s where the work gets real. In the empirical portion of his research, Wolfram took on the challenge of applying Semantic Web principles in a content strategy project. He didn’t just theorize; he built a metadata strategy and even proposed a sample architecture for Elevate.

It is in the empirical part of the work that Wolfram did the hard part of devising a way to walk the Semantic Web talk in a content strategy project. Having argued that improved findability and discoverability of content are a matter of metadata well-managed, as an artefact of his study, Wolfram presents a metadata strategy, accompanied by a sample architecture of the technical solution.

On a very practical level, what Wolfram suggested as an assemblage in Figure 17: Metadata Level 2: Transcription, translation and search system (see Appendix 2 for larger version) would benefit from a paragraph explaining the conceptualization of the search function and also a short brief on how exactly metadata would enhance existing search for the users of the Elevate’s festival website.

Along the way, Wolfram had to balance the expressive potential of metadata with the technological maturity of existing systems. He presented the solution in several tiers, so that project-wise it becomes feasible. For example, his concept for a “Metadata Level 2” system tackles transcription, translation, and search in a way that could immediately improve how Elevate users navigate the festival’s archive.

Cooking with Knowledge Graphs: The Hard Work of Making Ideas Real

I really saw Wolfram’s work as one that lays the foundations of future research along that particular intersection, which is becoming more and more relevant for companies, especially with the uptake of GenAI and the need for solid, interoperable metadata to support any such project in a meaningful way.

That said, I didn’t save Wolfram the agony of answering several Million Dollar Questions, for example:

Are a data models related to user experience and if yes how?

What is the major pillar of RDF?

What intersections do you see between data and content modeling?

And of course these are not to be answered by one person, these are questions we are to find ways answering and using for the real cooking of the knowledge soup!

A delicious soup we all need  when looking to use semantic technologies to support content operations and user journeys.  

A Call To Dialogic Action:

Let’s keep cooking. Let’s turn more ideas into actionable solutions and build a future where content is connected, enriched, and easily discoverable with the help of a little semantics and a lot of change management puzzle-solving 🙂