In a previous article, we explored ontology governance in metaphactory. Here, we'll explore new features that enable flexible and transparent governance and editorial workflows for your vocabularies, simplifying collaboration among multiple team members. Keep reading! 

Couldn’t make it to SEMANTiCS 2025 in Vienna? Our Community Growth Manager, Larry Swanson, was there soaking up the talks and hallway conversations with fellow semantic-tech enthusiasts. From real-world applications like ZEISS’s Service Copilot and IKEA’s evolving enterprise-scale knowledge infrastructure to recurring themes around the interplay of knowledge graphs and LLMs, Larry came back with plenty of inspiration and a few standout takeaways. Keep reading for the full report!

Discover how neural-network technologies like large learning models and generative AI work with symbolic technologies like knowledge graphs to give enterprises the trustworthy AI they need.

This article was previously published on the Big Data Value Association (BDVA) blog. 

We’ve attended The Knowledge Graph Conference (KGC) numerous times and yet we’re always delighted to find that each year brings a refreshing perspective to a long-standing yet quickly-evolving industry. In this article, our Community Growth Manager, Larry Swanson, shares his report of this year’s KGC, specifically noting two talks that underscored the human-centric theme that recurred throughout the conference. Keep reading for his takeaways!

Discover the Knowledge Graph & AI Hub, a global community for knowledge graph and AI enthusiasts, researchers and professionals—organized by metaphacts. 

In this article written for The Knowledge Graph Conference, we explore the two typical approaches for implementing an EIA and offer recommendations for how you can ensure a smooth transformation of your data environment. Keep reading!

This post has also been published on The Knowledge Graph Conference blog.

In this blog post, we recap a panel discussion from the HybridAIMS 2024 conference, which explores the impact the potential convergence of hybrid artificial intelligence and enterprise modeling could have on information systems.

From disconnected data silos to a unified, knowledge-centric organization—discover how two multinational organizations reshaped their data culture with a semantic model-driven Enterprise Information Architecture.

In this guest post, Michael Schäfer, IT architect and Division Lead Multicloud & Modern Work at Netlution dives into how semantic knowledge models enable efficient data collection, organization, and utilization to drive business success, as well as important considerations when assessing the IT operating model for an EIA solution.

In this article, Richard Wallis, a distinguished Linked Data and Semantic Web expert and thought leader, shares insights from the recent BIBFRAME Workshop in Europe where he presented a novel knowledge graph-powered solution created for a major national library. He also explores the common challenges that libraries currently face and the opportunities that technologies like linked data and knowledge graphs can offer for managing and connecting massive data volumes, as well as improving the experience for library users.

In this blog post, we’ll explore the importance of establishing policies and frameworks that govern the creation and management of ontologies within your organization. We also look at how metaphactory’s ontology management helps to facilitate proper governance.

If your organization doesn’t already have an enterprise information architecture in place—it should, and if you do have one, it should be based on a semantic model. In this article, we’ll explain what an “enterprise information architecture” is and how it can support your enterprise with decision intelligence, knowledge democratization and enterprise-wide optimization.

In this blog post, guest author Veronika Heimsbakk, knowledge graph lead at Capgemini, shares her approach to creating semantic knowledge models for clients. Read this guide to learn how she works together with clients to build semantic knowledge models from the ground up and discover practices you can apply to your own semantic modeling initiatives.

In this blog post, we talk about how we created a knowledge graph-powered out-of-box metaphacts Resource Hub that integrates with our content management solution. We also discuss how you can achieve a similar integration with your CMS while reviewing the KompAKI knowledge hub, as another example.

In this blog post, we’ll explore how to build a massive knowledge graph from existing information or external sources in a repeatable and scalable manner. We’ll go through the process step-by-step, and discuss how the Graph-Massivizer project supports the development of multiple large knowledge graphs and the considerations you need to take when creating your own graph. Keep reading!

In this blog post, we dive into how knowledge graphs play an important role in IKEA's recommendation systems, based on our experience attending two presentations by IKEA at the 2023 Knowledge Graph Conference.

In this blog post, we'll discuss the powerful knowledge graph-based solution that transformed NLB's library and resource management, and how you, too, can leverage these tools to support your organization's data-driven use case! 

This article is the first in a series of two where we discuss our perspective on what is considered a semantic knowledge graph, why it's important, and share how they can drive your enterprise goals forward.

The terms "ontology" and "vocabulary" are often used interchangeably. However, more often than not, this leads to confusion among customers who want to semantically model their domain and results in questions about whether there is in fact a distinction between the two and whether both are needed to implement a knowledge graph.

The meta-layers that these terms describe have been captured by different standards (OWL and SKOS respectively) and we at metaphacts believe that there is value in treating both as individual but complementary assets in their own right.

This blog post is co-authored by Felix Engel and Stefan Schlager. Felix and Stefan work for the department of Biological Anthropology at the University of Freiburg where they lead the development of AnthroGraph – an application that researchers can use to model anthropological data as knowledge graphs and intuitively explore, visualize and find information. In this guest post for the metaphacts blog, they explain how metaphactory was used as the development framework for AnthroGraph and how the resulting application can support the standardization of research data and the creation of reliable, curated and reusable collections of osteological research, ultimately allowing researchers to collaborate across disciplines and perform large-scale analyses.