NEW and FREE: eccenca announces the general availability of the Corporate Memory Community Edition. This master class provides the foundation of KG solutions based on the eccenca Corporate Memory platform. The platform covers the full lifecycle of KG applications. Our partners and experts love it...

The Shape Constraint Language (SHACL) is a W3C standardization for validating our semantic knowledge graphs by defining a set of constraints. By constraining RDF using SHACL we gain the possibility of exactly this—validating semantic knowledge graphs under a closed world assumption! This mastercl...

What are LLMs, why do they matter, and why we should care.

The core questions:

1. What are the possibilities of applications for large language models & where are the biggest hurdles?

2. How can people use them in everyday work or life, and where are there greatest opportunities for developin...

In this workshop, we learn how to link climate data in an S3 Parque data lake to an Amazon Neptune knowledge graph, using virtualization.

In this workshop we are going to use Wikibase (the software that runs behind Wikidata) to

1) construct a Knowledge Graph about the KG Conference itself,
2) construct a question answering system on top of it.

The goal of the workshop is to show how Wikibase can be used as an infrastructure ...

Reasoning has become an increasingly valued tool in the semantic web space, and yet to many it’s still a black box solution. Perhaps more tragically, despite the explosion of its development in recent years, many in the space still perceive it as a slow, cumbersome, and ultimately impractical tec...

Most large enterprises struggle to adopt knowledge graphs and semantic models given years of investments in legacy mainframe, relational database and data warehousing technologies. Because legacy data has been created and retained in source application schemas with zero semantic structure, the c...

The utility of knowledge graphs grows with the volume and the types of data that it integrates. The ability to acquire data from external sources is a key enabler for extended technical and business value.

Join this this workshop as we demonstrate and share practical insights on how to create an...

Attendees who take this Masterclass will come away with a completed semantically enriched Knowledge Graph.

Hands-on instruction will show how to build a Semantic Layer, including building a model, representing metadata with real business meaning, creating business rules, using inferencing to fi...

In this hands-on masterclass, we show how to do this with examples from RelationalAI’s Rel language. We also preview several other interesting tasks that use MLMs, such as semantic search and automatic labeling of features with concepts from an ontology. This combination of the formal and informa...

Graph Neural Networks have demonstrated incredible results in different domains where a network is present.
The workshop objective is to use the Yelp Dataset to create business recommendations for users exploiting the network composed of reviews, users, friends, tips, and businesses.
We will st...

Reasonable Ontology Templates (OTTR) is a language with supporting tools for representing and instantiating RDF graph and OWL ontology modelling patterns. It is designed to improve the efficiency and quality of building, using, and maintaining knowledge bases.

Wikidata is the largest collaboratively curated and open knowledge graph of the Wikimedia Movement. It contains general purpose data about the world, from the number of inhabitants of a country to who won the last Oscars to symptoms of a particular illness. It's data is used in technology you use...

This masterclass introduces core features and functionality of the KnowWhereGraph project (https://knowwheregraph.org/), an open, cross-domain knowledge graph and associated tool-set that aims to provide area briefings within seconds. KnowWhereGraph links over 30 data layers on social and environ...

Graph embeddings can be used for a variety of applications, including recommendation, fraud detection, and other machine learning tasks. In this work, we aim to walk through various different embedding techniques, starting with spectral approaches, moving towards graph neural networks, and finall...

This master class will contain international experts on knowledge engineering and will detail their experiences, lessons learned, and best practices in how they have and currently teach their students and educate their workforce on knowledge graph concepts. The masterclass will be implemented as ...

XSLT3 is a powerful tool for transformations, one that's often underutilized in the RDF space. However, the combination of SPARQL, SHACL and XSLT3 together provides a comprehensive tool for transformation of semantic content that can complement existing capabilities such as SPARQL UPDATE, enablin...

The tussle between graph databases vs. relational databases is misplaced and hinders wider adoption of graph databases. Many graph databases bring tremendous value, but at the cost of the bread and butter data management issues that relational databases are extremely good at. If the two can co-ex...

The ever-increasing number of published scholarly articles imposes significant challenges in organizing scholarly knowledge. We present the Open Research Knowledge Graph (ORKG), a scholarly infrastructure that provides scholarly knowledge as structured data stored within a knowledge graph. With i...

Attendees who take this Masterclass will come away with a completed semantically enriched Knowledge Graph.

Hands-on instruction will show how to build a Semantic Layer, including building a model, representing metadata with real business meaning, creating business rules, using inferencing to fi...

This masterclass will take participants through the analysis, loading, and querying of the Offshore Data Leaks dataset from the International Consortium of Investigative Journalists (ICIJ) into a single-node Dgraph cluster. The data set comprises over 2 million nodes and 3 million
relationships e...

Having a distributed and scalable graph database system is highly sought after in many enterprise scenarios. This, on the one hand, is heavily influenced by the sustained rising and popularity of big-data processing frameworks, including but not limited to, Hadoop, Spark and NoSQL databases; on t...

This masterclass will empower attendees to identify and detect quality issues in knowledge graphs, with methods inspired from linguistics, statistical modeling, and ontological analysis. By the end of it, they will be able to uncover key quality dimensions, typical causes of low scores in each of...

Knowledge Graphs drive modern data fabrics, enabling frictionless access to and sharing of data. They have led to great advances in terms of data integration, interoperability and accessibility, and are a key instrument for transforming data into valuable and actionable knowledge. But while the b...

Taxonomies should not be looked at merely as the extension of ontologies downward into subclasses and individuals; taxonomies can also serve as a source of creating ontologies upward. Ontologies are best designed with a combination of top-down and bottom-up approaches. Top-down involves designati...