Industry

The volume of published, scientific data is growing at an exponential rate. When carefully curated and paired with emerging technologies such as knowledge graphs, the data is a powerful catalyst to accelerate innovation across a wide range of disciplines.

For the past decade or so, Knowledge Graphs have been sneaking into our daily lives, be it through voice assistants (such as Alexa, Siri or Google Assistant), intuitive search results or even personalized shopping experiences through online store recommenders.

With the growing need for volumes of data required by ML and Knowledge Bases, copying/duplicating potentially Petabytes of data is a real problem. Working with data "in situ" is fast becoming the only viable pattern for enterprises.

Making sense of data using semantics, open domain knowledge and standards to reach for interoperability within the public sector
 

Machine Learning technologies have been used throughout the community and industry successfully for several years now. In this session we bring together technology experts and lawyers from different areas to discuss with us their digital success, experience, learnings and most especially vision for the future.

To make adequate decisions, businesses have to combine their databases - their own view of the world - with non-proprietary data. However, combining diverse data from multiple sources is a complex task.

A story about elephant and poachers. About rangers fighting wildlife crime. And about the role of semantics in all this.
A story also, about how high-tech companies are helping rangers to turn wild spaces into safe havens.
 

The Legal domain is complex in terms of underlying texts and language, amount of data and frequency of changes. Therefore, the process of designing a legal research solution becomes a more and more challenging task.