GDPR: 4 letters, an acronym being a nightmare for many companies. For the first time companies are really required to manage their data storage, workflows, security processes and processing. This session is about how graph database can support a GDPR compliance assessment.

For the milestone of the 3.4 release, we’ve implemented a set of information retrieval features exposed via new database object View.

Recently similarity algorithms were introduced in Neo4j graph algorithms library, so I decided to show how easy it has become to infer a graph using Jaccard similarity and then run Community detect…

At linked data-driven companies you will find it difficult to distinguish between “traditional” data workers and those in other functional areas who, at other companies, are less reliant on data.

Recently I decided to teach myself #React and #electron so I built out a IDE for running traversals and visualizing results for @apachetinkerpop enabled databases. If you want to try it out you can get it here: https://t.co/Yb6eaF6HKo #graphDB #graph— Dave Bechberger (@bechbd) August 23, 2018

I usually mention both as unique/key features of RDF: global identifiers and zero-cost merge— Martynas Jusevicius (@namedgraph) June 8, 2018

Happening in March next year: the @w3c Workshop on Web Standardization for Graph Data.Mark your calendars and express your interest in participating!https://t.co/HbDEO3dxM4 https://t.co/PELY1dVkyT— Olaf Hartig (@olafhartig) October 15, 2018

The DBpedia Databus is a decentralized data publication and integration platform. Its mission is to provide global and unified access to knowledge. Read the interview on WordLift blog.

This case study shares how Refinitiv used ArangoDB to build a sophisticated Business Intelligence Platform.

We're introducing new features that help you resume tasks where you left off, keep track of ideas and content that you found useful, and get relevant suggestions of things to explore next.

TigerGraph has brought forward a free Developer Edition of its graph analytics platform for lifetime non-commercial use. But, please, what is graph analytics? As defined nicely here by Hitachi ...

Noam Chomsky, the outspoken and prolific linguist, cognitive scientist, philosopher and social critic, is the subject of the first public Knowledge Graph,

SAN FRANCISCO, May 2, 2018 -- Neo4j, the leading platform for connected data, today announced Neo4j 3.4, which includes horizontal scaling, performance

Learn the fundamental algorithms and theories used for understanding large-scale graphs and knowledge graphs.

Neo4j, DataStax Graph and Janus property graph schema design decisions for vertex and edge definitions.

Your business has its own language. If you sell cars, then you need not only make, model and year, but also MSRP, leather bucket seats and dealer incentives. Media companies have producers and writers, actors and grips, distribution networks and video masters. Business Language

You may have also noticed the emergence of 360° initiatives, letting you see how all the data within your organization relates to other data, and that it should also be possible to dig deep into your data systems to power natural language chatbots, dashboards, data analytics, and more

Graph analytics is a hot topic, but what does it mean? At the DC GraphTour, I learned the difference between graph queries, graph algorithms, and graph analytics. Next up: San Francisco GraphTour.

GDPR can offer valuable insights into your organization's overall visibility.

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AI is in its infancy and cannot be left unattended. Whether unintentional or by malicious design, algorithms behaving unexpectedly are now a fact of life.

An evaluator's task is to connect the dots between program goals and its outcomes. This can be accomplished through surveys, research, and interviews, and is frequently performed post hoc. Research evaluation is hampered by a lack of data that clearly connect a research program with its outcomes and, in particular, by ambiguity about who has participated in the program and what contributions they have made. Manually making these connections is very labor-intensive, and algorithmic matching introduces errors and assumptions that can distort results. In this paper, we discuss the use of ident...

Bye Bye Silos! Those who stay on their islands will fall back. This statement is valid on nearly any level of our increasingly complex society, ranging from whole cultural areas down to single individuals.

Earlier this year, we were fortunate enough to be contacted by Brian Keegan, Assistant Professor in Information Science at the University of Colorado Boulder, who specialises in the field of network analysis. Brian and his team were planning to mine the official biographies of every legislator pu

The O’Reilly Data Show Podcast: Fabian Yamaguchi on the potential of using large-scale analytics on graph representations of code.

There has been a recent resurgence in the area of explainable artificial intelligence as researchers and practitioners seek to provide more transparen…

From a talk at the Data Architecture Summit in Chicago in 2018--reviews digital transformation and what deep transformation really implies at the data layer. C…