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Graph Day - at Data Day Texas
Registration and full details at : http://datadaytexas.com/2019-graph-day-tx/news Originally conceived in 2012, Graph Day finally launched in Austin in January 2016. Since then, we've held Graph Day in multiple cities, like Seattle and San Francisco, but the crowds are always the best in Austin. So, for 2019, and possibly beyond, Austin will be the global home of Graph Day. As part of Graph Day TX 2019, we'll also be hosting the Knowledge Graph Summit (details forthcoming). Everyone is welcome Graph Day is an independently organized vendor-neutral conference -- bringing leaders from every corner of the graph community for a day of sessions, workshops, and the inevitable before and after parties. Previous speakers have included Emil Efrem, creator of Neo4j; Matthias Broecheler, Inventor of the Titan Distributed Graph Database; Marko Rodriquez, creator of the Gremlin query language and of Apache Tinkerpop fame; Ted Wilmes and Jason Plurad of the JanusGraph project; Luca Garulli creator of OrientDB, Claudius Weinberger, creator of ArangoDB; Jans Aasman, creator of AllegroGraph; and many others. Speak at Graph Day Graph Day seeks presentations and workshops related to the following areas: Property Graphs, RDF Graphs, Knowledge Graphs, Graph Query Languages, Graph Theory and Algorithms, Graph Analytics and Visualization, Linked Data, Ontologies, etc. We welcome use cases involving Neo4j, Titan, OrientDB, Tinkerpop, Gremlin, Giraph, and other tools/frameworks. Presentations are 40 minutes including Q&A. Workshops/Deep Dives are 90 minutes long. Case studies (not product pitches) involving multiple frameworks are especially welcome. http://datadaytexas.com/2019-graph-day-tx/proposals

AT&T Conference Center

1900 University Ave · Austin, TX

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What we're about

NY Graph is a place for people to learn about and discuss graph structures, graph theory, graph databases and related topics. We host technical presentations and lectures, product demos, lightning talks, seminars, town hall-style open forums and hands-on tutorials, in addition to less-structured monthly gatherings.

Why graphs? Why now?
Graph structures and methods are being used everywhere. As the size of datasets being generated, processed, and presented continues to grow, the relative strengths and weaknesses of different data structures, including graphs, have become more and more significant in everyday applications. Meanwhile, wider awareness of graph concepts (thanks in large part to the popularity of online social networks and widespread adoption of machine learning techniques) has increased the use of graph methods in a variety of fields. As a result, the last few years have seen renewed interest in academic circles, and a large number of companies and independent efforts putting a great deal of effort into creating faster, more scalable, and more reliable graph databases and ever more powerful interfaces.

Am I missing something? What are graphs?
The following Wikipedia entries provide a decent primer:
http://en.wikipedia.org/wiki/Graph_theory
http://en.wikipedia.org/wiki/Graph_(data_structure)
http://en.wikipedia.org/wiki/Graph_database

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