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Incident response involving human responders requires context of systems and services that are encountering issues. Getting this context…

The final blog from the Synaptica team on the Stanford University course series on Knowledge Graphs. This week looked at open research questions.

Bob Kasenchak and Ahren Lehnert, Synaptica

Bob Kasenchak and Ahren Lehnert, Synaptica

Bob Kasenchak and Ahren Lehnert, Synaptica

The team continue their blogs on the Stanford University course on Knowledge Graphs. This week “What is the role of knowledge graphs in machine learning?”

We’re happy to announce the release of Stardog 7.0 Beta 2, complete with lots of changes designed specifically to help make the world’s best Knowledge Graph even more awesome.

Stardog, the leading provider of Enterprise Knowledge Graph technology, today announced the release of Stardog Sandbox, a free, hosted environment built to make knowledge graphs more accessible. Stardog Sandbox allows users to experiment with queries, mappings, and capabilities with no installation, setup, or configuration.

#DataManagement ‘useful fictions’ @StardogHQ @kendall @pymnts: Firms only exist to be the repository of a particular #data universe. Key that may differentiate Tier 1 bank from other banks: #data it has on hand, tied to specific operations, customers https://www.pymnts.com/data/2019/stardog-on-data-managements-useful-fictions/

Deploying Stardog Cluster on Kubernetes is a walk in the park. In this post we show you how easy it is and how it works.

GraphQL is going to eat most of the APIs, and SPARQL is for the hard stuff. They seamlessly interoperate in Stardog and we support both.— Stardog (@StardogHQ) November 26, 2018

/PRNewswire/ -- Stardog, the leading Enterprise Knowledge Graph platform, today announced the release of the first data model template compatible with the...

.@StardogHQ scores $9M Series B #funding to launch new product offerings, scale go-to-market initiatives. Stardog will expand its product offering to include #KnowledgeGraph as a Service, enabling hybrid #cloud environment #EmergingTech #AI #graphdatabase

market,” said Kendall Clark, CEO and Founder of Stardog. “We plan to expand our successful EU operations, strengthen our work in the public sector, and to develop tools and partnerships to broaden access to knowledge graphs.” Stardog’s Enterprise Knowledge Graph platform is used by industry leaders including Morgan Stanley, NASA, Schneider Electric and Bayer. Customers use Stardog for a range of solutions including operational resilienc

learning by itself is only half a solution.To explain this (and the relationship that graphs have to machine learning and AI), it's worth spending a bit of time exploring what exactly machine learning does, how it works. Machine learning isn't actually one particular algorithm or piece of software, but rather the use of statistical algorithms to analyze large amounts of data and from that construct a model that can, at a minimum, classify the data consistently. If it's done right, the reasoning goes, it should then be possible to use that model to classify new information so that it's consistent with what's already known.Many such system

While graph #tech #GraphDB graph computation will not be everything, true #digitaltransformation will only get underway once we begin building out #knowledgegraphs to mediate the hardest part of #datamanagement: integration #innovation #data #2020NewYear

data lived in files. End of story. The files likely had different formats because each programmer was essentially maintaining their own information, but on the flip side the only person who had access to that data was the programmer, and that meant that your data was safe so long as your programmer was trustworthy.Networks had also been around since the 1960s, since computers were expensive and it was simply not efficient to have one programmer per computer. This meant that different people would have access to the same computer at the same time, usually by computers temporarily swapping out one person's data and swapping in someone else's so they had a slice of time on the CPU. That data was persisted when not in use in magnetic core memory i

file contained a list of properties separated by a unique character. Each subsequent row contained the val

#knowledgegraphs differ from relational DBs primarily in how information gets stored. KGs consist of index holding at least three values: subject, predicate, object (triple). In typical triple stores, the index is the database. This has several advantages

Property graphs seem inherently simpler. Semantic graphs put more emphasis on #datamodeling, treat node/edges as concepts bound by a universally unique identifier #data #tech #knowledgegraph #EmergingTech #datamodel #datascience #software @kurt_cagle [LINK]https://www.linkedin.com/pulse/state-graph-merger-property-graphs-semantic-kurt-cagle [LINK]https://media-exp1.licdn.com/dms/image/C5612AQF2DIFR7DjXKQ/article-cover_image-shrink_600_2000/0?e=1585785600&v=beta&t=tN9Z8ZbE1VeNHiPvhdFfDi34VwHW_pOHXPWv7Il8f7Q

IMO there's no need to mix-in #SPARQL into #SQL. There's SQL/MED. Only few things are missing in standard SQL to query distributed #LinkedData: 1. HTTP endpoint 2. SPARQL SERVICE alike SQL keyw. Who helps proposing a spec. about this? @danbri Is @w3c the right place to do this?— Stefan Keller (@sfkeller) February 23, 2019

friendly and has detailed narrated examples designed to serve as a starting point for tasks.It’s a stellar package.If you’re familiar with StellarGraph, the release notes show all the improvements from 0.11 to 1.0.A gr

Google's new search quality evaluator guidelines are out, dated yesterday https://t.co/owM4OJHGGV— Stephen Kenwright (@stekenwright) May 17, 2019

A blueprint for the next @apachetinkerpop and an analysis on #opensource. @twarko @_mmadt #presentation from @DataDayTexas #GraphDB #data #tech #cloud #insight #softwareengineering #softwaredevelopment #AWS

For those of you who have been struggling through my series of posts on the TDWG Standards Documentation Specification, you may be happy to ...

TigerGraph is offering free Cloud and Enterprise Edition use for applications requiring massive data or high computation needs for Coronavirus research.

imec from Belgium. Semantic reasoning over streaming data Semantic reasoning with streaming data does not necessarily require specialised formalisms and tools. You can perform stream reasoning using Stardog with a relatively simple Python extension, which I’ll demonstrate below. Industry 4.0: Hello data Companies around the world are connecting their equipment, machinery and even people to the worldwide web. The Internet of Things (IoT for short) defines these connected things as smart devices, all of which are producing floods of data. This data has become a target for business intelligence and analytics to generate important business insights. However the raw data is often too opaque to process thus it has become a popular approach to annotate it with metadata and inte

proof data model. Marit explains knowledge graphs in detail, emphasizing that they can reduce training of machine models, allow new data to be input easily, and make analyzing unstructured data much easier. Knowledge graphs take data that would normally only make sense to humans and in effect tran

First data modeling is based on two assumptions. The first