Posts Tagged ‘Stardog’

Stardog 2.1 Hits Scalability Breakthrough

Stardog LogoWashington, DC – January 21, 2014 – The new release (2.1) of Stardog, a leading RDF database, hits new scalability heights with a 50-fold increase over previous versions. Using commodity server hardware at the $10,000 price point, Stardog can manage, query, search, and reason over datasets as large as 50B RDF triples.

The new scalability increases put Stardog into contention for the largest semantic technology, linked data, and other graph data enterprise projects. Stardog’s unique feature set, including reasoning and integrity constraint validation, at large scale means it will increasingly serve as the basis for complex software projects.

“We’re really happy about the new scalability of Stardog,” says Mike Grove, Clark & Parsia’s Chief Software Architect, “which makes us competitive with a handful of top graph database systems. And our feature set is unmatched by any of them.”

The new scalability work required software engineering to remove garbage collection pauses during query evaluation, which the 2.1 release also accomplishes. Along with a new hot backup capability, Stardog is more mature and production-capable than ever before.

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The Business Value of Reasoning with Ontologies

[Editor’s note: this guest post was co-written by Héctor Pérez-Urbina (Clark & Parsia) and Juan Sequeda (Capsenta)]

Image of a human brain with computer data overlay.Important enterprise business logic is often buried deep within a complex ecosystem of applications. Domain constraints and assumptions, as well as the main actors and the relations with one another, exist only implicitly in thousands of lines of code distributed across the enterprise.

Sure, there might be some complex UML diagrams somewhere accompanied by hundreds of pages of use case descriptions; but there is no common global representation of the domain that can be effectively shared by enterprise applications. When the domain inevitably evolves, applications must be updated one by one, forcing developers to dive into long-forgotten code to try to make sense of what needs to be done. Maintenance in this kind of environment is time-consuming, error-prone, and expensive.

The suite of semantic technologies, including OWL, allows the creation of rich domain models (a.k.a., ontologies) where business logic can be captured and maintained. Crucially, unlike UML diagrams, OWL ontologies are machine-processable so they can be directly exploited by applications.

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“Semantic Hack” Hackathon Announced for Semantic Technology & Business Conference

Semantic Hack - June 1, 2013 at the Semantic Technology & Business Conference

What could you build if the entire web was your database?

A hackathon has been added to the agenda of the Semantic Technology & Business Conference. Semantic Hack, organized by and Diffbot, will be an opportunity for developers and designers to work with RDF, SPARQL, OWL, entity extraction, natural language processing, sentiment analysis, newly available datasets, and other semantic technologies that help make the web more readable, accessible and dynamic for humans and more interpretable by machines. Semantic Hack is free to attend and prior experience with semantics is NOT required to participate.

Registration is open, but space is limited. Hackathon organizers are currently seeking coaches and sponsors; those interested in either role should contact the organizers.

  • Who: Developers, designers, and others interested in semantic technology
  • What: A day-long hackathon to build applications that help further expand the semantic web, or demonstrate the power of accessible web data
  • Where: Hilton San Francisco Union Square
  • When: Saturday, June 1, 2013, 9am – 9pm

Current sponsors include Bosatsu Consulting, The National Center for Biomedical Ontology, Protégé, and Stardog.

Best Buy Releases ‘Like for Like’ Metis API

Best Buy has now released its previously announced “Like for Like” Metis API: “BBY Open and the Metis project team are excited to announce the release of our semantically-driven ‘Like for Like’ endpoint, available now for public consumption. Like for like functionality is defined as: “for any given game, software, or hardgood SKU, display the products most like it, ordered by the number of product attributes that match’.” Read more

Introduction to: Triplestores

Badge: Hello, my name is TriplestoreTriplestores are Database Management Systems (DBMS) for data modeled using RDF. Unlike Relational Database Management Systems (RDBMS), which store data in relations (or tables) and are queried using SQL, triplestores store RDF triples and are queried using SPARQL.

A key feature of many triplestores is the ability to do inference. It is important to note that a DBMS typically offers the capacity to deal with concurrency, security, logging, recovery, and updates, in addition to loading and storing data. Not all Triplestores offer all these capabilities (yet).

Triplestore Implementations

Triplestores can be broadly classified in three types categories: Native triplestores, RDBMS-backed triplestores and NoSQL triplestores. Read more

Stardog Meets SPARQL

Kendall Clark recently discussed what users can expect from Stardog next. Clark wrote, “The most pressing need in Stardog is support for SPARQL 1.1. We got stuck between the devil and the deep blue sea—trying to push the 1.0 release before the SPARQL Working Group was completely finished with the SPARQL 1.1 spec. We were motivated to avoid reimplementing any parts of SPARQL 1.1 because the spec shifted. So we decided SPARQL 1.10 for the Stardog 1.0 release. Then we told everyone that SPARQL 1.1 would be the highest priority item for the post-1.0 release cycle. And so it’s been.” Read more

Stardog 1.0.2 Released by C&P

C&P has released an update to Stardog, a NoSQL graph database. The article states, “C&P LLC, the company behind Stardog, today announced the release of Stardog 1.0.2. Stardog is a NoSQL graph database based on W3C semantic web standards: SPARQL, RDF, and OWL. Stardog is a key component in Linked Data-based information integration at Fortune 500 enterprises and governments around the world. The new release follows closely on last month’s launch of Stardog 1.0. The 1.0.2 release includes Stardog Community, a free version of Stardog for community use in academia, non-profit, and related sectors. Stardog is being used by customers in the areas of government, aerospace, financial, intelligence, defense, and at consumer-oriented startups.” Read more

Stardog RDF Database Bites Into Fat Part Of The Market

Clark & Parsia’s Stardog lightweight RDF database is moving into release candidate 1.0 mode just in time for next week’s upcoming Semantic Technology & Business Conference in San Francisco next week. The product’s been stable and useable for awhile now, but a 1.0 nomenclature still carries weight with a good number of IT buyers.

The focus for the product, says cofounder and managing principal Kendall Clark, is to be optimized for what he says is the fat part of the market – and that’s not the part that is dealing with a trillion RDF triples. “Most people and organizations don’t need to scale to trillions of anything,” though scaling up, and up, and up, is where most of Clark & Parsia’s competitors have focused their attention, he says. “We’ve seen a significant percentage of what people are doing with semantic technology and most applications are not at a billion triples today.” Take as an example Clark & Parsia’s customer, NASA, which built an expertise location system based on semantic technology that today is still not more than 20 million triples. “You might say that’s a little toy but not if you are at NASA and need defined experts, it is a real, valuable thing and we see this all the time,” he says.

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Attune Part II: Productivity Built on Semantics

“Attune is my favorite kind of semantic app: the kind where users can’t see the semtech, but it’s making life easier and better for them, and the developers, by being smart and flexible. We’re proud that Pancake has built Attune using Stardog as its RDF database.” – Kendall Clark, Clark & Parsia

Robert ButlerYesterday, in Part I of this two-part series, we learned about the new productivity application, Attune. Here in Part II, Robert Butler, president of Pancake Technology, tells us about the technology under the hood and why he chose to build Attune from the ground-up on top of Semantic Technologies. What Semantic Tech are you using?
Robert Butler: Attune was built on top of Stardog, Clark & Parsia’s new RDF database. All of the data, therefore, is stored as RDF data and we use Stardog’s intuitive native interface to update or create data. Queries are run using SPARQL. We have built OWL 2 ontologies for Attune, currently targeted at the QL profile. We plan to increase our use of ontology expressability, eventually using either EL or RL.

SW: Why did you choose Semantic Technologies rather than other options?
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Attune Part I: Productivity with Semantics (and Pancakes?)

Attune - keeping you in tune with everything you need.Pancake Technology, LLC has released a new productivity application called Attune and we caught up with Robert Butler, the company’s president (“The president of Pancake” — now there’s a job title I’m envious of!) to learn more about Attune and the semantic platform under its hood. In part one of this two-part interview, we learn about what users of Attune can experience now and what they can look forward to as the product matures.

Q: What is Attune?
A: Attune is a flexible and powerful personal productivity application, built to overcome limitations in current productivity tools. Attune allows you to create lists, notes, tasks and projects and relate them to each other.

Q: With a lot of productivity applications out there, what’s different here? Why did you create Attune?
Robert ButlerA: I have long been frustrated by the inflexibility of existing productivity tools. They almost always seem overly rigid and unable to capture the complexity of my thoughts and projects. My brain doesn’t always operate in terms of tasks and projects, which is why I often resort to note taking to capture my thoughts and why I like products like Evernote. If you are going to build a tool that can capture and remember the vast majority of information in the world, you need text and images. On the other hand, the goal of all the free-form text and images out there is to actually use it to get something done, which brings you back to the structure of tasks and projects. To our knowledge, there isn’t a tool out there that handles this duality well.

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