Linked Data

PredictionIO Raises $2.5M for Open Source Machine Learning Platform

predChristopher Tozzi of The VAR Guy reports, “PredictionIO, the open source machine learning platform, has received a big boost with the announcement of $2.5 million in seed funding, which it plans to use to make its automated data interpretation and prediction platform widely available to open source developers. PredictionIO’s goal is to make it easy for developers and companies of all sizes to integrate machine learning —i.e., software that can interpret data intelligently to make automated decisions and predictions—into their products. ‘PredictionIO aims to be the Machine Learning server behind every application,’ according to the company. ‘Building Machine Learning in software will be as common as search soon with PredictionIO’.” Read more

LODLAM Training Day at Semantic Technology & Business Conference

LODLAM: LinkedOpen Data in Libraries, Archives, and MuseumsAmong the many exciting activities at the 10th Annual Semantic Technology & Business Conference (#SemTechBiz) is the partnership with the Linked Open Data in Libraries Archives, and Museums (LODLAM) Community. On Tuesday, August 19, 2014, LODLAM will hold a full day of trainings at the SemTechBiz Conference in San Jose, California.  Registration information is available here.

We spoke to Jon Voss, Co-Founder of the International LODLAM Summit, about the Training Day:

SemanticWeb.com: What is the LODLAM Training Day?

Photo of Jon VossJon Voss: The LODLAM Training Day is an all-day, hands-on workshop led by practitioners of Linked Open Data in libraries, archives and museums from around the world.

SW: What can people expect to learn?

JV: We’ve broken the day down into two sections, basically: publishing data and reusing data.  The first part of the day we’ll look at ways that libraries, archives and museums are putting massive amounts of structured data online for the public good, and what techniques and tools you can use to do it.  The second part of the day we’ll be looking at using this data in different ways, how to use SPARQL queries, how to build data into other mashups, how to use open datasets to improve your own data, etc.
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Introduction to: Linked Data Platform

Nametag: Hello, my name is Linked Data PlatformIn its ongoing mission to lead the World Wide Web to its full potential, the W3C recently released the first specification for an entirely new kind of system. Linked Data Platform 1.0 defines a read-write Linked Data architecture, based on HTTP access to web resources described in RDF. To put that more simply, it proposes a way to work with pure RDF resources almost as if they were web pages.

Because the Linked Data Platform (LDP) builds upon the classic HTTP request and response model, and because it aligns well with things like REST, Ajax, and JSON-LD, mainstream web developers may soon find it much easier to leverage the power and benefits of Linked Data. It’s too early to know how big of an impact it will actually make, but I’m confident that LDP is going to be an important bridge across the ever-shrinking gap between todays Web of hyperlinked documents and the emerging Semantic Web of Linked Data. In today’s post, I’m going to introduce you to this promising newcomer by covering the most salient points of the LDP specification in simple terms. So, let’s begin with the obvious question…

 

What is a Linked Data Platform?

A Linked Data Platform is any client, server, or client/server combination that conforms in whole or in sufficient part to the LDP specification, which defines techniques for working with Linked Data Platform Resources over HTTP. That is to say, it allows Linked Data Platform Resources to be managed using HTTP methods (GET, POST, PUT, etc.). A resource is either something that can be fully represented in RDF or otherwise something like a binary file that may not have a useful RDF representation. When both are managed by an LDP, each is referred to as a Linked Data Platform Resource (LDPR), but further distinguished as either a Linked Data Platform RDF Source (LDP-RS) or a Linked Data Platform Non-RDF Source (LDP-NR).

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Spiderbook’s SpiderGraph: Linking Datasets To Help You Sell Better

spiderpix1Startup Spiderbook, which is building a linked dataset of companies and their partners, customers, suppliers, and people involved in those deals, has recently closed its seed round for $1 million. The next-generation sales intelligence company was co-founded by CEO Alan Fletcher, who was a vp of product engineering, IT and operations at Oracle, and Aman Naimat, who has been working in the realm of CRM software since he was 19 years old and also has a background in natural language processing. Along with other core members of the team, the company puts natural language processing and machine learning technology to work to help sales people better connect the dots that explain business relationships, extracting information from unstructured text to sell more effectively.

State-of-the-art CRM, says Naimat, by itself doesn’t help salespeople sell. Since the days of Salesforce, which he worked on at IBM and Oracle, it has remained the same thing, he says, “just evolving with better technology. But basically it is an internal-facing administration tool to give management visibility, not to help a salesperson sell or create business relationships.”

Built from billions of data elements extracted from everything from SEC filings to press releases to blogs to Facebook posts, Spiderbook’s SpiderGraph is taking on that challenge, starting with the goal of helping salespeople understand who is the right contact to talk to, how he or she can meet that person (through shared contacts, for instance), and who competitors are, including those providing technology or other products already in use at the company. “We have created a graph of customers, competition, and suppliers for every company that is all interconnected,” he says.

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Add schema.org Actions to Your Own Knowledge Graph (Video — Part 3)

[Editor's note: this is Part 3 of a series. See Part 1 and Part 2]

schema dot org logoIn Part 3 of this series, Jarek Wilkiewicz details activating the small Knowledge Graph (built on Cayley) with Schema.org Actions. He begins by explaining how Actions can be thought of as a combination of “Entities” (things) and “Affordances” (uses). As he defines it, “An affordance is a quality of an object, or an environment, which allows an individual to perform an action.”

For example, an action, might be using the “ok Google” voice command on a mobile device. The even more specific example that Wilkiewicz gives in the video (spoiler alert) is that of using the schema.org concept of potentialAction to trigger the playing of a specific artist’s music in a small music store’s mobile app.

To learn more, and to meet Jarek Wilkiewicz and his Google colleague, Shawn Simister, in person, register for the Semantic Technology & Business Conference where they will present “When 2 Billion Freebase Facts is Not Enough.”

New Open Source Graph Database Cayley Unveiled (Video – Part 2)

Cayley Logo[Editor's note: This is Part 2 of a 3 part series. See Part 1 and Part 3]

Barak Michener, Software Engineer, Knowledge NYC has posted on the Google Open Source Blog about “Cayley, an open source graph database.”: “Four years ago this July, Google acquired Metaweb, bringing Freebase and linked open data to Google. It’s been astounding to watch the growth of the Knowledge Graph and how it has improved Google search to delight users every day. When I moved to New York last year, I saw just how far the concepts of Freebase and its data had spread through Google’s worldwide offices. I began to wonder how the concepts would advance if developers everywhere could work with similar tools. However, there wasn’t a graph available that was fast, free, and easy to get started working with. With the Freebase data already public and universally accessible, it was time to make it useful, and that meant writing some code as a side project.”

The post continues: “Cayley is a spiritual successor to graphd; it shares a similar query strategy for speed. While not an exact replica of its predecessor, it brings its own features to the table:RESTful API, multiple (modular) backend stores such as LevelDB and MongoDB, multiple (modular) query languages, easy to get started, simple to build on top of as a library, and of course open source. Cayley is written in Go, which was a natural choice. As a backend service that depends upon speed and concurrent access, Go seemed like a good fit.”

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How to Build Your Own Knowledge Graph (Video – Part 1)

Photo of Jarek WilkiewiczStraight out of Google I/O this week, came some interesting announcements related to Semantic Web technologies and Linked Data. Included in the mix was a cool instructional video series about how to “Build a Small Knowledge Graph.” Part 1 was presented by Jarek Wilkiewicz, Knowledge Developer Advocate at Google (and SemTechBiz speaker).

Wilkiewicz fits a lot into the seven-and-a-half minute piece, in which he presents a (sadly) hypothetical example of an online music store that he creates with his Google colleague Shawn Simister. During the example, he demonstrates the power and ease of leveraging multiple technologies, including the schema.org vocabulary (particularly the recently announced ‘Actions‘), the JSON-LD syntax for expressing the machine readable data, and the newly launched Cayley, an open source graph database (more on this in the next post in this series).

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Building The Scientific Knowledge Graph

saimgeStandard Analytics, which was a participant at the recent TechStars event in New York City, has a big goal on its mind: To organize the world’s scientific information by building a complete scientific knowledge graph.

The company’s co-founders, Tiffany Bogich and Sebastien Ballesteros,came to the conclusion that someone had to take on the job as a result of their own experience as researchers. A problem they faced, says Bogich, was being able to access all the information behind published results, as well as search and discover across papers. “Our thesis is that if you can expose the moving parts – the data, code, media – and make science more discoverable, you can really advance and accelerate research,” she says.

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Big Data Startup Roletroll Disrupts Job Search

roletroll

New York, NY, June 20, 2014 –(PR.com)– Former Wall St trader Adam Grealish launches Roletroll.com, a job recommendation engine for finance and tech jobs. The site uses unstructured data and statistics, collectively known as big data, to match users with jobs based on their unique skills and experiences.

 

Roletroll is a Brooklyn, NY-based start-up serving New York, Chicago and San Francisco. Job seekers upload their resumes, and computer programs do the job-search grunt work for them, aggregating jobs from multiple sources and identifying jobs that are a particularly good fit. Already Roletroll has scored over 5 million individual job matches. Read more

Semantic Tech Takes On Grants Funding, Portfolio Management

octoimageWhether the discussion is about public grants funding or government agencies’ portfolio management at large, semantic technology can help optimize departments’ missions and outcomes. Octo Consulting, whose engagement with the National Institutes of Health The Semantic Web Blog discussed here, sees the issue in terms of integration and aggregation of data across multiple pipes, vocabularies and standards to enable grant-makers or agency portfolio-managers to get the right answers when they want to search to answer questions, such as whether grants are being allocated to the right opportunities and executed properly, or whether contracts are hired out to the right vendors or licenses are being duplicated.

Those funding public grants, for instance, should keep an eye on what projects private monies are going to, as well – a job that may involve incorporating data in other formats from other public datasets, social media and other sources in addition to their own information, in order to optimize decisions. “The nature of the public grant market is effectively understanding what the private grant market is doing and not doing the same thing,” says Octo executive VP Jay Shah.

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