If you would like your company to be considered for an interview please email editor[ at ]semanticweb[ dot ]com.

In this segment of our “Innovation Spotlight” we spoke with Andreas Blumauer, the CEO of  Semantic Web Company. Semantic Web Company is headquartered in Vienna, Austria and their software extracts meaning from big data using linked data technologies. In this interview Andreas describes some of the their core products to us in more detail.

Sean: Hi Andreas. Can you give us a little background on your company? When did you get started in the Semantic Web?

Andreas: As an offspring of a ‘typical’ web agency from the early days of the internet, we became a specialized provider in 2004: The ‘Semantic Web School’ focused on research, consulting and training in the area of the semantic web. We learned quickly how the idea of a ‘semantic web’ was able to trigger a lot of great project visions but also, that most of the tools from the early days of the semantic web were rather scary for enterprises. In 2007 we experienced that information professionals began to search for grown-up semantic web solutions to improve their information infrastructure. We were excited that ‘our’ main topics obviously began to play a role in the development of IT-strategies in many organizations. We refocused on the development of software and renamed our company.

Read more

Big Data and the Semantic Web are on a track to intersect. And businesses that want to be on track to profit from the explosion in data should start looking a little more closely at that intersection, and soon.

“We’ve got more data now than ever before coming at us, and it is coming faster and faster,” says Frank Coyle, director of the Software Engineering program in the Lyle School of Engineering at Southern Methodist University, whose research is in the area of web services and semantic web technologies. “So the semantic angle is how can you organize this data to take advantage of it, to do queries over it.” Those in the semantic web community say RDF is the way to go, he says, adding that people now use the term linked data as another way of describing semantic data. “If you take Big Data and link it, then you have semantics – you have meaning now introduced into the equation.”

Read more

Dr. Graham G. Rong, founder of IKA LLC, and senior industrial liaison officer at the MIT Corporate Relations Office, leading collaboration between the institute and industry, has been working on a semantic web approach to social and financial analysis based on digital financial data and other information related to companies that can be found on the Internet. The approach first turns XBRL data from SEC reports into RDF format, and then links that with the relevant social information in the company’s ecosystem, to deliver more business value.

The project, which began at MIT (see our earlier story here), has advanced to the application stage, and the software is moving from a JAVA to a browser-based interface. Rong says the team also is developing a web services API for the system.

“Current XBRL technology primary collects financial data for reporting, and secondarily, as more XBRL-based financial data becomes available, it will need to effectively extract financial data for value,” says Rong. Semantic web technology lets the focus be on the latter.

Read more

Last week The Semantic Web Blog continued its coverage of Google’s Knowledge Graph with the news of its worldwide launch for English-language users. This week we’ve learned about a paper submitted to the 1^st International Workshop on Knowledge Extraction and Consolidation from Social Media (KECSM2012), which takes place in November in Boston, about work underway on the topic of crowd-sourcing an Open Knowledge Graph API.

The paper, authored by Thomas Steiner of the Universitat Politècnica de Catalunya in Barcelona and Stefan Mirea of Jacobs University, Bremen, Germany, and currently pending review, proposes that the crowd step in where Google has so far failed to tread when it comes to creating an interface to the Knowledge Graph of more than 500 million objects – landmarks, celebrities, cities, sports teams, buildings, movies, celestial objects, works of art, and more – and 3.5 billion facts about and relationships between them. There is no publicly available list of all those objects, and, say the authors, even if there were, “it would not be practicable (nor allowed by the terms and conditions of Google) to crawl it.” Hence, the crowd-sourcing approach.

Read more

Querying semantic databases isn’t necessarily the most user-friendly thing to do on the planet. Consultancy ABComputing is trying to change that, with its EQL (Entity Query Language) technology.

“We wanted to where possible have it so the syntax was more closely mirrored with SQL than with SPARQL because people understand SQL,” says Martin Bradford, primary developer at the company. “If you build on that knowledge, that helps matters.”

EQL came about from the company’s work on a potential contract that involved semantic technology. Exposure to the world of semantic web technologies and SPARQL in particular led Antonia Bradford, who started the firm a couple of decades ago, to conclude that there had to be a better way of working with RDF data without sacrificing the power inherent in the semantic web.

Read more

A new presentation from the ICWE Conference is available online. The presentation is titled An Introduction to SPARQL and Queries over Linked Data: “Nowadays, more and more datasets are published on the Web adhering to the Linked Data principles. The availability of this data, including the existence of data-level connections between datasets, presents exciting opportunities for the next generation of Web-based applications. As a consequence, consuming Linked Data is a highly relevant topic in the context of Web engineering. Our introductory tutorial aims to provide participants with an understanding of one of the basic aspects of Linked Data consumption, that is, querying Linked Data.” Read more

A fascinating project has been undertaken by the Partners of the Pan-Canadian Documentary Heritage Network (PCDHN): It’s a proof-of-concept showcase of using Linked Open Data visualizations for “Out of the Trenches.” This is a look at the First World War from the Canadian perspective: war songs, postcards, newspapers, photos, films, and these resources’ intersection with Canadian soldiers who fought in the war.

These digital resources from organizations such as McGill University, the Universities of Alberta, Calgary and Saskatchewan, and the Bibliothèque et Archives nationales du Québec have been linked through existing metadata provided in formats ranging from spreadsheets to MODS XML to RDF. Rather than reduce the metadata to a common subset, the approach was to maximize its use by moving to the “web of data” concept, so that the resources can be combined in different and unexpected ways, according to the proof-of-concept final report that was issued on the project.

The premise was to expose the metadata for these resources using RDF XML and existing published ontologies such as the Event Ontology, the Dublin Core Ontology and the Biographical Ontology, elements sets, vocabularies and resources like the Geonames geographical database to maximize discovery by the user community and contribute to the Semantic Web.

Read more

Last week The Semantic Web Blog covered the launch of the SindiceTech Assisted SPARQL Editor as an open source project, noting that SparQLed also is part of SindiceTech’s commercial suite for large enterprises building private linked data clouds. This week, we’ll dive a little deeper into SindiceTech and its progress since the founders of the Sindice web of data search engine turned their attention to focusing on the commercial application of its technology as a real-time semantic warehousing infrastructure, which leverages cloud computing for integrating and normalizing the massive amounts of data the enterprise must deal with.

As SindiceTech founder and CEO Giovanni Tummarello explains, companies actually approached his team to help them make a reality of their visions to use RDF and SPARQL, as the best knowledge representation and querying technologies available, by providing the missing scalability and stability. Sindice.com was evidence that the technology the team had developed could answer these enterprises’ needs; currently there are about 700 million semantically marked-up web pages indexed in the Sindice.com search engine, with a live updated index of some 80 billion triples daily. Its database is over 5 terabytes.

Read more

Early in 2011, I wrote a piece here on SemanticWeb.com which explored the relationship between Semantic Technologies and super-computing’s venerable rock star, Cray. Then, earlier this year, Cray spun out a new division to focus upon exploring massive graph databases; something which should resonate with the semantic technology community. The new division — YarcData — differentiates itself quite clearly from its parent, leading with a data-led proposition and typically operating at quite a different pricepoint to its eye-wateringly expensive parent.

I sat down with YarcData President Arvind Parthasarathi during the Semantic Technology & Business Conference in San Francisco, to get an update on YarcData and to hear why the company is investing $100,000 in prizes for a new ‘Big Data Graph Analytics Challenge.’ Read more

(Editor’s Note, June 29: The SparQLed project URL now is available here.)

SindiceTech today released SparQLed, the SindiceTech Assisted SPARQL Editor, as an open source project. SindiceTech, a spinoff company from the DERI Institute, commercializes large-scale, Big Data infrastructures for enterprises dealing with semantic data. It has roots in the semantic web index Sindice, which lets users collect, search, and query semantically marked-up web data (see our story here).

SparQLed also is one of the components of the commercial Sindice Suite for helping large enterprises build private linked data clouds. It is designed to give users all the help they need to write SPARQL queries to extract information from interconnected datasets.

“SPARQL is exciting but it’s difficult to develop and work with,” says Giovanni Tummarello, who led the efforts around the Sindice search and analysis engine and is founder and CEO of SindiceTech.

Read more