Inventorying and managing cultural heritage data turns out to be a pretty complicated undertaking. The construction of a famous site may have lasted across different time periods, and its present location may span multiple districts. Buildings may be associated not only with famous architects but also with well-known residents. Or structures may have been constructed atop pre-existing entities.

Helping sort it all out is the work of The Arches Project, collaboration between the Getty Conservation Institute (GCI) and World Monuments Fund (WMF). The Arches effort grew out of GCI’s and WMF’s work to develop MEGA-Jordan, a purpose-built geographic information system (GIS) to inventory and manage archaeology sites at a national level for that country. But for this more generic and open-source take at accommodating any country, region or other institution worldwide responsible for the protection of immovable cultural heritage, the focus expanded from the geo-spatial to the semantic.

“We became very familiar with the CIDOC Conceptual Reference Model ontology,” says Alison Dalgity, who manages the Arches project on GCI’s side. The CRM provides definitions and a formal structure for describing the implicit and explicit concepts and relationships used in cultural heritage documentation. “We realized we needed something like that. Now, the GIS piece is only part of this – it’s nice to know where something is, but all the other relationships – the who, how, what and when and so on – have to be represented, too.”

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“We want to help the world make sense of data and we think graphs are the best way of doing that.”

That’s the word from Emil Eifrem, CEO of Neo Technology, which makes the open-source Neo4j NoSQL graph database. He’s not talking in terms of RDF-centric solutions, even though he says he’s 100 percent in agreement with the vision of the semantic web and machine readability. “The world is a graph,” Eifrem says, “and RDF is a great way of connecting things. I’m all in agreement there.” The problem, in his opinion, is that execution on the software end there has been lacking.

“This comes down to usability,” he says, and the average developer, he believes, finds the semantic web-oriented tools largely incomprehensible. Eifrem says he’s speaking from real-world experiences, having worked directly with RDF and taught classes on the semantic web layers. Where it took a week to get students up to speed on things like Jena and Sesame, they ‘get’ the property graph and graph databases in half-a-day, he says. Neo4j stores data in nodes connected by directed, typed relationships with properties on both – also known as a property graph.

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This week Dandelion, which bills itself as the one-stop shop for smart, high-quality Geo and Linked Data from trusted sources, starts its private beta. The service, which promises end users quality, normalized, linked and enriched data for their apps and reports; developers a simple API for any kind of language on any kind of platform; and corporate and government entities a way to publish and profit from their data, comes from SpazioDati.

That company is the creation of four Italian entrepreneurs – CEO Michele Barbera, president Gabriele Antonelli, partnerships director Andrea Di Benedetto, and Luca Pieraccini – who lived first-hand the frustrating experience of trying to find and leverage useful data for the custom web and mobile apps they were developing while running and working in small IT consulting companies. In an attempt to reverse the ratio of finding and cleaning data to actually building apps, says Barbera, the founders began participating in several EU-funded research projects and in the Open Data movement in Europe and Italy, including founding the non-profit Linked Open Data Italy. They also started experimenting with Semantic Web technologies.

“Open Data helps us to find valuable data and to build value-added web and mobile apps,” says Barbera. “So, let’s say that we solved partly the first problem of finding data, but not the second one, normalizing and cleaning data, since it is still very difficult to merge different data sources to put data in context.” Read more

Conversational user interfaces and natural language processing could be put to much more use than they currently are.  At the GigaOM Structure Data event in New York City this week, IBM distinguished engineer Currie Boyle, who leads the vendor’s North American natural language services practice, including for deep question and answer Watson-type natural language and unstructured information processing systems, and Nuance Communications CTO Vlad Sejnoha, discussed the realized promises, but also the waiting opportunities.

At Nuance, Sejnoha noted, the focus is on the notion that we are entering a time when how we interact with systems and access information and content is undergoing a “dramatic transformation.” Contributors to that include high- level artificial intelligence reasoning and natural language understanding. “We are overwhelmed with lots of data including unstructured data and these technologies make a difference in how we take advantage of all that,” he said.

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Earlier this month Gartner named semantic technologies to its top ten trends list (see our story here). Recently, we caught up with Gartner vp and distinguished analyst Debra Logan, the lead author on the semantic technologies section of the Top 10 Technology Trends Impacting Information Infrastructure, 2013, to learn more about sem tech’s earning a place on the list.

One interesting point Logan made is that the top ten trends list actually is a reflection of inquiries Gartner sees from its end-user clients. So, semantic technologies’ spot on the list would seem to indicate a bubbling-up of real-world, enterprise interest. As Logan sees it, it’s very much about information overload, about minimizing the risk and maximizing the value of the data on their hands, and about the availability now from providers like Amazon and Google of infrastructures for analyzing Big Data sets.

“If we could get the same meaning from data, we might actually know what is going on, because we sure don’t now,” says Logan, of the quandary facing enterprise IT leaders. “They are struggling with definition issues and reconciliation because of the proliferation of different IT systems.”

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Google Analytics gives web site owners good information about what’s clicking with visitors to their site, how those users got there, and more. But, attaining that insight can be somewhat laborious for those not well-versed in the tool and its interface, says Nick Cassimatis, associate professor in the Department of Cognitive Science at Rensselaer Polytechnic Institute. He’s the founder of natural language processing technology startup SkyPhrase. His take: Apply SkyPhrase to the task, and things get a lot easier.

The startup in February began private beta testing of its NLP interface to Google Analytics. “Google Analytics lets you ask things like how many people from California visited the site last month, or which of your pages were most visited on mobile devices,” says Cassimatis. “Our system lets you ask these questions in natural language and get answers to them” more seamlessly than using Google Analytics alone.

Previous to bringing its NLP help to Google Analytics, SkyPhrase had a public site that let users run natural language searches of their Gmail or Twitter accounts, as well as flights and music.

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Semantic technologies have made it to Gartner’s list of the top technology trends that will impact information infrastructure this year.

The research firm yesterday released the list of nine trends that it says will play key roles in modernizing information management and in making the role of information governance increasingly important. Semantic technologies come in at No.3 on the list – right behind closely-tied-to trends Big Data and modern information infrastructure.

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The 2013 Stanford Prizes for Innovation in Research Libraries (SPIRL) were announced this week, and among the recipients and commended institutions are those where semantic web technology and Linked Data are on display.

One of the recipients is the Bibliothèque nationale de France (National Library of France), for both its Gallica and Data Digital Libraries. The discovery service, Data (data.bnf.fr), has integrated numerous BnF catalogues and finding-aids using a Semantic Web approach, so that the BnF’s collection holdings, including those of Gallica (which promotes French cultural heritage in digital form), “are visible through a single, high-tech lens,” according to the announcement of the awards.

“Together, both efforts drive a wider audience to the digital library from search engines,” the SPIRL announcement reports.

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Image Courtesy: ipharmd.net

Dr. Carlo Trugenberger, co-founder and Chief Scientific Officer at InfoCodex Semantic Technologies AG, has co-authored a report reflecting the topic he discussed at last fall’s London SemTech event: An approach to drug research that relies on identifying relevant biochemical information using the company’s autonomous self-organizing semantic engines to text mine large repositories of biomedical research papers.

The model, says Trugenberger, is a departure from many other semantically-engineered approaches to streamlining drug research, which are based on natural language processing (NLP). That’s good for extracting information from documents, he says, but not as adept at discovering knowledge. “That’s what our InfoCodex software is designed for, to find new facts and hidden correlations” in repositories of unstructured information.

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Valentine’s Day is all about celebrating the coming together of two parties who are made for each other. That’s as true when it comes to semantic technology as it is for two people – sort of.

Yes, semantic tech aligns with the concept of matchmaking in its own ways. They aren’t always as romantic as a quiet dinner with a bottle of wine and a bouquet of roses, but hey, love comes in many forms. Here’s a quick look at semantic tech and its role in matchmaking, of various kinds:

• In the journal Concurrency and Computation: Practice and Experience you’ll find the work Semantic Web Service Matchmakers: State of the Art and Challenges. The semantic matchmakers it’s talking about get involved in helping developers partner up with the right web services: The mission of Web service discovery, its abstract explains, is to seek an appropriate Web service for a service requester on the basis of the service descriptions in Web service advertisements and the service requester’s requirements. But a problem in that discovery process is ambiguity, because the standard language used for encoding service descriptions does not have the capacity to specify the capabilities of a Web service.  According to the abstract of the article, “This brings up the vision of Semantic Web Services and Semantic Web Service discovery, which make use of the Semantic Web technologies to enrich the semantics of service descriptions for service discovery. Semantic Web Service matchmakers are the programs or frameworks designed to implement the task of Semantic Web Service discovery.” The paper surveys and analyzes typical, contemporary Semantic Web Service matchmakers across six technical dimensions.  Read more