Steven Rosenbaum of Forbes recently posed the question, is there too much information out there? He writes, “If anyone knows anything about the web, where it’s been and where it’s going, it’s David Weinberger.  As a co-author of the seminal Clue Train Manifesto, Weinberger gave a generation of web innovators a clue as to how the web would evolve. In Too Big To Know Weinberger sets out to argue that the very nature of information and ideas is changing, even as you flip the pages of his book.”

Rosenbaum continues, “The world was, almost since the beginning of time, built around the concept of triangular knowledge. At the bottom of  the triangle is data. Raw and unstructured.  The Knowledge Triangle presented first in 1988 by Russel Akkoff presented DIKW (Data, Information,  Knowledge, Wisdom) as the basis for our information ecology.  Weinberger says our Information Age was built on this pyramid – creating an elaborate filtering system to sort Wisdom from Data.”

Read more here.

Image: Courtesy David Weinberger

SemTechBiz is Less Than 3 Weeks Away

The Semantic Tech & Business Conference (SemTechBiz) is coming to San Francisco on June 3-7! Join us for case studies, innovative panels, tutorials, and keynotes that will provide you with practical advice, hands-on guidance, and breakthrough approaches to solving business problems with semantic technology. Passes go up $200 at the door. Sign up now and save !

The financial services sector was in focus at this week’s Sentiment Analysis Symposium in New York City, which is organized and produced by Alta Plana Corp. and its founder, Seth Grimes.  Take, for example, the presentation by Rich Brown, head of Elektron Analytics at Thomson Reuters, who disclosed that the company is about to launch market response indicators in support of its Thomson Reuters News Analytics system for the financial community. That product this week also won The Technical Analyst’s 2012 award for best news analytics software.

With its software, originally discussed here, qualitative, unstructured information is turned into a quantitative data set allowing users – machines and humans – to quickly analyze thousands of news stories in less time than it takes to read a single headline, as Thomson Reuters describes it. It uses natural language processing technology to get to the end game, which is to forecast financial market response from news and social media sentiment. Some 82 fields of metadata come into play for automating the analysis of news content. That encompasses sentiment down through to the degree of positive, negative or neutral expressions and how individual companies mentioned in a piece fare in those respects – rather than just the tone of the piece at large. “The computational linguistics system measures the author’s tone as positive or negative on any given entity, which is important and the harder part of it,” Brown said. Other fields include, for example, relevance, genre, intensity of news flow, and more.

Read more

Philip Fennell of O’Reilly recently commented on Tom Koulopoulos’s keynote speech at the recent MarkLogic World conference. Fennell writes, “Although he did not mention Linked Data explicitly, Tom Koulopoulos’ presentation drew attention to the importance of ‘connections’ – links between data and the value that has both within an organisation’s data and outside to externally held data and he chose to underline this by likening it to the neural connections within the brain.” Read more

Ben Rooney of the Wall Street Journal reports that as need for Big Data professionals continues to soar, the pool of qualified candidates is failing to keep up. Rooney reports, “According to a report published last year by McKinsey, there is a problem. ‘A significant constraint on realizing value from Big Data will be a shortage of talent, particularly of people with deep expertise in statistics and machine learning, and the managers and analysts who know how to operate companies by using insights from Big Data,’ the report said. ‘We project a need for 1.5 million additional managers and analysts in the United States who can ask the right questions and consume the results of the analysis of Big Data effectively.’ What the industry needs is a new type of person: the data scientist.” Read more

Rob Styles has written an article regarding how semantic technologies can be effectively applied to the third V of Big Data: variety. (The other two Vs are volume and velocity.) Styles writes, “That third V of the Big Data puzzle is where I’ve been helping people use graphs of data (and that’s what RDF is, a graph model). Graphs are great where you have a variety of data that you want to link up. Especially if you want to extend the data often and if you want to extend the data programmatically — i.e. you don’t want to commit to a complete, constraining schema up-front. The other aspect of that variety in data that graphs help with is querying. As Jem Rayfield (BBC News & Sport) explains, using a graph makes the model simpler to develop and query.” Read more

Bryan Bell of Cogito reports that financial companies are wise to turn to semantic metadata for better Big Data analytics. Bell writes, “Financial institutions are looking to linguistics and semantics as the best option for managing and taking advantage of their unstructured data, using it to better understand customers and competitors, to identify impactful market trends or simply to automate the process of answering common customer questions. As one Chief Data Officer put it, ‘We are the stewards of one of our firms’ most important assets, data, and we have been charged with bringing meaning to the data. I believe semantics offers a consistent, long-term capability and change in how data will be managed’.” Read more

Derrick Harris reports that DataPop, an LA-based startup that uses Big Data to deliver custom online ads has raised $7 million in Series B funding. Harris states, “The company’s technology uses big data techniques such as natural-language processing and semantic association to automatically generate online ads based on what a web user has searched for. Essentially, the DataPop service works like this: DataPop gathers information on products, services, promotions and other relevant  data from customer web sites; it then automatically presents ads for those products, etc., when someone searches for something related on Google or Microsoft; the ads appear as if a human wrote them, not just a collection of keywords.” Read more

Q-Sensei Corporation has announced version 2.0 of Q-Sensei Enterprise, the company’s enterprise search platform. According to the company, the new version is “designed to rapidly and flexibly develop tailored search-based applications (SBAs) tapping the wealth of data from enterprise Intranets, social media, third parties and the Internet. The new platform features ontology-based data processing and configuration, and a new API to increase time-to-market, flexibility, scalability and efficiency in handling Big Data.” Read more

Digital marketing agency BigVoice Unlimited has announced a new Big Data analysis platform. According to the company, the platform is “a comprehensive set of consumer research tools and methodologies designed to deliver more meaningful web-based consumer insight & brand information. At BigVoice our goal is to help our clients improve the accuracy and efficiency of marketing activities by providing fast, cost-effective digital solutions for consumer research, strategic planning, and measurement analytics. Our new Big Data Analysis platform utilizes patented technology to capture timely and precise consumer insight from the web and social media that can be used to more effectively reach, attract and engage consumers to accelerate business growth.” Read more

The Open Knowledge Foundation is using open data to try to prevent violent conflict around the world. The foundation states, “We’re in the planning stages of a conflict prevention project called PAX and open data perspectives have fed into our thinking in its processes and structures. PAX aims to provide early warnings of emerging violent conflict, through an online collaborative system of data sharing and analysis. We’re still in the early stages of exploration and experiment, but the principle is that open data could help provide warnings of emerging violent conflict, enabling governments, NGOs and citizens to take action to prevent it escalating.” Read more