Mark van Rijmenam of Big Data Startups recently wrote, “Geospatial data is data that identifies a geographic location on Earth, such as natural or constructed features, oceans, and more. The data is generally stored as coordinates and topology and can be mapped. Geospatial data is all around us and it is growing at a staggering pace of 20% per year. McKinsey Global Institute estimated that location data level stood at 1 petabyte in 2009, excluding data from RFID tags. Geospatial data is created by a vast array of different applications such as satellites, digital cameras, wearables, smartphones, radars, sensor networks, cars, trucks, trains and other transportation. With trends such as the quantified-self, the Internet of Things and the Industrial Internet the amount of geospatial data will grow exponentially in the coming years and you can harness this data to better serve your customers.” Read more
Posts Tagged ‘semantic data’
London, 30 Oct 2013 — Ontology Systems, the semantic search company for enterprise application data, today announces the launch of its partner programme, aimed at recruiting data integration specialists across the globe. Ontology, which provides technology that replaces traditional lengthy integration projects by making enterprise data 100% consumable and accessible, offers lower risk, cost and improved innovation to organisations. It is looking to expand from its heritage in the telecommunications sector by recruiting partners that can help sectors make better use of their data. Read more
NEW YORK, NEW YORK–(Marketwired – Oct. 21, 2013) - ADmantX, the next-generation contextual analysis and semantic data provider, and Turn, the marketing software and analytics platform, today announced a partnership to enable Turn’s clients to improve performance of their online ad campaigns by leveraging ADmantX semantic analysis and targeting. Read more
Alexandra Stevenson of The New York Times reports, “You may not admit that you want to watch ‘The Real Housewives of New Jersey,’ but Netflix knows you do. Using algorithms that use search data to predict what television shows people want to watch is one way in which companies are using Big Data to connect the dots. It’s captured the imagination of some of Silicon Valley’s most well-known venture capitalists, who have committed more than $10 million to a new early stage fund to help foster start-ups that analyze behavioral data to determine patterns and make predictions about social behavior.” Read more
Joseph Janes, editor of Library 2020, recently shared an excerpt from that publication on LibraryJournal.com. The article envisions two research libraries in the year 2020, one that has embraced technology, and one that has not. Janes prefaces the article, “Transformation. The word is so pervasive these days, it’s a cliché. We’re so inured to it—even tired of it—that it’s becoming background noise, and perhaps some of us don’t hear it anymore. As we all know, accomplishing real transformation is easier said than done. This is the theme taken up by Mary Ann Mavrinac in her essay for Library 2020, which LJ excerpts here. She is the vice provost and dean of River Campus Libraries at the University of Rochester, NY; I met her when teaching a few summers ago at the University of Toronto, when she was running the splendid library at its campus in Mississauga.” Read more
d-Wise Technologies, Inc. Partners with SOA Software to Deliver Semantics Manager Product for Clinical Standards Compliance
Morrisville, NC (PRWEB) September 12, 2013 — d-Wise Technologies, a leading life sciences and healthcare technology solution provider, and SOA Software, a leading provider of API Management and Service-Oriented Architecture (SOA) governance products announced today that they have signed a formal partnership to provide services related to SOA Software’s Semantics Manager Product to life science organizations throughout the United States and Europe. Read more
Adform and ADmantX Partner to Deliver Advanced Brand Safety and Contextual Targeting Within Adform’s DSP
LONDON, UNITED KINGDOM and COPENHAGEN, DENMARK–(Marketwired – Sept. 9, 2013) - ADmantX, the next-generation contextual analysis and semantic data provider, announced today that ADmantX superior semantic features are now live on Adform, Europe’s leading advertising technology platform. Through the integration, Adform’s customers will automatic access the ADmantX rich set of semantic data to improve their campaign success, safety and efficiency. Read more
Mankind has been trying to understand the nature of time since, well, since forever. How time works is a big question, with many different facets being explored by scientists, philosophers, even social-psychologists. Semantic technologists, however, are focusing a little more strategically, considering temporal data management for semantic data.
At the Semantic Technology and Business Conference in NYC, coming up in early October, Dean Allemang, principal consultant at Working Ontologist LLC will be hosting a panel on the topic of managing time in Linked Data. Relational database systems long have been tuned into dealing with bi-temporal data, which changes over two dimensions of time independently – that is, valid (real world) and transactional (database) time. Not so with RDF databases. But many institutions, in fields ranging from finance to health care, have no desire to go back.
“They’ll lose all the RDF powers they’re familiar with, all the semantic linkages,” says Allemang. “And if you want that kind of distributed data understood in your enterprise, a relational solution isn’t going to help.”
Andy Flint of CloudTech recently wrote, “Analytics depends on data — the more, the merrier. If we’re trying to model, say, the behaviour of customers responding to marketing offers or clicking through a website, we can build a far stronger model with 10,000 samples than with 100. You would think, then, that the rise of Big Data and its seemingly inexhaustible supply of data would be every analyst’s dream. But Big Data poses its own challenges for modeling. Much of Big Data isn’t what we have historically thought of as ‘data’ at all. In fact, 80% of Big Data is raw, unstructured information, such as text, and doesn’t neatly fit into the columns and rows that feed most modeling programs.” Read more
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