Prachi Patel of IEEE Spectrum reports, “Farmers today produce three times as much food as they did 50 years ago using just 12 percent more land, thanks to new technologies and better farming practices. But the global playing field isn’t level. In Africa, farmers produce a fraction of what they could, according to the Forum for Agricultural Research in Africa, and most barely get by, struggling against infertile soil, drought, and diseases. Helping farmers—in Africa and elsewhere—produce more will be key to lifting millions out of poverty and sustainably feeding a world population of 9 billion in 2050. Food-policy experts believe that a crucial step toward that goal is to give farmers, scientists, and entrepreneurs unhindered access to agricultural data which is generated at research centers worldwide.” continued…

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Paul Miller of Cloud of Data recently discussed the issue of proper data attribution. He writes, “There have always, it seems, been people for whom attribution and citation really matter. Some of them passionately engage in arguments that last months or years, debating the merits of comma placement in written citations for the work of others. Bizarre, right? But, as we all become increasingly dependent upon data sourced from third parties, aspects of this rather esoteric pastime are beginning to matter to a far broader audience. Products, recommendations, decisions and entire businesses are being constructed on top of data sourced from trusted partners, from new data brokers, from crowdsourced communities, or simply plucked from across the open web.”

Miller continues, “Without an understanding of where that data came from, and how it was collected, interpreted or maintained, all of those products, recommendations, decisions and businesses stand upon very shaky foundations indeed. continued…

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Industry engineers waste a significant amount of time searching for data that they require for their core tasks. When informed about potential problems, diagnosis engineers at Siemens Energy Services, an integrated business unit which runs service centers for power plants, need to access several terabytes of time-stamped sensor data and several gigabytes of event data, including both raw and processed data. These engineers have to respond to about 1,000 service requests per center per year, and end up spending 80% of their time on data gathering alone. What makes this problem even worse is that their data grows at a rate of 30 gigabytes per day. Similarly, at Statoil Exploration, geology and geographic experts spend between 30 and 70% of their time looking for and assessing the quality of some 1,000 terabytes of relational data using diverse schemata and spread over 2,000 tables and multiple individual databases [1]. In such scenarios, it may take several days to formulate the queries that satisfy the information needs of the experts, typically involving the assistance of experienced IT experts who have been working with the database schemata for years.

Siemens and Statoil Exploration are hardly the only companies faced with time-wasting Big Data issues, but the root of these issues is not simply the “big” aspect of their data. The real challenge is finding a way to efficiently and effectively mine data for value and insight, regardless of its volume.

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David Hill of Network Computing recently shared his theory on the three transformations of IT. He writes, “The first was the digitization of business. The second is the continuing digitization of human experience. The third stage is the digitization of machines. Each transformation is ongoing, builds upon the others, and may overlap. Thus, some technologies that formed a foundation earlier are still active. For example, the mainframe is still alive and well, even in the time of mobile computing. Even though specific technologies provide a frame of reference, these transformations span a broad perspective and are not dependent upon any one technology. Please also note that there is not a smooth transition to each transformation, but that elements of a later transformation may be present while the key transformation of an earlier era is still more prominent.” continued…

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Barbara Starr of Search Engine Land reports, “In a June 2010 Semantic Web Meetup in San Diego, Peter Mika of Yahoo!’s research division gave a presentation entitled, ‘The future face of Search is Semantic for Facebook, Google and Yahoo!’ As the title suggests, the presentation focused on the ever-growing use of semantic markup as a means for helping computers parse and understand content. The talk focused on what was then the current state of the Semantic Web, as well as upcoming formats/technologies in development and the research being done in the field of semantic search.” continued…

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Tom Slee of The Guardian recently raised some of his concerns regarding who profits most from open data. He states, “In the technology world, ‘openness!’ has long been a battle cry of the underprivileged. It’s the language of bottom up freedom against top-downcontrol; of Linux against Microsoft and Wikipedia against Britannica. And now, open government data is the demand of those who would drag government data out from behind locked doors. But the world has changed since Linus Torvalds started his hobby operating system, and now openness is heard from the top as much as the bottom.” continued…

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Craig Hammer of the Harvard Business Review recently opined that open data has little value if no one is able to use it. He writes, “Open data could be the gamechanger when it comes to eradicating global poverty. In the last two years, central and local governments and multilateral organizations around the world have opened a range of data — information on budgets, infrastructure, health, sanitation, education, and more — online, for free. The data are not perfect, but then perfection is not the goal. Rather, the goal is for this data to become actionable intelligence: a launchpad for investigation, analysis, triangulation, and improved decision making at all levels. While the ‘opening’ has generated excitement from development experts, donors, several government champions, and the increasingly mighty geek community, the hard reality is that much of the public has been left behind, or tacked on as an afterthought.” continued…

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Trento, Italy, hosted a technology conference ‘ICT Days 2013’ between 20th and 23rd March. Like all such events it was interesting, dynamic and informative, but it was also quite different from the normal conferences.

It broadcast a very loud message that Semantic Technology, Big Data, and the interconnectivity of things will – without any doubt – affect everything and everyone; that these technologies will change the way everyone interacts with public services, the way in which dwindling natural resources are distributed and managed, the way citizens interact with each other, the way in which public and private bodies cooperate to support the needs of the citizen and the way in which public bodies are monitored and held accountable to the people that elected them.

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The 2013 Semantic Technology and Business Conference in San Francisco is fast approaching. The conference, which will run June 2-5, will combine innovative panels, case studies, tutorials, roundtables, keynotes, and lightning sessions that will give you an unparalleled interactive experience. Starting things off with a splash, the opening keynotes will feature speakers from WalmartLabs and Viacom.

Opening Keynotes:

How to Connect People and Products Using Big, Fast, and Heterogeneous Data with Abhishek Gattani, Senior Director, Distinguished Architect – WalmartLabs

With over 200 million people walking into stores each week, 43+ million unique visitors per month online, and access to the full twitter fire-hose (i.e. 200 million tweets per day), WalmartLabs is processing large amounts of data to help connect people to products and also provide unexpected insights to merchants. How do we turn this data into insights? How do we combine data internal to an enterprise with social data such as tweets and data from the “traditional” Web such as Wikipedia? When is social and web data useful? These are key questions when building any Big Data system. In this talk, Abhishek will discuss WalmartLabs’ work in this area and give examples of where social and web data was used to solve some key challenges faced when building the eCommerce search engine of the world’s largest retailer. continued…

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Dave McComb of Semantic Arts recently commented on Gartner’s nod to Semantic Technology. McComb writes, “Gartner has, finally, nominated Semantic Technology as one of their Top Technology Trends. We’ve seen this movie before. We know how it ends. Indeed it was Gartner themselves who named the plot trajectory: the ‘hype cycle.’ It’s worth a pause to reflect on why the hype cycle exists. The hype cycle suggests that a new technology follows a development growth path as predictable as egg to caterpillar to chrysalis to butterfly. In the hype cycle, the stages are [pictured above].” continued…

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Erik Nemeth of the Providence Journal recently opined that there is a current lack of taste and knowledge in the art world and suggested that the Semantic Web may be the right tool to help art collectors improve their decision making. He writes, “What the heck happened to cultural sensibilities last year? While collectors bid up record prices for artworks at auction–Edvard Munch’s ’The Scream’ went for $120 million in May–they were criticized for a lack of aesthetic judgment, especially at the premier U.S. fair, Art Basel Miami Beach. And cultural heritage took a turn for the worse as well. Cooperation on repatriation of antiquities was overshadowed by grim reports of wanton destruction of historic sites in Mali and Syria. With both contemporary and ancient art, the desire to collect and possess seemed to outstrip cultural appreciation. High-end collectors and cultural-heritage abusers alike would benefit from a boost in cultural intelligence, or ‘CQ,’ to grasp the interrelation of art, culture, economic development, and human rights.” continued…

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Ellyssa Kroski of American Libraries Magazine recently shared a list of ten technology initiatives that can improve libraries. She writes, “Today’s hottest web and mobile technologies are offering libraries a new world of opportunities to engage patrons. Ultra-popular social media websites and apps combined with the availability of affordable cloud-based services and the evolution and adoption of mobile devices are enabling librarians to share and build communities, store and analyze large collections of data, create digital collections, and access information and services in ways never thought about before.” continued…

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Ivan Kulikov of Gazea.ru recently wrote, “What is the difference between the search engine function and computer linguistics? Can natural language and machine language be merged? What counts as a language? Vladimir Selegey, head of the faculty of computer linguistics at the Russian State University for the Humanities and Moscow Institute of Physics and Technology, and director of the ABBYY linguistics research company, answered these and other questions for Gazeta.ru.”

Selegey stated, “The linguistics technology behind modern search engines is pretty basic. Let me explain what I mean here. Search engines are currently dominated by statistical methodology: they deliver quick results but without any linguistic analysis; they compare humongous quantities of text data on the system and the history of queries that have been fed in. continued…

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Leigh Dodds has drafted a diagram illustrating relationships between resources in an effort to understand and describe Dataset and API discovery in Linked Data. He writes, “While there’s been lots of research done on finding and using (semantic) web services I’m initially interested in supporting the kind of bootstrapping use cases covered by Autodiscovery. We can characterise that use case as helping to answer the following kinds of questions: Given a resource URI, how can I find out which dataset it is from? Given a dataset URI, how can I find out which resources it contains and which APIs might let me interact with it? Given a domain on the web, how can I find out whether it exposes some machine-readable data? Where is the SPARQL endpoint for this dataset?” continued…

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Kim Zetter of Wired reports, “The suicide last month of coder and internet activist Aaron Swartz prompted an outcry about the manner in which a U.S. attorney used anti-hacking legislation to launch a heavy-handed prosecution for what many considered a minor infraction. Federal prosecutors in Boston defended their actions, saying they were only upholding the Computer Fraud and Abuse Act, under which Swartz was charged. But two lawmakers are proposing long-overdue changes to the law that would help prevent prosecutors from overreaching in their use of the law, as has occurred in a number of cases in recent years.” continued…

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