by clicking on the page. A slider will appear, allowing you to adjust your zoom level. Return to the original size by clicking on the page again.
the page around when zoomed in by dragging it.
the zoom using the slider on the top right.
by clicking on the zoomed-in page.
by entering text in the search field and click on "In This Issue" or "All Issues" to search the current issue or the archive of back issues respectively.
by clicking on thumbnails to select pages, and then press the print button.
this publication and page.
displays a table of sections with thumbnails and descriptions.
displays thumbnails of every page in the issue. Click on a page to jump.
allows you to browse through every available issue.
GCN : April 2014
Bi D G i O i If there is one area of data growth that can rival social media, it's geospatial data. In the past decade, technical advances in the areas of global navigation satellite systems, satellite remote sensing, sensor networks and radar and LiDAR, combined with the exponential growth in location-aware mobile devices, have created the ultimate big data problem--- and opportunity. By harnessing all of this valuable geospatial data and combining it with content such as video, imagery and text, agencies have the data they need to see the bigger picture. That information, in turn, can be very useful in determining where to allocate resources, create new models for delivering services, and developing public policy. According to the United Nations Global Geospatial Information Management (UN-GGIM), there are 2.5 quintillion bytes of data generated that data is location-aware. That is both the challenge and the opportunity. The • Crisis management: With access to information combined from location- aware devices including roadside sensors and security cameras, along with natural disasters and wounded citizens. • Natural resource monitoring and management: Location-aware data can help agencies better track and predict where oil will go following a spill, model earthquake recurrence rates, detect probable locations of mercury to assess mercury risk, and understand and manage the effects of global change, to name a few. locations: With access to automotive telematics, mobile phone-based location devices, cities and states can optimize The challenge lies in harnessing these rich sources of geographic data in systems that can handle the processing of large amounts of unstructured location data. Traditional databases and algorithms aren't powerful or fast enough to process that amount or variety of data. Newer processing engines, based on NoSQL, Hadoop and other big data-friendly technologies, allow and analysis of data. G m C GAME CHANGING ECHNOLOG O MEE AGENC MI ION SPONSORED REPORT NoSQL If you haven't heard much about semantic technology, it's only a matter of time. emantic technology --- which takes text analytics to a new level by extracting meaning from both structured and unstructured data --- can make a real di erence in interpreting data and increasing the accuracy of projections and trends, especially when it comes to big data. Here's what you need to know. WHAT IS SEMANTIC TECHNOLOGY? Language is ambiguous --- one word or phrase can have multiple meanings. In the past, that has made accurate analysis of text di cult. emantic technology extracts the meaning from data using machine learning, natural language processing, text mining and advanced statistics. he technology also can tag, categorize and classify data in relationship to each other and other sources. WHY IS IT IMPORTANT IN THE CONTEXT OF BIG DATA? Big data is all about the volume, velocity, variety and variability of data. hat means massive amounts of unstructured data --- data from video, social media, voice and images, among others. emantic technology greatly improves the processing and understanding of rhetorical references, comparisons, slang and acronyms, as well as distinguishing whether an expression is intentional or emotional. his is especially helpful with social media and voice data. WHY DOES MY ORGANIZATION NEED SEMANTIC TECHNOLOGY? emantic technology supports better decision-making. Here are some examples: • peeds up reaction times, helpful in critical decision-making areas such as anti-terrorism, intelligence, defense, fraud detection and detection, crisis and emergency management • Increases accuracy of trends and projections, useful in security, decision support and risk management • Improves the knowledge base. By linking to a CRM system, semantic technology can help agencies understand what types of questions and answers are most useful to citizens. his, in turn, can be used to improve self-help web sites. FINDING MEANING IN WORDS LEFT UNSAID