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Next Generation GIS for the Data-Driven Government

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Today, GIS is not just software. It’s data. It’s people. It’s getting to the answer quicker.

Data is expanding and more users are demanding access to information. However, most users don’t consume the information in the same way as a GIS professional would. As curators and managers of geospatial information, GIS professionals are looking to support organizational needs, and not just those of GIS Departments. The CIO is acutely aware of how much geospatial data is being collected and wants to know how city and state governments leverage the data for smarter, more effective government services. The slides taken from the Pitney Bowes and NSGIC webinar cover five concepts of engineering the next generation of geospatial platforms:

Extensibility: Build a platform that can be customized for users beyond the GIS department.

Usability: GIS is a complex tool. Today’s desktop platform must be adaptable to many types of workflows.

Flexibility: The next generation of geospatial solutions must be ready to support the desktop, cloud, SaaS as well as mobile platforms.

Compatibility: GIS must work in mixed environments of open source and commercial software and ingest data from myriad sources.

Expandability: Can your GIS environment work in the world of big data? Smart cities depend on ingesting sensor data produced at high rates that require geoprocessing on a scale not thought possible until recently.

To view a recording of the webinar in which these slides were used visit the Pitney Bowes Li360 Community: https://li360.pitneybowes.com/s/article/Next-Generation-GIS-for-the-Data-Driven-Government-Webinar

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Next Generation GIS for the Data-Driven Government

  1. 1. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Next Generation GIS for Data-driven Government June 26, 2018 Joe Francica
  2. 2. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Challenges of the Geospatial Data-driven Government • Geospatial data not always seen as an asset • GIS departments are now more integrated with the IT department led by a Chief Information Officer and sometimes a Chief Data Officer • Data sources are still siloed…after all these years. • Utility department • Tax assessor • Others… 2
  3. 3. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 3 How did we get so much data? • Today, sensors are ubiquitous Where do we put it? • Databases will be larger How do we use it? • Will we break our GIS? Let’s answer these questions as well…
  4. 4. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Here’s how data is multiplying Every government agency is a collection of assets… …and these assets have a location
  5. 5. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Every city is a collection of assets, creating lots of data. 5 Bridges Fiber optic cables Fire boxes Fire hydrants When city leaders can identify, track, monitor and manage the data from these assets, the full value and possibilities of geospatial data & connected technologies result in the Location Intelligent city. Fleets and vehicles Kiosks and benches Manholes Parking meters Properties Roads and highways Sewer drains Sidewalks Street lights Traffic signals Trash barrels Trees
  6. 6. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 PREMISE: Government is a naturally geographic business… …driven by Geographic data
  7. 7. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 CONCLUSION:Therefore…Every government agency needs to become Location Intelligent …
  8. 8. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Five Pillars of the Next Gen GIS & Data-Driven Government 8 Extensibility Flexibility Connectivity & platform dependence 3 Expandability Scaling to data requirements 5 Extensibility Extensibility Support for the organization 2 Compatibility Working well in mixed GIS environments 4 Extensibility Usability It begins with clean data 1
  9. 9. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 1. Usability: GIS is a complex tool. But it’s only as good as the data. If you use bad data, you get bad results. Use case: Federal funding for U.S. Census 2020 9
  10. 10. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Data-driven Government must acknowledge location takes different forms • Coordinates (lat/long) • Cartesian • Coordinate reference systems; e.g. UTM, WGS84 • Location of Things • Address Data • Physical: 414 Hamilton Blvd., Suite 22, Peoria, IL 61602-1208 • Digital: IP Address 125.101.92.255 • Ephemeral • Routes • Dwell time 10
  11. 11. Pitney Bowes | Unlocking Value 2015 | January 12, 2015 11 Data Quality is Key for Location Intelligence in Local Government Name Address Address 2 City County Postcode Phone Email Mike Ashmore 414 Hamilton Blvd. Suite 22 Peoria Pr. 61602 309 555 1212 michael.ashmore@pb.com Michael Ashmore Williams St. Suite 22 Peoria 61602 309 555 1212 mike.ashmore@mapinfo.com M & L Ashmore 414 Hamltn Blvd. Peoria 601&2 309-555-1212 email@michaelashmore.com Mike Ashmore, Pitney Bowes Software 414 Hamilton Blvd. Peoria Berkshire 61602 01753 848 207 Multiple names Mixed business & contact names Incorrect address Typo Abbreviations Missing data Non standard Character Mis-fielded data Some typical challenges with address data.
  12. 12. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Geocoding Everything is Addressable 414 HAMILTON BLVD PEORIA, IL 61602-1208 USA 12
  13. 13. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Demo 13
  14. 14. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Census 2020 Local Update for Census Addresses (LUCA) 14
  15. 15. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 15 • In order to prepare for LUCA, local and state governments must… • Ensure that their address list contains multi-unit structure identifiers (such as apartment numbers for individual units) and that they can distinguish between residential addresses and nonresidential addresses. • Identify local address sources, such as building permits, E-911 address files, local utility records, annexation records, and assessment or taxation files. Critical Business Issue for States & Counties
  16. 16. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 16 Five (5) grant programs administered by the U.S. Department of Health and Human Services (HHS) use the Federal Medical Assistance Percentage (FMAP) FMAP determines reimbursements to and payments from each state government… … $286.1 billion in FiscalYear 2015
  17. 17. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 17 • In PENNSYLVANIA FMAP funding = $1746 per resident • Pennsylvania Residential Population from US Census: 5,955,478 • If the undercount is as little as 2% ~ 120,000 residents • Potential Federal assistance lost ~$208,000,000 Federal MedicalAssistance Percentage
  18. 18. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 2. Extensibility: Whatever the choice, the platform must be customizable for users beyond the GIS department. *Requests from other departments should be self- service 18
  19. 19. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 1919
  20. 20. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Apcoa Denmark LI Web and app client 20 Economy CRM PLM Fleet Man. Location Intelligence/GIS Maps/ Geo DB Module Eq. real time monitoring Module Sales/ Market Module Planning Rounding Module Customer Relations Module Parking Attendants Spectrum Spatial Sokigo AddSpatial Spectrum Spatial Analyst Sokigo AddSpatial LI API’s MapInfo Pro
  21. 21. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 21 Apcoa Denmark Planning routes/rounds and real time monitoring Map and analyze sites/lots
  22. 22. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 22 Demo of Sunshine CoastAustralia Cairns
  23. 23. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 23
  24. 24. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Geoenrichment The ability to append authoritative attributes to location-based features 24
  25. 25. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 25
  26. 26. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 3. Flexibility: The next generation of geospatial solutions must add connectivity services and be ready to support the desktop, cloud, SaaS as well as mobile platforms. *GIS must adapt to the user’s preferred IT environment … not the other way around. 26
  27. 27. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Data Discovery & Profiling Data Integration & Federation DataGovernance BusinessStewardship,Data, Policies,Monitoring,Measuring .SHP .DGN PostGreSql PostGIS Data Warehouses Web Services Hadoop / Big Data Data Quality Data Cleansing Entity Resolution Merge/Consolidation Names Addresses Connectivity Data GeoEnrichment Geocoding Geospatial Analysis Routing Spectrum Architecture BusinessApplicationConnectors, BI Connectors, Web Services, APIs,Visualization Points Lines Areas
  28. 28. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 28 4. Compatibility: GIS must work in mixed environments of open source and commercial software and ingest data from myriad sources. *Users of MapInfo, ArcGIS, QGIS…must share files and must be interoperable.
  29. 29. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 MapInfo Professional Desktop Mapping 29
  30. 30. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Interoperability & File Formats Multi-Resolution Raster (MRR) format was designed for storing raster and grid data For MRR, we already have a GDAL driver that supports read-only access available upon request For MapInfo Extended (NativeX) support, we have a few alternatives we are exploring. Our goal here is to also enable full abilities to read, write and create NativeX tables through GDAL. MapInfo TAB files are supported today through GDAL with the open source MITAB library 30
  31. 31. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 31
  32. 32. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 5. Expandability: Can your GIS environment work in the world of IT & big data? *Smart cities depend on ingesting sensor data produced at high rates that require geoprocessing on a scale not thought possible until recently. 32
  33. 33. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 33 But… How big is “big data”
  34. 34. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Big data in ecommerce 34 • eBay uses two data warehouses at 7.5 petabytes and 40PB as well as a 40PB Hadoop cluster for search, consumer recommendations, and merchandising. • Walmart handles more than 1 million customer transactions every hour, which are imported into databases estimated to contain more than 2.5 petabytes • the equivalent of 167 times the information contained in all the books in the US Library of Congress.
  35. 35. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 35 30% Increase from 2016 29% 45% 47%
  36. 36. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 36 The Tsunami of Satellite Image Data DigitalGlobe maintains an historical database of 100 petabytes
  37. 37. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Big Data … … is just data 39
  38. 38. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 40 It’s the platform that matters now… … Hadoop, Spark, Graph others
  39. 39. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 What is Hadoop? • Apache Hadoop is an open source technology • It allows you to split data and processing across lots of low cost machines • Pitney Bowes uses this technology to run our spatial processing against very large volumes of data very quickly.
  40. 40. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Data Discovery & Profiling Data Integration & Federation DataGovernance BusinessStewardship,Data, Policies,Monitoring,Measuring .SHP .DGN PostGreSql PostGIS Data Warehouses Web Services Hadoop / Big Data Data Quality Data Cleansing Entity Resolution Merge/Consolidation Names Addresses Connectivity Data GeoEnrichment Geocoding Geospatial Analysis Routing Spectrum Architecture BusinessApplicationConnectors, BI Connectors, Web Services, APIs,Visualization Points Lines Areas
  41. 41. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Spectrum Spatial Modules for Big Data Support MapReduce, Hive UDF and Spark-based implementations. 43 Module Features Spectrum Geocoding for Big Data • Global forward geocoding • Global reverse geocoding • 145 countries at street level of better • 245 total countries supported at variety of accuracy levels Spectrum Location Intelligence for Big Data • Find the nearest • Point and polygon • Spatial join • Distance to point, shape, line Spectrum Routing for Big Data • Global route generation, isochrones, isodistance • Walk time/drive time • Point-to-point calculations SpectrumTM for Big Data Enabling big data frameworks with data quality and geospatial technology Advanced Matching Universal Address- ing Data Normaliz- ation Universal Name Geocoding Geospatial analysis Routing Spectrum Spatial for Big Data Certifications
  42. 42. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 Five Pillars of the Next Gen GIS & Data-Driven Government 44 Extensibility Flexibility Connectivity & platform dependence 3 Expandability Scaling to data requirements 5 Extensibility Extensibility Support for the organization 2 Compatibility Working well in mixed GIS environments 4 Extensibility Usability It begins with clean data 1
  43. 43. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 45 Software and Data Marketplace Free data samples www.pitneybowes.com/us/data
  44. 44. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 46 Q & A
  45. 45. Pitney Bowes | Next Gen GIS for Data-driven Government | June 1, 2018 47 Thank you Joe Francica Joe.Francica@PB.com

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