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It’s not CAD to GIS; It’s Design
to As-Built
Richard E Chappell
APS (Arizona Pubic Service)
APS Background
                                            1.3 Million Customers
                                            5 Operating Divisions
                                            1140 Feeders/Circuits
                            North
                            East
                                            Metro Region =
                                              75 % of Customers,
                    North
                    West
                                              15% of Service Territory
    South
    West                                    One of the Fastest
                        Metro
            Metro                            Growing Customer bases
            West                    South
                                     East    in United States
Contents


• Discuss issues related to managing data across the facility
  management organization
• Dispel myths
• Identify technical issues
• Identify non-technical issues
• Discuss options
Intended Audience


• Designed for a mixed audience
• Generally not technical
• Some understanding of AutoCAD and GIS would be helpful

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Branford, Connecticut's 6th grade performance on the Connecticut Mastery Test (CMT) declined from 2006 to 2010 based on its Connecticut Index Rank (CIR). In math, Branford's CIR fell from 55 in 2006 to 85 in 2010, moving from the top 50% of districts to the bottom 50%. Reading scores dropped from a CIR of 44 in 2006 to 78 in 2010, with 34 more districts scoring higher. Writing ranks were excellent in 2007-2008 but dropped to 91 in 2010, in the bottom 50% of districts and below 51 additional districts. Overall, Branford's CMT scores declined over 5 years from excellence to mediocrity or worse, in the bottom 50% of reporting districts.

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Finalcad is a mobile platform that uses predictive analysis to help construction teams anticipate and solve issues during projects. It allows teams to access drawings, record observations, and use integrated tools from the construction site. The platform provides centralized monitoring of activities and issues across projects. It has helped save over 250 hours on one residential tower project in London through reduced time spent on site and clearer communication. Finalcad currently has over 100,000 users on more than 10,000 construction projects globally.

mobileconstructiontechnology
The FINALCAD Story (graphic recording)
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FINALCAD's entrepreneurial story, captured by Nicolas Gros (Wild is the Game) from a presentation at Startup Assembly event in Paris, on May 28th 2015.

storytellingreal estateentrepreneurship
Ground Rules


• No religious discussions
  – No discussion of whether GIS or CAD is better.
  – Many of us, for various reasons, need to work in an environment shared
    between CAD and GIS software
Critical Terminology


• Error
• Accuracy
• Precision




              Photo Credit: http://www.mandypatinkin.net/PB/pb.html
Error


Measurement is an inexact science. There is error inherent in all
  measurement.
• Errors can exist due to mistakes
• Errors can exist due to methods and tools
Accuracy and Precision


"Accuracy - closeness of an estimated (e.g., measured or computed)
  value to a standard or accepted [true] value of a particular
  quantity.”
     FGDC-STD-007.1-1998


Precision - in statistics, a measure of the
tendency of a set of random numbers to cluster about a number
  determined by
the set.
     FGDC-STD-007.1-1998

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This document discusses various CAD standards including: 1. Graphical standards like GKS and OpenGL that define graphics primitives and device independence. 2. Data exchange standards like IGES and STEP that define neutral formats for transferring geometric and non-geometric CAD data between systems. 3. Communication standards like LAN and WAN that define how CAD data is transferred over networks between systems. The goals of CAD standards are to enable interoperability and portability of CAD data across different software and hardware platforms. They aim to support the complete transfer of product description data.

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Photo credit: NOAA Collections
http://celebrating200years.noaa.gov/distance_tools/theb1670.html
Photo Credit: How to:
http://www.westone.wa.gov.au/toolbox6/hort6/html/resources/visitor_centre/how_to/measure.htm
Target Model of Data Quality




ACCURATE                PRECISE            ACCURATE &
                                             PRECISE
–Accuracy is the quality of the tools and methods
–Precision is how well the measurement is done
Data Sets at Different Levels of Precision

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Data input and editing in GIS involves collecting, digitizing, and correcting geospatial data to build a GIS database. There are two main types of data sources: digital data which may require processing or conversion, and non-digital hardcopy data which must be digitized. Common digitizing methods include on-screen digitizing, scanning, and geocoding of hardcopy maps and plans. Data editing aims to correct locational, topological, and attribute errors introduced during data input. Thorough planning is required to determine the best data collection and input methods based on factors like data format, source, accuracy needs, and project requirements.

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The document discusses vector data models in GIS. Vector data models represent geographic features using points, lines, and polygons. The key vector data models are the spaghetti model, which encodes features as strings of coordinates, and the TIN (triangulated irregular network) model, which creates a network of triangles connecting points. Vector models allow for discrete boundaries but complex algorithms, while raster models divide space into a grid but are simpler.

Different Levels of Precision
Some Myths to Dispel


•   CAD is dumb data
•   GIS data is not accurate
•   CAD doesn’t use coordinate systems
•   Technology now allows us to capture 80% of CAD data for GIS
•   CAD uses x and y coordinates, and GIS uses Latitude and Longitude
•   CAD is a graphics program and GIS is a database program
CAD and GIS Basics


• Both consist of basic primitive elements
  – Points
  – Lines
  – Polygons
  – Attributes
• Both store this information within a database
Points


• Represent a position or location
• Consist of coordinates – X, Y and Z

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Lines


• Consist of coordinate pairs – a start point and end point
Polygons


• Consist of group of coordinate pairs – a boundary of lines
Complex Features


Complex features are generally some construct of these primitives
• Annotation is a form of point
• Polylines are groups of lines
Attributes


• Primitives will have data elements attached
  – Some elements describe the object itself
  – Some are data describing what the object represents

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So what is the difference?


There are 2 key differences between CAD and GIS that are critical
• Data Structure Paradigm
• Graphic Representation
Data Structure Paradigm


• AutoCAD stores data in a free form object oriented database
  where the fields in each row are defined by the entity type
• ArcGIS stores data in predefined data structures where the fields
  are defined in each data type
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What this means


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railway systemsgis
Graphic Representation


• In AutoCAD, the graphic representation is stored on the object as
  part of the individual object definition
• In ArcGIS, all graphic representation is kept separate from the data
What this means


• Sharing a DWG file provides an exact representation of the original
  graphic representation
• Sharing a GIS data set will not provide an exact representation of
  the original graphic representation, without the ancillary support
  files
 Not good or bad – just different
Other Differences


• Coordinate number data types
  – Floating point vs Long Integers
     • 32-bit
  – Single vs Double Precision
• Some differences in primitives
  – Annotation – feature linked as well as annotation objects
  – Curves – curve data isn’t carried through some GIS data sets
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What’s The Point


The physical transfer of data is a minor technical issue
• Most software vendors now provide excellent tools to transfer data
  back and forth
• Most will allow direct editing of other data formats
Third-Party Options


• Additonally, there are a number of third-party applications to
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  – GISConnect by Haestad Methods (Bentley)
  – Crossfire by EMS
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Design Representation

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How it is seen in GIS
Integration Barriers


• The primary barriers to integration are data organization and
  business issues rather than technical issues
• The purposes of the data have a much larger impact than how the
  data is stored
• Understanding those issues can remove the barriers
Purpose of the Data


• The purpose of the data can have a profound impact on the data
• Across the facility management environment, there are a number
  of areas of the lifecycle, each with its own requirements
Commonality Across the Workflow


• Design and Facility Management are different activities that have
  unique requirements
• Identify the common requirements and you identify the targets of
  integration
• Then we can move to a real design to as-built data management
  process

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Some of the Issues


•   Scale
•   Precision
•   Granularity
•   Generalization
•   Data Capture
•   Cartographic Issues
Scale


• Different scales have different requirements
• Generally, design scales will be much larger than GIS map scales –
  Design scales get in the 1”=20’-50’ range, where system maps get
  much smaller, as in 1”=100’-400’
1”=5000’ Map
Electrical System
Map
It shows the road
centerlines and the
feeders
1”=500’
Distribution
System Map


Shows
parcels,
buildings,
primary,
secondary
and service
lines

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1”=50’
Distribution
System Map
Shows
addresses,
individual
services, line
labels,
individual runs
Generalization


• Reduce complexity by
  – Grouping of similar objects to simplify an image
  – Simplification of lines based on scale
  – Feature coalescence, selection and complexity reduction
Granularity


• Granularity is the grouping of dissimilar objects to represent a
  single feature
• Items that aren’t important to the operation of the system may be
  dropped from facility maps
Precision and Accuracy


• Higher accuracy is more expensive
• Design requires a high degree of accuracy
  – Underground utilities
• Most new construction work will include a site survey of 3rd order
  (or close) to identify the existing conditions
• With a large land base, highly accurate data is likely too expensive
  to create and maintain

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Cartographic Issues


• Symbols
  – Blocks vs Fonts
  – Linetypes and masking
• Appearance – White Space
  – “Slackuracy”
Putting It Together


•   Determine what data can move through the work flow
•   Understand how the pieces fit together
•   Be willing to re-evaluate your processes
•   Use the information to develop CAD standards that can make
    integration possible
Standards


• Freeform nature of AutoCAD allows great flexibility
• We can constrain CAD data to a similar organization as GIS through
  standards
Areas of Standardization


•   Layering
•   Symbols (Block)
•   Geometry
•   Attributes

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Layers


• In AutoCAD, layering is the most common method of segregating
  data
• In ArcGIS, feature classes and subtypes define segregate the data
• Match layers to feature classes and subtypes to segregate the data
• Use similar object types within each layer
  – ie. Lines with lines, points with points
Point Symbols


•   Represent points in data set
•   ArcGIS uses a font in the map document to create the symbol
•   AutoCAD would use a block in the drawing
•   Identify Font-Block Mappings during conversion
Geometry


• Maintain snapping through connected line features – use wipeouts
  to mask lines
• Insure intersections are broken within a single data set
• Use closed polygons to identify polygons
Attributes


• Use attributes to label items rather than text labels
• Use label blocks to attribute polygons and lines – after conversion,
  they can be spatially joined
• One label block per element
• Consider using external database links and maintaining an ID as an
  attribute

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Conclusion



By understanding the issues that really impact our processes,
we can develop workflows that will allow us to take the most
                   advantage of our data
Questions?
Au 2007   It’S Not Cad To Gis Final

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Au 2007 It’S Not Cad To Gis Final

  • 1. It’s not CAD to GIS; It’s Design to As-Built Richard E Chappell APS (Arizona Pubic Service)
  • 2. APS Background 1.3 Million Customers 5 Operating Divisions 1140 Feeders/Circuits North East Metro Region = 75 % of Customers, North West 15% of Service Territory South West One of the Fastest Metro Metro Growing Customer bases West South East in United States
  • 3. Contents • Discuss issues related to managing data across the facility management organization • Dispel myths • Identify technical issues • Identify non-technical issues • Discuss options
  • 4. Intended Audience • Designed for a mixed audience • Generally not technical • Some understanding of AutoCAD and GIS would be helpful
  • 5. Ground Rules • No religious discussions – No discussion of whether GIS or CAD is better. – Many of us, for various reasons, need to work in an environment shared between CAD and GIS software
  • 6. Critical Terminology • Error • Accuracy • Precision Photo Credit: http://www.mandypatinkin.net/PB/pb.html
  • 7. Error Measurement is an inexact science. There is error inherent in all measurement. • Errors can exist due to mistakes • Errors can exist due to methods and tools
  • 8. Accuracy and Precision "Accuracy - closeness of an estimated (e.g., measured or computed) value to a standard or accepted [true] value of a particular quantity.” FGDC-STD-007.1-1998 Precision - in statistics, a measure of the tendency of a set of random numbers to cluster about a number determined by the set. FGDC-STD-007.1-1998
  • 9. Photo credit: NOAA Collections http://celebrating200years.noaa.gov/distance_tools/theb1670.html
  • 10. Photo Credit: How to: http://www.westone.wa.gov.au/toolbox6/hort6/html/resources/visitor_centre/how_to/measure.htm
  • 11. Target Model of Data Quality ACCURATE PRECISE ACCURATE & PRECISE –Accuracy is the quality of the tools and methods –Precision is how well the measurement is done
  • 12. Data Sets at Different Levels of Precision
  • 13. Different Levels of Precision
  • 14. Some Myths to Dispel • CAD is dumb data • GIS data is not accurate • CAD doesn’t use coordinate systems • Technology now allows us to capture 80% of CAD data for GIS • CAD uses x and y coordinates, and GIS uses Latitude and Longitude • CAD is a graphics program and GIS is a database program
  • 15. CAD and GIS Basics • Both consist of basic primitive elements – Points – Lines – Polygons – Attributes • Both store this information within a database
  • 16. Points • Represent a position or location • Consist of coordinates – X, Y and Z
  • 17. Lines • Consist of coordinate pairs – a start point and end point
  • 18. Polygons • Consist of group of coordinate pairs – a boundary of lines
  • 19. Complex Features Complex features are generally some construct of these primitives • Annotation is a form of point • Polylines are groups of lines
  • 20. Attributes • Primitives will have data elements attached – Some elements describe the object itself – Some are data describing what the object represents
  • 21. So what is the difference? There are 2 key differences between CAD and GIS that are critical • Data Structure Paradigm • Graphic Representation
  • 22. Data Structure Paradigm • AutoCAD stores data in a free form object oriented database where the fields in each row are defined by the entity type • ArcGIS stores data in predefined data structures where the fields are defined in each data type
  • 26. AutoCAD Point Data Set with Attributes
  • 28. What this means • The means that AutoCAD will store multiple data types in a single DWG, while ArcGIS will store multiple data types in separate files – Tables in Geodatabase – Sets of files for Shapes and other formats
  • 29. Graphic Representation • In AutoCAD, the graphic representation is stored on the object as part of the individual object definition • In ArcGIS, all graphic representation is kept separate from the data
  • 30. What this means • Sharing a DWG file provides an exact representation of the original graphic representation • Sharing a GIS data set will not provide an exact representation of the original graphic representation, without the ancillary support files Not good or bad – just different
  • 31. Other Differences • Coordinate number data types – Floating point vs Long Integers • 32-bit – Single vs Double Precision • Some differences in primitives – Annotation – feature linked as well as annotation objects – Curves – curve data isn’t carried through some GIS data sets
  • 32. Curves from a Shapefile
  • 33. What’s The Point The physical transfer of data is a minor technical issue • Most software vendors now provide excellent tools to transfer data back and forth • Most will allow direct editing of other data formats
  • 34. Third-Party Options • Additonally, there are a number of third-party applications to further enable this interaction between systems – FME by Safe Software – GISConnect by Haestad Methods (Bentley) – Crossfire by EMS
  • 35. So What’s the Problem?
  • 37. How it is seen in GIS
  • 38. Integration Barriers • The primary barriers to integration are data organization and business issues rather than technical issues • The purposes of the data have a much larger impact than how the data is stored • Understanding those issues can remove the barriers
  • 39. Purpose of the Data • The purpose of the data can have a profound impact on the data • Across the facility management environment, there are a number of areas of the lifecycle, each with its own requirements
  • 40. Commonality Across the Workflow • Design and Facility Management are different activities that have unique requirements • Identify the common requirements and you identify the targets of integration • Then we can move to a real design to as-built data management process
  • 41. Some of the Issues • Scale • Precision • Granularity • Generalization • Data Capture • Cartographic Issues
  • 42. Scale • Different scales have different requirements • Generally, design scales will be much larger than GIS map scales – Design scales get in the 1”=20’-50’ range, where system maps get much smaller, as in 1”=100’-400’
  • 43. 1”=5000’ Map Electrical System Map It shows the road centerlines and the feeders
  • 46. Generalization • Reduce complexity by – Grouping of similar objects to simplify an image – Simplification of lines based on scale – Feature coalescence, selection and complexity reduction
  • 47. Granularity • Granularity is the grouping of dissimilar objects to represent a single feature • Items that aren’t important to the operation of the system may be dropped from facility maps
  • 48. Precision and Accuracy • Higher accuracy is more expensive • Design requires a high degree of accuracy – Underground utilities • Most new construction work will include a site survey of 3rd order (or close) to identify the existing conditions • With a large land base, highly accurate data is likely too expensive to create and maintain
  • 49. Cartographic Issues • Symbols – Blocks vs Fonts – Linetypes and masking • Appearance – White Space – “Slackuracy”
  • 50. Putting It Together • Determine what data can move through the work flow • Understand how the pieces fit together • Be willing to re-evaluate your processes • Use the information to develop CAD standards that can make integration possible
  • 51. Standards • Freeform nature of AutoCAD allows great flexibility • We can constrain CAD data to a similar organization as GIS through standards
  • 52. Areas of Standardization • Layering • Symbols (Block) • Geometry • Attributes
  • 53. Layers • In AutoCAD, layering is the most common method of segregating data • In ArcGIS, feature classes and subtypes define segregate the data • Match layers to feature classes and subtypes to segregate the data • Use similar object types within each layer – ie. Lines with lines, points with points
  • 54. Point Symbols • Represent points in data set • ArcGIS uses a font in the map document to create the symbol • AutoCAD would use a block in the drawing • Identify Font-Block Mappings during conversion
  • 55. Geometry • Maintain snapping through connected line features – use wipeouts to mask lines • Insure intersections are broken within a single data set • Use closed polygons to identify polygons
  • 56. Attributes • Use attributes to label items rather than text labels • Use label blocks to attribute polygons and lines – after conversion, they can be spatially joined • One label block per element • Consider using external database links and maintaining an ID as an attribute
  • 57. Conclusion By understanding the issues that really impact our processes, we can develop workflows that will allow us to take the most advantage of our data