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FME®

Desktop Training Workbook

FME Desktop 2013 Edition

ii

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Much of the data used here originates from public domain data made available by the City of Austin and Travis County, Texas. The datasets can be found at:

ftp://ftp.ci.austin.tx.us/GIS-Data/Regional/coa_gis.html

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Revisions

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Document Information

Document Name: FME Desktop Training Workbook 2013 Version: FME Desktop 2013 Updated: January 2013

www.safe.com

FME Desktop Training Workbook

Training Exercises

FME Desktop Training Workbook .................................................................................................................... 3

This Workbook .............................................................................................................................................................. 3 Scenario ........................................................................................................................................................................ 3

Session 2 – Data Transformation .................................................................................................................... 5 Objective ....................................................................................................................................................................... 5 Detailed Steps ............................................................................................................................................................... 6 Advanced Tasks .......................................................................................................................................................... 13

Session 3 – Translation Components ............................................................................................................ 14 Objective ..................................................................................................................................................................... 14 Detailed Steps ............................................................................................................................................................. 14 Advanced Task 1 ........................................................................................................................................................ 19 Advanced Task 2 ........................................................................................................................................................ 20

Session 4 – Datasets and Feature Types ...................................................................................................... 22 Objective ..................................................................................................................................................................... 22 Detailed Steps ............................................................................................................................................................. 22 Advanced Tasks .......................................................................................................................................................... 25

Session 5 – Practical Transformer Use ......................................................................................................... 26 Objective ..................................................................................................................................................................... 26 Detailed Steps ............................................................................................................................................................. 26 Advanced Task ........................................................................................................................................................... 30

Session 6 – Best Practice .............................................................................................................................. 32 Objective ..................................................................................................................................................................... 32 Detailed Steps ............................................................................................................................................................. 32 Advanced Tasks .......................................................................................................................................................... 36

Session 7 – Group Project ............................................................................................................................. 37 Task 1: Data Preparation ............................................................................................................................................ 38 Task 2: Data Extraction ............................................................................................................................................... 40 Task 3: Schema Definition and Schema Mapping ...................................................................................................... 42 Advanced Tasks .......................................................................................................................................................... 44


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c) Test that each property in a block has a common Block ID number. These three properties form a single block, but the lower property has a problem (again!). This time it’s a different block ID number. Detailed Steps 1) Inspect the Source Data Inspecting the source data with the FME Universal Viewer before a translation should now be automatic. Start the FME Universal Viewer and use it to open the source dataset. Query some features to become familiar with the geometry and attributes that exist. The source data here is: Reader Format MapInfo MIF/MID Reader Dataset C:\FMEData\Data\Properties\parcel_L26.mif 2) Create a New Workspace Start Workbench and create a workspace to translate the source data (parcel_L26) to: Writer Format Google Earth KML Writer Dataset C:\FMEData\Output\DesktopTraining\Parcels.kml Save the workspace. 3) Place a Transformer – GeometryFilter From inspecting the data you will have noticed that both line and point features occupy a single layer (feature type). However, only the line features are needed to build polygons. In workspace authoring it’s often useful to run the workspace after every step, without writing data. So, first delete the existing connection between reader and writer feature types. Now add a GeometryFilter transformer using Quick Add to place it unconnected onto the canvas. Then connect the GeometryFilter to the reader feature type.

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10) Run the Workspace Again Run the workspace and check for invalid features. Even if you can’t see a fault in the highlighted features, query them and check their attributes; the GeometryValidator transformer adds an attribute to indicate the problem(s) and which test(s) was failed . Again, in the real world the FAILED features would probably be saved for further examination. 11) Place a Transformer – PointOnAreaOverlayer If you looked carefully during the data inspection, then the lack of attributes is no surprise because you’d have noticed it was the polygon centroids (point features) that held the attributes, not the line features. So the next task is to get the attributes off the point features and onto the new polygons. The PointOnAreaOverlayer transformer transfers attributes from points onto surrounding areas. Use whatever method you prefer to locate the PointOnAreaOverlayer transformer and place one into an empty part of the workspace. 12) Correct Connections This is where you start to use transformers in parallel. Connect GeometryFilter:POINT to the input port PointOnAreaOverlayer:POINT Connect GeometryValidator:PASSED to the input port PointOnAreaOverlayer:AREA Check the PointOnAreaOverlayer parameters (see the yellow button) and accept the defaults. At this point your workspace will look like this:


Training Exercises Page 11

13) Run the Workspace Connect up some Inspectors and run the workspace again. 14) Check the Output Query a feature. That’s much better. Polygons were formed with the correct attributes.

However – have you noticed anything about the Feature Counts on the completed translation? Do the numbers reveal anything about the quality of the output?

15) Place a Transformer – Tester Well done if you noticed the problem: 1570 area features but only 1512 point features. This means a number of area features are without a centroid, and therefore without attributes. Potentially it’s worse – what if areas are overlapping and sharing the same centroid? Let’s test for polygons without a one-to-one match. Place a Tester transformer on the canvas. Connect it to the PointOnAreaOverlayer:AREA port. See if you can figure out how to set up the Tester before looking at the next step! 16) Check the Transformer Parameters Did you figure it out? Importantly the PointOnAreaOverlayer adds a new attribute called _overlaps. This tells you how many points were found inside each area. Set the Tester properties with the required test: _overlaps = 1



17) Identify Bad Output Bad features (those where the number of overlaps is zero, or more than one) will emerge from the Tester:FAILED port. Let’s run the workspace to identify bad output quickly. Delete any existing Inspectors then add two more; one to the port Tester:FAILED and another to PointOnAreaOverlayer:POINT (inspecting the points is necessary to see why the areas failed). Run the workspace and examine the bad data. How many bad features are there? 18) Make Final Connections Now we’ve filtered out all of the bad data, we can make a final connection to the output dataset. Connect the output port Tester:PASSED to the destination feature type OGCKML:parcel_k26 Delete any existing Inspectors.

19) Save and Run the Workspace Save the workspace using the Save button on the toolbar. Run the workspace again. 20) Check the Output Inspect the output data to prove that it only contains polygon features with attributes. Open it in Google Earth to make sure it is in the correct location.

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2) Start Workbench Start Workbench. Create a workspace to translate the AutoCAD landmarks data; namely: Reader Format Autodesk AutoCAD DWG/DXF Reader Dataset C:\FMEData\Data\Landmarks\Landmarks.dwg Reader Parameters Group Entities By: Attribute Schema Writer Format Adobe 3D PDF Writer Dataset C:\FMEData\Output\DesktopTraining\Cellmasts.pdf 3) Place a Tester While inspecting the data you should have noticed that there is an attribute called LANAME – this represents the name of the landmark feature. One task is to filter out landmarks which have:

• No name (i.e. no value for LANAME) • The word “School” in the name

…as City council has determined that no cell-phone masts should be erected on school property. Place a Tester transformer with the PASSED output port connected to the output. The test will be set up so that the features we want will pass the test.

Set up two tests:

• LANAME Attribute Is Empty • LANAME Contains School

Then click the Negate option for both of these. That way we will cause these features to FAIL.

Be sure to set up the Pass Criteria field as “All Tests (AND)”; i.e. filter where LANAME is not empty AND it doesn’t contain the word “School”.

This is a very interesting test of logic.

If the tests were not negated, then the pass criteria should be OR.

But, because the tests are negated, the pass criteria should be AND Basically, if you negate multiple tests, you’ll want to switch from OR to AND. Can you see why this might be?



4) Run Workspace? At this point you may wish to disconnect the writer and connect Inspectors to both Tester output ports, and run the workspace to make sure the Tester is acting as expected. If all features emerge from the PASSED port, then check the Pass Criteria setting and try again. 5) Add Reader The next step is to include the elevation model data that is required. Select Readers > Add Reader from the menubar, and add the following reader: Reader Format Canadian Digital Elevation Data (CDED) Reader Dataset C:\FMEData\Data\ElevationModel\RasterDEM-250K.dem 6) Place Transformers – Reprojectors You may have noticed that the data in the two source datasets are stored in different coordinate systems. The Landmark source DWG file is stored in the coordinate system LL84. The DEM source CDED data is stored in the coordinate system LL72-SECONDS. If we want to overlay the landmark features onto the raster DEM, we need to convert them to the same coordinate system. The Reprojector transformer allows us to do this inside a workspace. Place two Reprojector transformers. Connect one of them to the CDED Reader’s single Feature Type. Connect the other to the Tester:PASSED output port.

Set up these transformers to reproject the source datasets to a common TX83-CF coordinate system. The Source and Destination Coordinate System are the key parameters to define. The Reprojector parameters for the Landmark data will look like this: Q) Could you leave Source Coordinate System as ‘Read from Feature’? How would you know?



7) Run Workspace To ensure the Reprojector transformers are working as expected, connect them both to Inspector transformers and re-run the workspace. If the data is reprojected correctly, both sets of features appear in the same coordinate space. 8) Place a Transformer – PointOnRasterValueExtractor To assign elevation to landmark data, we need to overlay it onto the DEM and extract a Z value. Place a PointOnRasterValueExtractor transformer. Use its default parameter values. Connect the landmark REPROJECTED data to the PointOnRasterValueExtractor:POINT input port, and the elevation model REPROJECTED to PointOnRasterValueExtractor:RASTER.

Again, connect an Inspector to the PointOnRasterValueExtractor and run the workspace to inspect what data the process has created so far. The resulting attribute from this operation is called ‘_band{0}.value’.

The attribute is called ‘_band{0}.value’ because it’s the first band (layer) of the raster. In fact this layer of DEM values is the only band here. A three-band color raster dataset would produce _band{0}.value, _band{1}.value, and _band{2).value for the colors Red, Green, and Blue. 9) Place a Transformer – 3DForcer The elevation can now be used to provide the output features with a proper Z value. Place a 3DForcer transformer. For elevation click on Set To Attribute Value and select _band{}.value:

You will be prompted to select the element in the list that you wish to use. In this instance, choose 0 (the only list element that will actually have a value).



Once more, connect an Inspector and run the workspace. Querying a feature should show that each landmark feature now has a Z coordinate.

The last part of the workspace will now look something like this: 10) Place Transformers – Sorter and Sampler Not much work left now: we just need to select the top 10 sites in terms of elevation. Place a Sorter transformer and set it up to sort features in order of elevation – highest to lowest.

Place a Sampler transformer and set it up to pass only the first 10 features in the workflow.

11) Reconnect Writer Reconnect the writer, and delete any remaining Inspectors. The workspace should now look something like this:

12) Run Workspace Save and run the workspace, and inspect the output.

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Page 23

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6) Place a Transformer – CoordinateRounder Change detection could be adversely affected if the developer’s data has a different precision than City standards. To avoid potential problems add two CoordinateRounder transformers. Connect each to an AreaBuilder:AREA port.

Set both X and Y coordinates to be rounded to six decimal places. All data now has the same level of precision.

7) Place a Transformer – ChangeDetector Now the data has been fully prepared, change detection can take place. Place a ChangeDetector transformer in the workspace. Connect the city data CoordinateRounder:ROUNDED port to ChangeDetector:ORIGINAL Connect the developer data CoordinateRounder:ROUNDED port to ChangeDetector:REVISED 8) Check Transformer Parameters Check the ChangeDetector parameters to ensure the Match Geometry setting is set to ‘2D’ and the Lenient Geometry Matching setting is set to ‘Yes’. Set the Attribute Matching Strategy to ‘Match Selected Attributes’ – but don’t select any! Lenient Geometry Matching ensures a match when features have the same coordinates, but – for example – are in the reverse order.

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FME Desktop T

Page 26

Session 5

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2) Add a PointOnAreaOverlayer To discover which sites fall into which zipcodes, a PointOnAreaOverlayer transformer can be used. Place one of these transformers. Connect RandomNumberGenerator:OUTPUT to PointOnAreaOverlayer:POINT Connect MIF:zipcode_boundaries to PointOnAreaOverlayer:AREA Open the properties dialog for the PointOnAreaOverlayer and enter a list name of SiteList

3) Add a ListSorter Add a ListSorter transformer connected to the PointOnAreaOverlayer:AREA output port. Open the properties dialog and set it to sort on the attribute SiteList{}.DailyPollutionLevel Set Sorting Type = Numeric, and Sorting Order = Decreasing

This will ensure the site with the highest pollution level is on top of the list.



4) Add an AttributeCreator Add an AttributeCreator transformer connected to ListSorter:OUTPUT This will be used to create a string reporting the highest polluter. Open the parameters dialog, and set the Attribute Name field to HighestPolluter In the value field, open the String Editor dialog. Enter Constant: The highest polluter in zipcode<space> Attribute Value: zipcode Constant: <space>is:<space> AttributeValue: SiteList{}.FacilityName When prompted for the list element number, select 0 (the default) to pick the top of the list. New Line: Constant: With a pollution index of:<space> Attribute Value: SiteList{}.DailyPollutionLevel Again, when prompted for the list element number, select 0 to pick the top of the list. The String Builder should now look like this: 5) Add a Tester Now a Tester must be used to ensure only the chosen zipcode is output. Add a Tester transformer connected to AttributeCreator:OUTPUT Open the Parameters dialog. Under the Test Clauses section, set: Left Value: Attribute Value > zipcode Operator: = Right Value: Parameter > Create User Parameter When prompted, create a new parameter as follows: Name: ZipcodeTestParameter Prompt: Enter Zipcode Default Value: 78754

Click OK to accept this dialog.

NB: Valid zipcode numbers are:

• 78724 • 78751 • 78752 • 78753 • 78754



The final test clause should now look like this:

6) Place ListRemover Use Quick Add to place a ListRemover. Notice how the transformer actually placed is an AttributeRemover. The ListRemover has been merged into this in FME2012. Connect it to the Tester:PASSED output port, open the parameters dialog, and set it up to remove the list attribute SiteList{}

7) Run Workspace Connect a Logger transformer to the AttributeRemover:OUTPUT port. Run the workspace (use Prompt+Run if you wish to set Zipcode to something other than the default). Once complete you should find an attribute in the log similar to: INFORM|Attribute(encoded: utf-8): `HighestPolluter' has value `The highest polluter in zipcode 78754 is: IMAGE MICROSYSTEMS INC With a pollution index of: 9.36' Remember, because the pollution data is based on a random number, you will get a different result each time you run the workspace.

FME Desktop T

Page 30

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If you have FME Server, publish the workspace as a Data Streaming service and run it online.

FME Desktop T

Page 32

Session 6

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2) Set Up Schema Let’s make the first task to tidy the reader and writer schemas. Add two new writer feature types (either by Writers > Add Feature Type) or by duplicating the existing writer type. Rename the three writer feature types as Blocks, Lots, and Centroids. The Lots feature type should have just one user attribute; PARCEL_ID. The Blocks feature type should have just one user attribute; BLOCK_ID The Centroids feature type should have just one user attribute; PARCEL_ID On the reader side, hide all attributes except BLOCK_ID and PARCEL_ID 3) Check Problem Linework Let’s check the sort of problems that can be found in the data. Add Inspectors to both AreaBuilder output ports. Run the workspace. Examine the unused lines layer. Most are unrelated to any polygon, but two in particular seem to be part of polygons that are not being properly formed. 4) Fix Problem Linework The most obvious solution to a non-continuous line is to snap it into place. FME 2013 has snapping capability built into the AreaBuilder transformer, for this very occasion.

Open the AreaBuilder parameters dialog. Set Snapping Type to End Point Snapping.

Experiment with the snapping tolerance setting to find the smallest possible tolerance that fixes the two problem polygons (remember, you can use FME Universal Viewer to measure the gaps). As a guide, try 1.1 (feet).

FME Desktop T

Page 34

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7) Create Centroids We now need to create a new centroid – a point guaranteed to be inside each polygon. The CenterPointReplacer may be adequate – but we can’t be sure that all the points it generates will be inside the correct polygon, so place an InsidePointReplacer transformer. Create a second connection from the Counter:OUTPUT port and into the InsidePointReplacer. This will turn each polygon feature into a new centroid. Connect the InsidePointReplacer:INSIDEPOINT port into the writer feature type for OGCKML:Centroids

8) Create City Blocks The final task is to create a new set of features to represent city blocks and to give them a suitable ID number. A city block is comprised of a number of adjacent lot polygons, so the first task is to remove all the inner boundaries between adjacent lots to produce a city block outline. Place a Dissolver transformer connected either before or after the Counter.

Route the Dissolver output port labelled AREA to an Inspector, delete or disable any other existing Inspectors and run the workspace again. 9) Inspect City Block Output Inspect the City Block output in the FME Universal Viewer. Can you see any problems? In fact there may be one or two pieces of bad geometry; spikes in the data. Can you locate them with the FME Universal Viewer? If not, they may not exist! The problems may have been cleared up by the Snapper depending on the tolerance you used. If you do see these problems, do you know why they still occurred, even though we already used the GeometryValidator?

FME Desktop T

Page 36

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FME Desktop T

Page 38

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1) Create Workspace The first step should be to create a basic workspace to read the data. With multiple formats it’s probably easier to start with an empty canvas and simply add as many readers as are required to read all the source datasets. 2) Add Writer Once readers have been added a writer is required. If the intention is to turn this into a Custom Format then the format shouldn’t matter, but FFS would be a good choice in either case. So add an FFS format writer and duplicate all reader feature types on the writer. 3) Process GPS Now the GPS data needs processing. It is a plain text file with X,Y coordinates in different fields. A simple combination of 2DPointReplacer and PointConnector transformers will achieve this goal. 4) Add Attribute Data You’ll notice the GPS data has no attributes. These are stored in a Microsoft Access Database Reader Format Microsoft Access Reader Dataset C:\FMEData\Data\GPS\road_attrs.mdb The next step should be to connect these attributes onto the correct road features with a Joiner. 5) Update major roads schema Once attributes have been added to the GPS data, they should also be defined in the writer schema, so add them there and remove any existing attributes. 6) Create Custom Format Now a Custom Format can be created. Save the workspace and then choose File > Export as Custom Format from the menubar. 7) Update/Check Permitted Geometries In the custom format, open all of the writer feature types and check the allowed geometry settings. They should all be set to fme_line, since these are all line features. Your custom format could now look very much like this:

FME Desktop T

Page 40

Task 2: Dat

Scenario

Data

Overall Goal

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FME Desktop T

Page 42

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FME Desktop T

Page 44

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