ArcGIS Data Reviewer Tag
The geometric network provides a way to model common networks and infrastructures and supports a variety of analysis tasks. However, in order for these tasks to produce reliable results, your data must be error-free and must display proper connectivity. Data Reviewer provides a number of checks that can be configured to validate data that participates in the Geometric Network. Below, we’ll highlight several checks that will help ensure your data can be fully utilized for tasks supported by the network.
Identifying Coincident Service Connections using the Duplicate Geometry Check
The presence of coincident point features in the geometric network, such as duplicate gas meters (service points), impacts analysis since the geometric network will only allow connectivity to one of those points. The second point is disconnected from the network which affects service outage notifications. The Duplicate Geometry check in Data Reviewer can be used to identify where coincident points exist that may negatively impact analysis tasks. In the screenshot below, the check has been configured to look for duplicate meters which may disrupt connectivity and affect network tracing tasks.
Here are the steps to configure and run this check:
- From the Data Reviewer Toolbar, click on the Select Data Check dropdown.
- Expand the Duplicate Geometry Checks category and click on Duplicate Geometry Check.
- For Check Title type Duplicate Meters.
- Choose Meters for Feature Class 1.
- Choose Meters for Feature Class 2.
- Click OK to dismiss the check properties dialog.
The image illustrates duplicate meters found upon running the check.
The team just released a patch for Data Reviewer 10 Service Pack 4 that addresses two issues.
- Cannot create a Reviewer workspace in a SDE database
- Creating grids using Create Polygon Grid was taking longer or would not create at all
Be sure to download the patch if these issues are critical to your organization.
What exactly does Data Reviewer’s Invalid Geometry check find? Before I provide an answer, let’s explore how invalid geometries are introduced in your geodatabase in the first place. Typically loading data from shapefiles or CAD files can introduce invalid geometries. When data is migrated into an enterprise geodatabase using the simple loader invalid geometries such as empty, null, and no envelope will be filtered. However, if you’re using a third party data migration tool, all features including invalid geometries could be migrated. Similarly, when importing data into a personal or file geodatabase all geometries will be copied over. While the Check Geometry geoprocessing tool reports such geometry problems, it only works on shapefiles and personal or file geodatabases, and not on enterprise geodatabases. That’s where Data Reviewer’s Invalid Geometry check is helpful.
The check returns features that meet one of the following conditions:
1. Nothing
2. Empty
3. Has an empty envelope
4. Not simple
Reminder: If you haven’t registered yet for the free GIS data health checks for water utilities and land records users at the CA/HI/NV regional user conference next week, please do so immediately by sending an email to datareviewer@esri.com. Experts will be available to perform validation on a sample of your data in a file or personal geodatabase and provide the results back to you.
In Part 1 and Part 2 of this blog series, I described three examples of how to use the Geo on Geo check as well as when to use the “Not” check box. The check provides six out-of-the-box standard relationships (Touches, Contains, Intersects, Within, Crosses, and Overlaps). Sometimes, however, these standard relationships might not work for the geometric relationship you’re interested in. This final part in the blog series focuses on how to use the custom relation option to build your own spatial relationship. I will also provide a preview of some of the new functionality available at ArcGIS 10.1 Data Reviewer for Desktop.
Warning: this blog is not for the faint-hearted as we’ll be delving into complex geometric relationships!!
Custom relationships
Trying to understand when and how to use the custom spatial relation option can get tricky. If the six standard relationships are not meeting your needs, it’s time to start thinking about whether the custom spatial relation option could be the solution. Today, I’d like to share just a few tips and tricks to get you started on using the custom spatial relation. My first and best advice is to begin by reviewing the topic in the Desktop Help here. I always refer back to it whenever I’m configuring a custom spatial relationship.
In Part 1 of the Geo on Geo check blog series I discussed the check’s parameters and provided a few examples of how to configure the check. Here in Part 2 I’d like to delve into an advanced example and focus on the “Not – find features not in this relationship” check box to highlight when and how to use it.
An advanced example
Let’s say I want to compare the street name on buildings to the names of the streets in the roads feature class to ensure the street name associated to the building is in fact the name of a nearby street. As you can see in the image below, the circular building has an address on “Hyde St” but none of the surrounding streets are named “Hyde St”. The Geo on Geo check enables you to flag such features as errors.
In order for the check to validate this business rule, we’ll take advantage of almost all the parameters in the Geo on Geo check properties dialog. First enter a Title for the check, Building Not Near Matching Street. Then choose Buildings as the first feature class and Roads as the second feature class. Continue reading »
Are you attending the CA/HI/NV Regional User Conference in Redlands, CA March 7-8, 2012? The ArcGIS Data Reviewer team is offering free GIS data health checks focused on validating water/wastewater and parcel data. Industry experts will run an analysis on your data in a file or personal geodatabase and provide a report of the error findings (if any). Be sure to sign up ahead of time by sending an email to datareviewer@esri.com in order to ensure a spot. Please provide your name, organization, and preferred time slot.
Are you attending the CA/HI/NV Regional User Conference in Redlands, CA March 7-8, 2012? The ArcGIS Data Reviewer team is offering free GIS data health checks focused on validating water/wastewater and parcel data. Industry experts will run an analysis on your data in a file or personal geodatabase and provide a report of the error findings (if any). Be sure to sign up ahead of time by sending an email to datareviewer@esri.com in order to ensure a spot. Please provide your name, organization, and preferred time slot.
In my opinion, the Geometry on Geometry (Geo on Geo, for short) check is one of the most versatile (and one of my favorites) among Data Reviewer’s 40+ automated checks. In this first of a three part blog series, I’d like to explain the check’s parameters and provide some examples to get you thinking of ways to use it in your own environment.
Geo on Geo parameters
To get started, here’s a quick breakdown of the parameters available in the Geo on Geo Check Properties dialog.
A simple example
In many cases you might not use all the above parameters. Let’s explore a simple business rule: buildings should not overlap. I am using a sample dataset where the buildings are quite dense and many of them share edges, and we want to ensure they do not overlap.
A common question when using Data Reviewer’s Positional Accuracy Assessment Tool (PAAT) is what sample size should be used when evaluating a geospatial data layer. Sometimes the sample size is mandated by a specification; but when it’s not, Data Reviewer’s Sampling check can be used to provide the sample size. In this blog, I’ll discuss how you can use the Sampling check to generate a statistically valid sample size and then explore two options for using it with the PAAT.
The steps include:
1. From the Data Reviewer toolbar, select the Select Data Check dropdown.
2. Expand the Advanced Checks category and select Sampling Check.
3. In the Sampling Check Properties dialog, select Auto Calculate.
4. Under Auto Calculate, select your Confidence Level and Margin of Error.
Note: The question you’re looking to answer: given a population size (number of features), what sample size do I need so that I’m “X” percent confident the sample size is statistically significant within a “Y” percent margin of error?
