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Wednesday, September 3, 2014

While working with geospatial information, it is often advantageous to find out how close one particular piece of data is to other pieces of data. This leads to a greater understanding of the area of study. The knowledge of how things relate to one another spatially is articulated in Waldo Tobler’s First Law of Geography. It states that “everything is related to everything else, but near things are more related than distant things.”

Thursday, January 2, 2014

A while back, my colleague Barry Schimpf touched upon some of the tools that we use in conjunction with the Platform Independent Model (PIM). Today, I will delve into one of the tools we use to generate physical schemas from the PIM. Before, I jump in, let’s review what a PIM is and what it does.

The PIM is an approach we have developed to enable proper configuration management of geospatial data models. We have used it successfully for federal customers to track multiple versions of complex data models, validate physical implementations of those models, and support profiling and adaptation of the models across user communities. The focus of a PIM is on the data model as opposed to the actual geospatial data so a PIM itself doesn’t store any geospatial feature data. It is merely a representation of the logical model; defining the feature types, attributes, relationships, and constraints necessary to build a geospatial data set that is in compliance with a particular data standard.

Friday, December 7, 2012

I have been a part of three different data collection efforts that collected line geometry and infrastructure of recreational trails.  One effort was the development of the Fish and Wildlife Services (FWS) Trails Inventory Program.  This effort involved collecting trails data in FWS national wildlife refuges across the United States.  The second was an effort to collect trails data on all of the recreational trails at Haleakala National Park in Hawaii.  This effort was based upon the FWS trails data collection with a few minor changes to how the data was collected.  In the third effort I was responsible for taking the data to its final state and for training field staff employed by the Student Conservation Association.

Based on these experiences, I have come to understand that the keys to a successful data collection effort lie in:

·         Communication

·         Planning

·         Flexibility, and 

·         Very clear goals of what is to be accomplished. 

Thursday, May 24, 2012

So nearly everything we have discussed so far is not really useful unless we can figure a way to get it to help with what we need to do with geospatial data.  It's sort of like having the world's greatest bowling ball with no lanes.  How do we make this help us with increasing productivity, promoting sharing, reducing user frustration, and making us 'cost competitive?' The simple, practical answer is flexible, user modifiable applications.

What are these applications?

Making practical use of a data standard involves a number of required functions.  These are:

  1. Performing an initial load of the PIM from the user defined Standard and providing a mechanism for modification/update
  2. Generating Schemas or compatible physical implementations in a variety of GIS formats
  3. Validating (checking) user data in these same GIS formats against the Standard
  4. Assisting with both User to User translations and Version to Version migrations
  5. Enforcing a discipline that allows for performance of #2 though #4 above. 
Monday, May 7, 2012

Much of the conceptual background and structure managing a geospatial data model using a platform-independent model (PIM) has been outlined in previous posts.  And while it is useful to understand how the PIM is structured in the tables and views inside the PIM database, the critical knowledge relates to the way the PIM API retrieves and organizes this information, and details the properties and methods of the various PIM API objects.  So if you are not particularly interested in the conceptual, now would be a good time to pay attention.

This post begins the process of moving from the abstract to the concrete. In the next series of posts, we will begin to build a simple data model in order to not only demostrate the concepts that have been previously discussed but also to showcase many of the existing tools for helping with various management tasks such as version migrations, script generation and data validation. In this post, we'll begin discussing the API provides the business rules for interacting with the PIM, enables configuration management activities, and acts as the interface bewteen the PIM and the applications that use it.

Friday, April 27, 2012

The PIM now contains sets of features (the pimFeature) grouped into sets (the pimConfiguration) with properties and referencing sets of attributes (the pimAttribute).  For may GIS solutions, this is all that is required for collecting, validating, and displaying geospatial data. 

But the PIM also contains the ability to constrain attribute values in a variety of ways, in much the same way that many of the RDBMS data stores contain a similar ability.  Probably the simplest of these ways is the 'Nulls Allowed' property.  In nearly all cases, attributes will be coded as 'Nulls Allowed', but specific user preferences might dictate otherwise, provided the user fully understands the implications of this coding. 

Monday, April 16, 2012

A quick review of the pimConfiguration to the pimFeature shows...

Friday, April 6, 2012

In a previous post, we discussed the meaning of the pimConfiguration as a collection of elements in the Platform Independent Model (PIM).  One of those elements (in fact, the most important geospatial one) is the pimFeature.  The pimFeature is that table/object that defines the geometric object that gets displayed on the map, sometimes called the 'shape'.  It is defined based on the contents of the pimGeometry table within the PIM.  These are currently defined as Point, Line/Polyline, or Polygon but could be easily expanded to 3D geometries and multipart geometries.

Wednesday, August 3, 2011

Zekiah supports many organizations, especially in the federal government, that have a need to run ArcGIS Server on networks that are not connected to the internet. Oftentimes, these organizations use tiled basemaps that are built from data or services that are available (whether free or by subscription) from the internet. While ArcGIS Server can produce these tile caches, organizations with production servers on disconnected networks can find it impractical to do so. Although the cost of running two ArcGIS Servers is sometimes a factor, we find more often that IT and information security policies make it difficult for these organizations to stand up servers on internet-connected networks. In such situations, a desktop solution is preferable.

Friday, July 22, 2011

One of the more critical, and somewhat confusing, concepts in the SDSFIE 3.0 is the notion of what constitutes a 'compliant' data set.  SDSFIE 3.0 offers considerably more flexibility in schema options than earlier releases.  This capability was created to permit individual DoD users some naming options to accommodate existing legacy applications that use geospatial data.  But the capability comes with a risk... namely compromising the very nature of a standard.

Many new DoD contracts are being awarded with a clause stating that the data deliverables are to be submitted compliant with SDSFIE.  Given the flexibility in schema naming and content, what does that really mean and how is that consistent with an absolute standard.

Wednesday, July 13, 2011

The Spatial Data Standards for Facilities, Infrastructure and Environment (SDSFIE) is the single Department of Defense spatial data standard that supports common implementation and interoperability for installations, environment, and civil works missions.  

SDSFIE is being managed by the Defense Installations Spatial Data Infrastructure (DISDI) Group. The DISDI Group is a formal governance group reporting to the Department of Defense’s Installations & Environment Investment Review Board.