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Learn more about Geocortex software, implementation, and the Maperture service powered by Geocortex Essentials.

As an authorized Geocortex Implementation Solution Provider, DDS has been providing custom Geocortex solutions to our clients since 2011. We work closely with our customers to identify their needs and requirements, and implement solutions designed to what is important to their organizational goals. We can develop Geocortex applications entirely within a client’s internal infrastructure, or develop applications on our server and later migrate it to the client site.

More information about DDS's Geocortex Implementation Solutions can be found at digitaldataservices.com

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What's new in Geocortex Essentials 4.9?

Our Product Development team has been hard at work for the past few months, adding functionality for GIS professionals to work more intuitively with data in tables (after all, your data is the most important aspect of your apps), and brings in editing functionality that has typically been reserved for desktop GIS tools. 

 

One of these features is a redesigned results table that dramatically improves performance, introduces infinite scrolling for hundreds (or even thousands) of records, and allows you to perform actions on specific results or sets of results. Geocortex Essentials users also benefit from advanced editing tools that allow you to cut and union geometries while maintaining attribute integrity.  

Geocortex Essentials 4.9 (alongside Geocortex Viewer for HTML5 2.10 and Geocortex Mobile Framework 2.3.1are now available for downloadYou can learn more about the latest releases on the product release page, or download the new versions in the Geocortex Support Center. 

Additional support for Geocortex Workflow 5 

We’ve continued to add support for Geocortex Workflow 5 to deploy offline workflows, dynamic forms, and new activities in Geocortex Essentials applications. 

Geocortex Workflow 5 is our newest product that allows you to extend Geocortex and Web AppBuilder for ArcGIS ® applications by turning complex business processes into simple, guided end-user interactions. Instead of writing thousands of lines of code to meet custom requirements, choose from more than 150 pre-built activities that chain together to automate almost any task. 

Building upon Geocortex Essentials’ popular workflow capabilities, Geocortex Workflow 5 is also offered as a standalone product and enables you to build workflows right in your browser.  

Take Geocortex Workflow for a spin in the Discovery Center, complete with videos, tutorials, and sample apps. 


Take 
workflows into the field 

Geocortex Workflow 5 provides the ability to take workflows offline to support field operations. You can download workflows and run them in your mobile viewers, keeping field workers productive… even in areas with no network connectivity.  

For example, a municipal field engineer may need to perform fire hydrant inspections throughout a rural neighborhood. With Geocortex Workflow 5, the inspection application and corresponding workflow can be downloaded right to the worker’s tablet at the beginning of the day, and the assigned inspections can be completed without any network connection.  

When the day is done and the tablet has returned to network connectivity, the field worker can sync the inspection data back to the database. This ensures that the field worker can continue to complete inspection, regardless of where they are, and that the data is readily available to the people in the office that need it. 

Explore Geocortex Workflow 5  

If you’d like to learn how you can take your business processes offline, or extend applications you’ve built with Web AppBuilder for ArcGIS, you can get a feel for the product in the Geocortex Workflow 5 Discovery Center. Here you’ll find demonstrations of different deployment scenarios, tutorials, and sample applications.  

Or, if you’re ready to get started with Geocortex Workflow 5 you can sign up for a free developer license here. 

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ArcGIS Pipeline Referencing: Choose the best data model

Over the past few weeks, I’ve shared foundational knowledge about how data is stored and managed in the pipeline industry. My first post introduced ArcGIS Pipeline Referencing (APR) and explained some options operators have in adopting it. My second post worked to demystify the confusing world of pipeline data models (there’s a lot to consider).

In this post, I will outline important information you need to consider when choosing a data model for your organization, including: 

Limitations of current data models; How APR is addressing these limitations; and Questions you should ask yourself to help assess the best data model for your organization (should you choose to move to APR).  

Limitations of Existing Models

A data model is defined as: “An abstract model that organizes elements of data, and standardizes how they relate to one another and to properties of real world entities.”

In the pipeline space, real world entities include not only the pipe and valves that make up the pipeline system, but all of the things that happen to and around the pipe. Things such as repairs & replacements, surveys & patrols, one-call, cathodic protection, ILI & CIS assessments, HCA & class location, land ownership & right-of-ways, and crossing information all have components that, in one form or another, need to be captured in your GIS.

The differing needs of these complex data representations expose limitations in legacy systems. And in a world where critical business decisions must be made from this data, identifying limitations and addressing them is an important step as we move to next-generation solutions.

Limitation #1: Data volume

As the years have progressed, the operational and regulatory needs surrounding pipelines have increased. These needs are driving new levels of inspections and analyses on pipeline systems - resulting in more data, both in terms of volume and complexity. The legacy systems were simply not designed to handle the volume of data current programs produce.

An example is the case of Inline Inspection (ILI) and Close Interval Survey (CIS) data. A single ILI or CIS inspection results in hundreds of thousands of records. With assessment intervals recurring every 1-7 years -- and operators performing dozens of inspections each year -- the resulting records from these inspections alone add millions of records to the database. This doesn’t include follow-up inspections, digs, and run comparison activities.

When you couple the sheer volume of records with complexities surrounding data management and the need to provide a high-performance environment, limitations in the system are quickly exposed. These limitations force operators to make difficult data storage decisions, often choosing to remove subsets of data from the system of record. This is sub-optimal to say the least; it significantly impacts your ability to view and analyze important trends in the data.

Limitation #2: Engineering Stationing

Engineering stationing is important, complex, and rooted in pipeline data management. Before modern GIS, operators kept track of the location of pipelines and associated appurtenances using engineering stationing on paper or mylar sheets. With a vast majority of pipelines that are in use being constructed before the existence of modern GIS technology, large volumes of data were referenced with this approach.

Engineering stationing doesn’t benefit all operators; however, companies that manage gathering and distribution assets find this method burdensome … and dare I say unnecessary?

When traditional data models were developed, the need to adhere to legacy engineering stationing outweighed the need to redesign the entire system to favor a spatial-first approach. But as technology has improved, and more users have embraced spatial data, new methods to blend modern (spatial-first) and legacy (stationing-first) models have emerged. Operators need this flexibility when managing their assets.

Limitation #3: Native support for the Esri Platform

The emergence of the Pipeline Open Data Standard (PODS) represents the last major shift in data storage solutions for pipelines, and it happened nearly 20 years ago. At that time, the GIS landscape was both immature and fragmented. As a by-product, PODS was designed specifically to be GIS-agnostic. In the nearly two decades since, Esri has emerged as the predominant provider of spatial data management, and they have developed a suite of solutions that enable stronger collection, management, and analysis of data.

Chances are your organization embraces Esri for spatial data management and content dissemination, which begs the question: “If your organization has standardized on Esri technology, does it make sense to employ a data structure that does not natively support the environment?” (Hint: probably not.)

Addressing and Improving Limitations

The core of APR has been engineered to address important limitations currently felt due to the existing designs of PODS and APDM. APR directly addresses the three limitations described above.

Improvement #1: Data volume

Understanding the need to support large datasets, time-aware data, and the ability to offload the storage of data to other systems, APR has been engineered to handle the high volume of data more efficiently, with a focus on scalability. To achieve this, available rules can be configured to allow a more fine-grained approach to managing data during routine line maintenance. No longer are implementations limited to keeping the data referenced to the LRS or detaching it.

Changes like these allow operators to keep more data in the system, providing a baseline for more powerful analysis and decision making.

Improvement #2: Engineering Stationing

As explained above, engineering stationing is firmly rooted in pipeline data management, but it’s not required for all operators. New construction, gathering systems, and vertically-integrated distribution companies are finding the rigorous application of stationing to be unnecessary overhead. If your current database repository requires it, and your organization doesn’t rely on it, you are taking on unnecessary data management cycles - costing valuable time and money.

APR not only provides the ability to manage data in stationed and non-stationed methods: its flexibility allows for both stationed and non-stationed lines to exist in the same model. Let that sink in for a bit: Operators that have deployed two separate data management systems can now consolidate the management of these assets! This functionality benefits a majority of the clients I’ve worked with over the years.

Improvement #3: Native support for the Esri Platform

As I stated in my previous post, APR is (possibly most importantly) integrated with the ArcGIS platform. You can perform complex long transactions on your data, analyze it in ways that have not been possible before, keep track of product flow using the Facility Network, and get the data in the hands of your organization with methods that are integrated, fluid, and connected.

Considerations for Implementation

If you’re considering implementing ArcGIS Pipeline Referencing (APR), knowing why, and which data model to use with it is has more to do with your business than with IT -- success can be achieved with either model.

But how do you decide which one is best for your organization?  Here are some questions to consider as you’re laying the foundation for your next-generation GIS implementation.

1) Business focus: What segment of the vertical are you in?

If you are a distribution company with transmission assets, the decision is pretty clear: you should choose Utility and Pipeline Data Model (UPDM). It’s designed as a distribution-first model, allowing you to integrate the management of distribution and transmission assets in a single model.

If your company is ‘upstream’ of distribution, the answer gets a bit trickier. Both models are adequate, but my vote tends to lean towards PODS for a few reasons:

Out-of-the-box PODS supports APR slightly more natively for operators without distribution assets than UPDM. Are you a liquids operator? As UPDM is focused on gas utility and transmission, the PODS model will provide a better solution for those moving liquid products. As an organization delivering a comprehensive model to the industry, PODS is a thriving community of operators and vendors working together to design a comprehensive model for the industry. This collection of subject matter expertise is invaluable to operators – and provides an opportunity to share your experience with like-minded individuals.

2) Existing model: What are you using now?

As you consider moving to APR, understand that it’s going to require a data migration. The existing system will need to be mapped and loaded into the new solution. If you are currently using PODS and are a gathering, midstream, or transmission company, APR with PODS is probably the best solution to implement. It’s likely that your existing data will migrate more seamlessly, and the model will make more sense to those that manage and interact with the data.

If your organization is primarily gas distribution, and you’ve implemented a PODS model for a small subset of high-pressure assets in the system you manage, consider UPDM. You can take advantage of the intended benefits and consolidate those assets into a common platform.

3) Other programs: ILI, CIS, other survey, Cathodic Protection

If your company has a strong investment in recurring inspections, PODS again rises as the preferred model, especially considering the efforts of the PODS Next Generation initiative around how to efficiently store and process this data moving forward.

4) Interoperability

With the growing importance of importing and exporting data (due to acquisitions, divestitures, etc.), analysis, and reporting, a system that promotes standard mechanisms to exchange data becomes increasingly more important. With the work the PODS organization is putting into a data interchange standard, it again rises as the preferred model.

There isn’t just one approach, but there is a best approach for your organization

While this change is beneficial for operators, many things need to be considered before you commit to an approach. I hope my series of posts provides some clarity for you. To stay up-to-date on the data model landscape and the tools surrounding it, I encourage you to follow the PODS association and Esri. The work of these two organizations in the pipeline space is a great thing for our industry.

If you’d like to discuss any of these concepts further, or would like to have a conversation about which model is best for your implementation, please get in touch with me here. I, and the rest of the Energy team at Latitude, are eager to offer our years of expertise to help you.  

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Demystifying Pipeline Data Models

If you’re reading this, you’re likely involved with managing GIS pipeline data. If you aren’t, I recommend checking out an informative, relevant (and quite possibly more interesting) read on enhancing your GIS with integrations or connecting business processes to your GIS. If you’re still with me, strap in.

Why do we talk about data models so much in the pipeline space? From my years interacting with operators, vendors, and regulators, I believe it comes down to a handful of reasons: 

  The regulatory landscape; The need for thorough and accurate data; Meeting demands of complex implementation architectures; Maintaining interoperability; and Aligning with industry standards for linear referencing.

The pipeline data model landscape can be a difficult one to navigate. Operators work with significant amounts of data and there is no shortage of models to explore.

In my last post, I introduced ArcGIS Pipeline Referencing (APR). APR is at the core of an integrated offering from Esri that incorporates linear referenced GIS (LRS) into the ArcGIS® platform. APR focuses on the “core” of the LRS, with modeling of the data on the line (events) being stored in either a Pipeline Open Data Standard Next Generation (PODS) or a Utility and Pipeline Data Model (UPDM).

This is a slight deviation from previous approaches, which has introduced some confusion. PODS and UPDM provide database models to organize your pipeline data, while APR provides a set of tools to manage and interact with it inside your GIS. Hopefully the diagram below helps explain it a bit.

Legacy data models and their impact

With the emergence of Integrated Spatial Analysis Techniques (ISAT), pipeline operators have had methods to store data about their systems and the surrounding environment since at least the early 1990s (some methods probably pre-date that). These methods have continued to develop through the work of the PODS organization and contributors to the ArcGIS Pipeline Data Model (APDM).

Each of these have offered unique benefits to the industry, but they’ve also introduced unneeded fragmentation to the landscape. As I mentioned in my previous post, APR helps simplify this by providing consolidation.

Pipeline Open Data Standard (PODS)

PODS is the data model standard for the pipeline industry. Founded in 1998, PODS was developed to extend legacy models (ISAT), and provide a baseline for software solutions in the industry. Since that time, PODS has established itself as the industry standard.

The success of PODS is rooted in the unique nature of operators and vendors coming together to meet the storage, analysis, regulatory, and reporting needs of the industry. It is important to note that PODS is more than a data model: it’s a group of individuals coming together to discuss, evaluate, and establish the data needs for the industry. The work of the PODS organization extends well beyond how to model a pipeline in a database.

PODS exists predominately in two variations: PODS Relational and PODS Spatial. Both models share a structure and format that adheres to the PODS standards, but differ in how they’re implemented. PODS Relational leverages core relational database standards, and PODS Spatial provides a native implementation for Esri Geodatabases.

Important to note: even though PODS Relational is designed as a GIS-agnostic data model (i.e. it’s not a geodatabase), most every implementation I have worked with has vendor-developed implementation methods and toolsets that integrates with Esri’s ArcGIS platform.

ArcGIS Pipeline Data Model (APDM)

APDM is the Esri pipeline data model template for pipeline assets. As with all of the models provided by Esri, APDM is a method for operators to access a structured data model, free of charge, in full support of an Esri implementation.

The template nature of APDM differs from the standards designation of PODS by allowing any portion of the base template to be altered to meet implementation requirements. This flexibility is the single biggest deviation from the standards-driven approach of PODS. Another separation between APDM and PODS is that APDM focuses on the features that make up the pipeline network itself, and is not intended to be as encompassing as the PODS models.

With the release of the UPDM, APDM has ultimately been retired.

Utility and Pipeline Data Model (UPDM)

As mentioned, UPDM has essentially replaced APDM as the recommended Esri pipeline data model.  This model provides an implementation foundation for gas and hazardous liquids industries. UPDM has been designed to work with or without the APR linear referencing component of the ArcGIS platform.

Most importantly, UPDM is the first model released that allows vertically-integrated utilities (gas distribution companies that operate regulated, high-pressure lines) to consolidate database schemas, and centralize data management to a single model.

Conclusion

I hope this post has helped demystify the world of pipeline data models, as there is a lot to consider and it can be difficult to understand.

Next week, I will dive into what you should consider when choosing the best pipeline data model for your operation, including the limitations of different models, how APR is addressing the limitations, and the questions you should be asking yourself.

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See the United Nations present at the 2017 Geocortex User Conference

We are thrilled to announce that the United Nations Department of Safety and Security (UNDSS) will be presenting at this year’s Geocortex User Conference!

The UNDSS provides safety and security services to 120,000 UN personnel in 117 countries, many of which work in challenging environments with increased risk to personal safety. Protecting UN personnel and enabling them to do their work is at the heart of what the UNDSS does.

 

To be successful, they must be coordinated, informed, and proactive. They maintain safety by analyzing threats, coordinating security in the field, supporting peacekeeping, collaborating with NGOs, and providing security at major events.

Andre Dehondt and Hwa Saup Lee of the UNDSS Crisis Management Information Support Section will present how their GIS helps them support this mission. Their systems provide critical information to decision makers that allows them to fulfill their duty of care obligations. Geocortex is currently used as the foundation for their Threat and Risk Assessment and Mobile Travel Advisory applications.

This is a presentation you won’t want to miss! The UNDSS does extremely important work, and they are a great example of how a GIS can help save lives and protect critical infrastructure.

We’re less than a month away from the Geocortex User Conference

This will be our first in-person conference in more than 10 years, and it’s sure to be a fun, informative, and inspiring few days! The conference takes place October 24 & 25 in Washington, DC. You can learn more about the 2017 Geocortex User Conference and register using the button below.

 

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What is ArcGIS Pipeline Referencing and why should you be paying attention to it?

ArcGIS Pipeline Referencing (APR) is an extension to Esri’s ArcGIS platform that provides an event-based GIS, with native support for linear referenced systems (LRS), through standard Esri tools. APR allows pipeline operators to standardize data management and take advantage of established patterns for connecting this data with other business systems.

 

APR addresses many challenges pipeline operators have faced over the years. From consolidating multiple editing environments to providing a single solution that caters to gathering, midstream, transmission, and distribution assets, APR is enabling companies to get more from their investment in spatial data. Coupling this extension with the ArcGIS platform provides a level of integration and visibility previously unrealized in this space.

Why does it exist?

Linear referenced GIS exists across multiple industries, including roads and highways, pipelines, rail, and water/wastewater. While there are differences in how LRS is implemented within these industries, the core principles are the same: provide linear features representing the location of the asset to the Earth (the centerline); provide a standard method to reference features on the line (the linear referencing); and locate appurtenances to the line (the events).

Through the years, proprietary implementations of LRS systems have been built across many verticals. This has resulted in a complex and fragmented approach managing linear referenced data in a GIS. APR provides consolidation to this landscape, and lays the foundation for next-generation solutions.

What are the benefits to operators?

Operators stand to be the biggest benefactors of Esri providing a native pipeline referencing solution.

Standardization: With the history of divergent data model implementations in the pipeline space, operators are limited to software that supports their underlying LRS. APR is disrupting the status quo, and establishing a new baseline, ultimately allowing you to select the most effective solution for your needs, without the restriction of compatibility to your data model implementation.

Data Governance: The tight coupling of GIS and linear referencing benefits those relying on high-quality, accurate data. With the rise in GIS, and Esri driving the adoption, many GIS technicians and analysts are already knowledgeable in how to manage spatial data with Esri technology. Standardizing on APR provides operators with access to a broader range of technical staff that are capable of managing LRS data.

Consolidation: With APR, multiple linear referenced systems can be supported in the same model. Many operators manage assets across a large supply chain. Long-haul transmission lines have established patterns relying on engineering stationing, while those overseeing gathering and distribution assets tend to forgo true engineering stationing in lieu of routes and measures. Before APR, this meant implementing multiple data models, bringing with it varied methods for managing the data. Now you can consolidate: one system, one model, and one set of editors can manage all assets with the same tools.

What is UPDM (Utility and Pipeline Data Model) and how does it relate to APR?

UPDM is an accompanying data model to APR with a focus on unifying the implementation of vertically-focused operators. While UPDM provides an effective data repository, it is not the only data model compatible with APR. For example, the PODS Association is building the Next Generation model in compliance with APR. 

The question then becomes, what data model should you choose for your implementation? I will be following up this post with a deep dive into the many data models that are available, and hopefully I can help you make better sense of these options.

Why are we engaged in this conversation?

Latitude Geographics provides solutions to gathering, midstream, transmission, and distribution clients around the world. In the past year, we’ve seen a sharp rise in the number of operators implementing and embracing APR. Geocortex has been 100% compatible with every implementation we’ve worked on, providing immediate value for clients leveraging PODS and UPDM. 

With the release of powerful linear referenced toolsets, Geocortex can further your success with APR. Please reach out to This email address is being protected from spambots. You need JavaScript enabled to view it. for more information.

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