Summary

Data supporting Navigation Systems and infrastructure is about collaboratively managing and applying data associated with the infrastructure assets to improve across the asset lifecycle across planning, design, construction, decision making, authority, operations, and maintenance. This data is a means to provide the greatest visibility to an enterprise’s navigable data assets to those who need it, when they need it and at the right level of detail to better inform decisions and actions.

Data is created and updated continuously during the lifecycle of an asset. Data is created and maintained generally in separate workflows by forms, sensors, mapping, field collection, systems, surveys, and more. To allow for data integration and best fit for use, data – including all entities, attributes, values, and relationships – require processes that data suppliers can use to create, update, read, and deliver in a manner that allows optimal interoperability, veracity, validation, tracking. In turn, users of the data require delivery of data such that the data is findable, accessible, interoperable, and reusable.

Problem and Solution

Data governance is the essential foundational activity of these aforementioned processes for enterprises. It guides and enables suppliers and stakeholders. They then apply data assets to be used in the next level of knowledge and wisdom solutions in decision support, modeling, analytics, visualization, and more. It includes supply chain management to ensure data acquisition, production, and product generation. Also, it is reliable, sustainable, and meets readiness and quality needs. It also involves deploying governance components, guiding standards and best practices for delivery platforms and data preservation.

Xentity worked to develop a data maturity model. Also, prepare an authoritative data source (ADS) implementation guide. Furthermore, conduct a pilot investigation for NDC’s navigation systems.

These tasks describe data governance dimensions and components and the elements associated with them. There are actions and milestones that plan to achieve and are presented aligned to target maturity objectives and data source and asset alignment improvements. By applying the requested guidance for the maturity model, authoritative data source, and reference architecture, resulting proposed actions and milestones to assess the current state-of-practice and develop can result in a roadmap with a clear set of actions.

Outcome and Benefit

We developed a data maturity model that will enable process improvement and mature management capability of NDC’s data assets. Through our approach to inventory ADS Store, interfaces, stewardship and process interactions, while defining a data portfolio taxonomy (data reference model), this creates a basis for the reference architecture. Furthermore, we created an inventory of publicly available data, with descriptions and metadata on these publications, creating the descriptions and metadata records as needed.

Also, we created and updated metadata for all NDC systems, tables, data services and reports. Furthermore we created and deployed to production a common NDC splash page. This incorporated information on all NDC systems and their metadata, and provided quick access to all available services and reports. Also, we created and deployed to production an internal USACE data services tool. Also, an external USACE data services tool. Finally we created a new tool to replace the deprecated navigation project profile and lock characteristics modules.