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Introduction to Digital Nautical Chart (DNC) enterprise production

In the past, data was stored in a set or many sets of files that a limited number of people could access or edit. With the geodatabase as the data store, the data is seamless and can be viewed and edited by multiple people. This minimizes the effort required to bring file-based datasets into a single data store for seamless usability. The sources may include both images and vectors in any number of projections, which do not need to be physically projected to a common projection to be usable in ArcMap.

In an enterprise environment, data is stored in a Digital Nautical Chart (DNC) Nautical Information System (NIS) database for editing and maintenance. One of the benefits the NIS database offers is that multiscale data can be stored in a central location for easy editing access. When implementing the DNC NIS, there are some decisions that an organization needs to make. First it needs to choose a database format to use for the NIS, such as PostgreSQL, Oracle, or SQL Server. Once configured, the database is then ready to load the DNC NIS schema. Each feature class in the NIS schema contains the field Library_Chart_Type, which identifies the DNC library scale of the feature data.

Production environment

The ArcMap environment accommodates many tasks from data automation to analysis and map production. There are many toolbars that are not exposed and must be exposed when required for a given task. Through the Customize menu, the ArcMap environment can be quickly adjusted. Select a task within the Toolbars environment option on the Customize menu, and toolbars are automatically added and removed to better accommodate the task. The Customize Mode option on the Customize menu also provides quick access to Esri Production Mapping commands that are less often used. The Customize menu can also be used to support other task requirements.

Data quality

Data quality is ensured through several methods. In-process automated quality control is built in to the database model and controls the available attribute values for many fields. Production Mapping extends the in-process automated quality control and includes tools that can be used to discover and log data errors for review and correction cycles. Both automated and manual quality controls are employed to ensure high-quality data.

Tasks

With the addition of the Production Mapping tools, tasks are streamlined by making the tools used to complete the task available with one click. Some of the tools on the Production Mapping toolbars are available through standard ArcMap menus, but most are not available with one click. The production environment, with the additional Production Mapping tools, can be quickly adjusted to the task, which streamlines the process.

Production process

There is an implied order to production. While quality control is discussed after data editing, it does not have to be implemented only at the end of production. Quality control processes should be run as needed to ensure that data is extracted properly throughout the project. The order in which features are extracted should be planned as part of a project process plan.

DNC editing considerations

There are many considerations when editing, maintaining, and providing quality control for a database. Some things to consider are the purpose of the database, what the intended use is for the data, what scale the data represents, what the target accuracy is of the data extracted, and whether the accuracy target makes sense with the sources available. These are all important things to consider when developing a production plan and quality assurance (QA) program. Other things that may be necessary to consider are the diversity and experience of the workforce and its distribution. It is much more difficult to ensure consistency of data extraction and quality control when the workforce is disconnected, which may impact both the production plan and the quality assurance program.

Before getting started with extraction for DNC, become familiar with the Individual Library Instruction (ILI) provided by the National Geospatial-Intelligence Agency (NGA). The ILI document contains all the standard information regarding the library and any deviations from the normal flow that NGA may request.

The Table Of Contents window

There may be many feature classes of many types in the ArcMap Table Of Contents window (TOC). Because ArcMap draws features from the bottom of the TOC, feature order in the TOC is important. There may be many feature class order scenarios that make sense during editing. The Production TOC Manager toolbar can be used to remove empty feature classes, alphabetize them, and organize them by type. With the Production TOC Manager toolbar, having many feature classes in the TOC is more manageable.

Data frame display tools

The Tools toolbar provides the necessary tools for managing the display of the data. It also houses tools to interactively interrogate features and measure distances in the data frame.

Data dictionary

The database design must be understood to effectively extract data that is meaningful to the database. The data dictionary contains all the required features and the attributes that are used to describe the features. The database design reflects the data dictionary, and much of the content of the data dictionary is contained in the feature class domains. The ArcGIS 10.3.1 for Desktop help includes a digital data dictionary of the products that are installed.

Suggested production workflow

DNC production is a multiple-step process. It includes production preparation, feature creation and collection, quality control, and data conversion. The following outlines the overall process.

  1. Review ILI and prepare the Chart History document and Data Quality Worksheet.
    • Determine the scale of the geodatabase to be produced and get the template geodatabase.
    • Become familiar with any deviations from normal production flow for the library.
  2. Set up the DNC ArcMap environment.
  3. Check out the DNC replica database.
  4. Create Dqyarea.
  5. Georeference DNC images.
  6. Configure the DNC database for validation.
  7. Create ECR features:
    • Copy Dqyarea to Ecrarea.
    • Cut up Ecrarea into ground surface elements, open water, and islands.
  8. Create HYD features:
    • Copy open water from Ecrarea to Hydarea.
    • Cut up Hydarea into different depth curve areas.
    • Use depth curve areas to create depth lines.
  9. Capture OBS features.
  10. Capture POR features.
  11. Capture CUL features.
  12. Capture remaining features (including notes.rat).
  13. Review and incorporate NGA List of Lights or U.S. Coast Guard (USCG) Light List.
  14. Review and incorporate Notice to Mariners.
  15. Extraction quality control (QC) will be done by the original analyst.
  16. Independent QC cycle will be conducted and completed by an independent reviewer.
  17. Unit conversion.
  18. Data migration.
  19. Convert to VPF.
  20. Complete a VPF validation cycle.