Data Management Plan
GUID: gov.noaa.nmfs.inport:47870 | Published / External
Data Management Plan
DMP Template v2.0.1 (2015-01-01)
Please provide the following information, and submit to the NOAA DM Plan Repository.Reference to Master DM Plan (if applicable)
As stated in Section IV, Requirement 1.3, DM Plans may be hierarchical. If this DM Plan inherits provisions from a higher-level DM Plan already submitted to the Repository, then this more-specific Plan only needs to provide information that differs from what was provided in the Master DM Plan.
1. General Description of Data to be Managed
The Coastal Program of Delaware's Division of Soil and Water conservation (DNREC), the University of Delaware, Partnership for the Delaware Estuary, and the New Jersey Department of Environmental Protection have partnered and are carrying out a bottom and sub-bottom imaging project to identify and map the benthic habitat and sub-bottom sediments of Delaware Bay and River. This project was initiated to better understand the distribution of bottom sediment types, habitat biodiversity, and most importantly, human's impact on the bay bottom and its living resources. The project integrates the use of three types of acoustical systems: Roxann Seabed classification system, chirp sub-bottom profiling, and multi-beam bathymetric mapping. Verification of the acoustic data with bottom and sub-bottom sediments is performed through the collection of bra banc core samples and underwater video images.
Original contact information:
Contact Org: NOAA Office for Coastal Management
Phone: 843-740-1202
Email: coastal.info@noaa.gov
Notes: Only a maximum of 4000 characters will be included.
Notes: Data collection is considered ongoing if a time frame of type "Continuous" exists.
Notes: All time frames from all extent groups are included.
Notes: All geographic areas from all extent groups are included.
(e.g., digital numeric data, imagery, photographs, video, audio, database, tabular data, etc.)
(e.g., satellite, airplane, unmanned aerial system, radar, weather station, moored buoy, research vessel, autonomous underwater vehicle, animal tagging, manual surveys, enforcement activities, numerical model, etc.)
2. Point of Contact for this Data Management Plan (author or maintainer)
Notes: The name of the Person of the most recent Support Role of type "Metadata Contact" is used. The support role must be in effect.
Notes: The name of the Organization of the most recent Support Role of type "Metadata Contact" is used. This field is required if applicable.
3. Responsible Party for Data Management
Program Managers, or their designee, shall be responsible for assuring the proper management of the data produced by their Program. Please indicate the responsible party below.
Notes: The name of the Person of the most recent Support Role of type "Data Steward" is used. The support role must be in effect.
4. Resources
Programs must identify resources within their own budget for managing the data they produce.
5. Data Lineage and Quality
NOAA has issued Information Quality Guidelines for ensuring and maximizing the quality, objectivity, utility, and integrity of information which it disseminates.
(describe or provide URL of description):
Process Steps:
- 2008-01-01 00:00:00 - Bivalve Reef (Oyster, Identified Oyster, and Corbicula) polygons were derived from the bottom sediment map that were constructed by the utilization of a Roxann Seabed Classification System and extensive sediment grab samples bottom sediment map that were constructed by the utilization of a Roxann Seabed Classification System and extensive sediment grab samples. Corbicula fluminea beds were identified on the Roxann output by the occurrence of data point which had moderate to high hardness return (E2) and an anomalously high roughness return (E1), as compared to the adjacent sediments. The sediments surrounding these beds are usually of a finer (silt to clay) grain size, with low roughness and hardness values. The regions where these types of returns were encountered were then sampled with a grab sampler. Several samples (2 to 3 samples) were collected at each station to increase the likely hood that Corbicula would be encountered, if it was indeed located in that region. Corbicula beds can have varying densities, distributions, and bed configurations; hence this sampling scheme was enacted to account for this spatial variability. Submersed Rooted Vascular Plants (Vallisneria Americana) beds outlines were identified through the same bottom sediment map used for delineating bivalve reef. SRV beds were identified on the Roxann output by the occurrence of data point which had very low hardness returns (E2) and an anomalously high roughness return (E1), as compared to the adjacent sediments. The regions where these types of returns were encountered, where then sampled with a grab sampler. Several samples (2 to 3 samples) were collected at each station to increase the likely hood that SAV would be encountered, if it was indeed located in that region. SAV beds can have varying densities, distributions, and bed configurations; hence the sampling scheme was enacted to account for this spatial variability. Outcrop areas consist of Cretaceous sediment that is at the river bottom surface (or near the surface ~1 to 2 cm). These areas are scour or erosional zones within the river. The outcropping material consists of highly compacted/de-watered silty fine sand to fine sandy silts, which contain relict burrow casts and glauconite. Outcrop boundaries were derived from the bottom sediment map raster grid.
- 2008-01-01 00:00:00 - The bottom sediment map was constructed by the utilization of a Roxann Seabed Classification System and extensive sediment grab samples. Data was collected in a gridded trackline configuration, with tracklines spacing of 100 meters parallel to the shoreline and 200 meters perpendicular to the shoreline. This project is an extension of the work currently being performed in Delaware waters by DNREC's Delaware Coastal Program's Delaware Bay Benthic Mapping Project. The bottom sediment point data, which has been classified according to the existing benthic mapping Roxann box plot, are converted from a number that categorizes the point according to its corresponding box (in the Roxann) into a number which reflects the sediment properties of each box in relation to one another. A ranking scale is used to allow a statistical gridding scheme to interpolate between sediment data points, while minimizing erroneous sediment classifications and allowing gradational sediment deposits to be gridded. A ranking scale from 0 to 28 was used for this project, with 0 representing the finest grained classifications (fluidized clay) and 28 representing the coarsest grained classifications (dense shell material). Table 1 illustrates the distribution of sediment classifications along the ranking scale, which takes into account the relation of sediment types and grain sizes to one another using both the Wentworth Scale and Shepard's classification system. Finer grains are more similar in their deposition environments, such as clay and silts, because they reflect similar current regimes, sorting, and reworking patterns (Poppe et al., 2003). While coarse sediments are much more dissimilar to finer grains, with respect to current velocities, sorting, and winnowing, the finer grains are much more closely related in their sediment diameters that the coarser grains as you increase in Phi size and/or diameter. These account for the close clustering of coarse grained deposit descriptions at the upper end of the ranking scale, while the finer grained sediments show a gradation as you increase in the rating scale.
- 2008-01-01 00:00:00 - The bottom sediment data is gridded in Surfer degrees 8, a surface and terrain modeling program, using block kriging and a nugget effect. This statistical griding technique estimates the average value of a variable within a prescribed local area (Isaaks and Srivastava, 1989). Block kriging utilizes the existing point data values, weights the values of the data depending upon the proximity to the point being estimated, to discretize the local area into an array of estimated data value points and then averaging those individual point estimates together to get an average estimated value over the area of interest (Isaaks and Srivastava, 1989). A variogram is constructed for the data, and the resultant spatial model that is developed from the variogram is used in the block kriging surface model to more accurately interpolate the sediment data . The fitted model was a nugget effect (with an error variance of 21.8%) and a linear model (with a slope of 0.00286 and an anisotropy of 1, which represents a complete lack of spatial correlation).The accuracy of the estimation is dependent upon the grid size of the area of interpolation, the size of each cell within the grid, and the number of discretized data points that are necessary to estimate the cells within that grid spacing. The grid size that was used to interpolate the bottom sediment maps was 442 lines x 454 lines, with a cell size of 44.93 m2. The nugget effect is added to allow the griding to assume there is very little, if any, lateral correlation or trends within the bottom sediment (Isaaks and Srivastava, 1989). The nugget effect model entails a complete lack of spatial correlation; the point data values at any particular location bear no similarity even to adjacent data values (Isaaks and Srivastava, 1989). Without the nugget effect the gridding would assume that you could only have a linear progression of sediment types and would insert all the sediment types along the scale between two sediment types (i.e. silty fine to medium sands and fine to medium sand with varying amounts of pebbles would be inserted between fine sand and coarse sand even though that is not what is occurring along the bottom. The sediment data is gridded with no drift for the data interpolation, also helping to minimize erroneous classifications. Sediment Classification Ranking Sediment Description 0-11-2 Clay, 2-33-44-55-66-7 Silt,7-88-9 Sandy Silts, 9-1010-11 Fine Sand, 11-1212-13 Silty Fine to Medium Sands, 13-14 Silty Medium Sand, 14-1515-16 Fine to Medium Sand, 16-1717-18 Fine to Medium Sand with abundant shell material and/or pebbles, 18-1919-20 Coarse Sand with varying amounts of pebbles, 20-2121-2222-23 Moderate Shell Material/Sandy Pebbles, 23-2424-2525-26 Abundant Shell Material/Gravel, 26-2727-28 Dense Oyster Shell.
- 2012-01-01 00:00:00 - Separate shapefiles for oyster beds, identified oyster beds, SAV, corbicula, outcroppings, and depositional zones were integrated into a single feature layer to produce a comprehensive benthic cover polygon data set using the ArcMap 10 Merge tool. A review of the bottom sediment raster data sets (Delaware River/Bay, Upper Shelf, and Roxann 2004 which lies along the Delaware near-shore area) indicated that they consisted entirely of various types of unconsolidated sediments ranging from fluidized clay to oyster shells. Each of these rasters were converted into a single Unconsolidated Sediments polygon layer, merged together and then joined with the other features (oyster, SAV, etc.) to form a continuous benthic cover layer for the entire project area. As a final step habitat classes from the Florida System for Classifying Habitats in Estuarine and Marine Environments (SCHEME) were added to the attribute table for this single polygon file to ensure consistency with other Digital Coast benthic cover data sets.
- 2012-01-01 00:00:00 - The bottom sediment maps (source for the unconsolidated sediments polygons in the vector data set) were constructed by the utilization of a Roxann Seabed Classification System and extensive sediment grab samples. Data was collected in a gridded trackline configuration, with tracklines spacing of 100 meters parallel to the shoreline and 200 meters perpendicular to the shoreline.This project is an extension of the work currently being performed in Delaware waters by DNREC's Delaware Coastal Program's Delaware Bay Benthic Mapping Project.The bottom sediment point data, which has been classified according to the existing benthic mapping Roxann box plot, are converted from a number that categorizes the point according to its corresponding box (in the Roxann) into a number which reflects the sediment properties of each box in relation to one another. A ranking scale is used to allow a statistical griding scheme to interpolate between sediment data points, while minimizing erroneous sediment classifications and allowing gradational sediment deposits to be gridded. A ranking scale from 0 to 28 was used for this project, with 0 representing the finest grained classifications (fluidized clay) and 28 representing the coarsest grained classifications (dense shell material). This ranking scale takes into account the relation of sediment types and grain sizes to one another using both the Wentworth Scale and Shepard's classification system. Finer grains are more similar in their deposition environments, such as clay and silts, because they reflect similar current regimes, sorting, and reworking patterns (Poppe et al., 2003). While coarse sediments are much more dissimilar to finer grains, with respect to current velocities, sorting, and winnowing, the finer grains are much more closely related in their sediment diameters that the coarser grains as you increase in Phi size and/or diameter. These account for the close clustering of coarse grained deposit descriptions at the upper end of the ranking scale, while the finer grained sediments show a gradation as you increase in the rating scale.
- 2012-01-01 00:00:00 - The bottom sediment data is gridded in Surfer degrees 8, a surface and terrain modeling program, using block kriging and a nugget effect. This statistical griding technique estimates the average value of a variable within a prescribed local area (Isaaks and Srivastava, 1989). Block kriging utilizes the existing point data values, weights the values of the data depending upon the proximity to the point being estimated, to discretize the local area into an array of estimated data value points and then averaging those individual point estimates together to get an average estimated value over the area of interest (Isaaks and Srivastava, 1989). A variogram is constructed for the data, and the resultant spatial model that is developed from the variogram is used in the block kriging surface model to more accurately interpolate the sediment data . The fitted model was a nugget effect (with an error variance of 21.8%) and a linear model (with a slope of 0.00286 and an anisotropy of 1, which represents a complete lack of spatial correlation).The accuracy of the estimation is dependent upon the grid size of the area of interpolation, the size of each cell within the grid, and the number of discretized data points that are necessary to estimate the cells within that grid spacing. The grid size that was used to interpolate the bottom sediment maps was 442 lines x 454 lines, with a cell size of 44.93 m2. The nugget effect is added to allow the griding to assume there is very little, if any, lateral correlation or trends within the bottom sediment (Isaaks and Srivastava, 1989). The nugget effect model entails a complete lack of spatial correlation; the point data values at any particular location bear no similarity even to adjacent data values (Isaaks and Srivastava, 1989). Without the nugget effect the griding would assume that you could only have a linear progression of sediment types and would insert all the sediment types along the scale between two sediment types (i.e. silty fine to medium sands and fine to medium sand with varying amounts of pebbles would be inserted between fine sand and coarse sand even though that is not what is occurring along the bottom. The sediment data is gridded with no drift for the data interpolation, also helping to minimize erroneous classifications. Sediment Classification Ranking Sediment Description: 0-11-2 Clay, 2-33-44-55-66-7 Silt, 7-88-9 Sandy Silts, 9-1010-11 Fine Sand, 11-1212-13 Silty Fine to Medium Sands, 13-14 Silty Medium Sand, 14-1515-16 Fine to Medium Sand, 16-1717-18 Fine to Medium Sand, with abundant shell material and/or pebbles, 18-1919-20 Coarse Sand, with varying amounts of pebbles 20-2121-2222-23 Moderate Shell Material / Sandy Pebbles, 23-2424-2525-26 Abundant Shell Material / Gravel 26-2727-28 Dense Oyster Shell
- 2015-01-01 00:00:00 - The data were converted from a single ESRI polygon shapefile classified according to the System for Classifying Habitats in Estuarine and Marine Environments (SCHEME) to the Coastal and Marine Ecological Classification Standard (CMECS) 2012 format (which can be found at https://coast.noaa.gov/digitalcoast/tools/cmecs-crosswalk) which produces separate geoform, substrate, and substrate feature layers from the original input benthic habitat dataset. This substrate feature layer contains CMECS substrate component attributes where an "Equal" or "Nearly Equal" SCHEME value was present in the original data. Polygons for which no substrate information was present have been removed. No other changes to the original polygon boundaries or any other alterations of the original SCHEME data were made during this process.
(describe or provide URL of description):
6. Data Documentation
The EDMC Data Documentation Procedural Directive requires that NOAA data be well documented, specifies the use of ISO 19115 and related standards for documentation of new data, and provides links to resources and tools for metadata creation and validation.
Missing/invalid information:
- 1.7. Data collection method(s)
- 3.1. Responsible Party for Data Management
- 4.1. Have resources for management of these data been identified?
- 4.2. Approximate percentage of the budget for these data devoted to data management
- 5.2. Quality control procedures employed
- 7.1. Do these data comply with the Data Access directive?
- 7.1.1. If data are not available or has limitations, has a Waiver been filed?
- 7.1.2. If there are limitations to data access, describe how data are protected
- 7.3. Data access methods or services offered
- 7.4. Approximate delay between data collection and dissemination
- 8.1. Actual or planned long-term data archive location
- 8.3. Approximate delay between data collection and submission to an archive facility
- 8.4. How will the data be protected from accidental or malicious modification or deletion prior to receipt by the archive?
(describe or provide URL of description):
7. Data Access
NAO 212-15 states that access to environmental data may only be restricted when distribution is explicitly limited by law, regulation, policy (such as those applicable to personally identifiable information or protected critical infrastructure information or proprietary trade information) or by security requirements. The EDMC Data Access Procedural Directive contains specific guidance, recommends the use of open-standard, interoperable, non-proprietary web services, provides information about resources and tools to enable data access, and includes a Waiver to be submitted to justify any approach other than full, unrestricted public access.
Public Information
Notes: The name of the Organization of the most recent Support Role of type "Distributor" is used. The support role must be in effect. This information is not required if an approved access waiver exists for this data.
Notes: This field is required if a Distributor has not been specified.
Notes: All URLs listed in the Distribution Info section will be included. This field is required if applicable.
Notes: This field is required if applicable.
8. Data Preservation and Protection
The NOAA Procedure for Scientific Records Appraisal and Archive Approval describes how to identify, appraise and decide what scientific records are to be preserved in a NOAA archive.
(Specify NCEI-MD, NCEI-CO, NCEI-NC, NCEI-MS, World Data Center (WDC) facility, Other, To Be Determined, Unable to Archive, or No Archiving Intended)
Notes: This field is required if archive location is World Data Center or Other.
Notes: This field is required if archive location is To Be Determined, Unable to Archive, or No Archiving Intended.
Notes: Physical Location Organization, City and State are required, or a Location Description is required.
Discuss data back-up, disaster recovery/contingency planning, and off-site data storage relevant to the data collection
9. Additional Line Office or Staff Office Questions
Line and Staff Offices may extend this template by inserting additional questions in this section.