The National Institute of Invasive Species Science (NIISS) Global Organism Detection and Monitoring (GODM) system data setEntry ID: USGS_BRD_NIISS
Abstract: The National Institute of Invasive Species Science (NIISS) Global Organism detection and Monitoring (GODM) system data set is a global data set of invasive species occurrence records that focuses on the United States. The data set is a compilation of integrated data sets and individual data contributions that all contain the core elements of who, what, where, and when. The minimal data required ... for inclusion within this data set include what species was found, where the species was found, by whom the species, found, and on which day was the species found. In some cases, archival data sets important for range distributions for key species have been included that only contained the year in which the species was observed. In these cases, the January 1st day was used for the given year.
The purpose of this data set is to provide a consistent nationwide database for the occurrences of invasive species throughout the United States. The primary uses of these data are thought to be for large scale spatial modeling and range distribution studies for the invasive species of the United States. These data may provide useful data for regional scale analyses and nation scale analyses. The data set may also contain attributes for species (e.g. percent cover, height, sex, weight etc.).
Data Set Citation
Dataset Originator/Creator: Dr. Thomas J. Stohlgren, Dr. Jim Graham, Dr. Catherine Jarnevich, Greg Newman, and Alycia Crall
Dataset Title: The National Institute of Invasive Species Science (NIISS) Global Organism Detection and Monitoring (GODM) system data set
Dataset Release Date: 2006-01-26T00:00:00.000Z
Version: Not provided
Data Presentation Form: Maps and DataOnline Resource: http://www.niiss.org
Start Date: 1911-03-14Stop Date: 2008-08-07
Quality The accuracy report varies for each dataset contributed to our websites and for each project these data reside within.
The NIISS GODM system uses controlled vocabulary based data standards to populate pick lists from which end users choose a result. These controlled vocabularies ensure data standardization. Our system also uses quality assurance / quality ... control measures such as checking incoming Latitude and Longitude coordinates against possible values (e.g. Longitude cannot be less than -180 or greater than 180 for example). Other data quality measures employed include ensuring that a zone was recorded and selected when contributing UTM data and preventing completion of data submittal until a zone is chosen.
Some topological errors in polygon data contributed that inherently contained the topological errors.
Currently, treatment data specifying the amount of a given chemical used and the exact solution mixed used are missing.
The horizontal dilution of precision and the vertical dilution of precision gave not been incorporated into our database yet. However, we are working on implementing these new features for our field tolls that make use of capturing GPS data from the NMEA standard output. We cannot however, ever ensure these data for data contributed that have not used our field tools for use with PDA devices with a GPS unit.
The processing steps involve data conversion to SI units upon data upload to our websites. The date of these processing steps varies depending upon the date of each data contribution.
Access Constraints No access and/or use constraints that are not otherwise handled by the data system. Some data have been flagged as sensitive data and these data are shown in detail to those who uploaded the data but are only shown as “fuzzed” data to the level the contributor specified when flagging the data as sensitive. Levels of fuzzy data can be at various levels of quarter quadrat grids across the United States and the world.
Use Constraints Data use: see (http://www.niiss.org/cwis438/UserManagement/NIISSDataUse.php)
(1) The quality and completeness of data cannot be guaranteed. Users employ these data at their own risk.
(2)Users must publicly acknowledge, in conjunction with the use of the data, the data providers whose invasive species data they have used. Data providers may require additional attribution of specific collections within their institution.
Data sharing: see (http://www.niiss.org/cwis438/UserManagement/NIISSDataSharing.php).
Data Set Progress
Distribution Format: Excel
Role: TECHNICAL CONTACT
Phone: (970) 491-0410
Fax: (970) 491-1965
Email: newmang at nrel.colostate.edu
Natural Resources Ecology Laboratory, Colorado State University
City: Fort Collins
Province or State: Colorado
Postal Code: 80523
Role: METADATA AUTHOR
Email: alicia.m.aleman at nasa.gov
Goddard Space Flight Center Code 610.2
Province or State: MD
Postal Code: 20771
Extended Metadata Properties
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Creation and Review Dates
DIF Creation Date: 2008-09-10
Last DIF Revision Date: 2018-05-15