This vignette describes minimum data requirements of the R package glatos to inform loading of data that is not in standard file formats of the Great Lakes Acoustic Telemetry Observation System (GLATOS) or the Ocean Tracking Network (OTN). Strictly speaking, there are no requirements of the glatos package as a whole, but input data are checked within each individual function to determine if requirements are met. The set of data requirements described in this vignette, if followed, will ensure compatibility with all glatos functions.
For data in standard GLATOS and OTN formats, use of built-in data loading functions (see the Data Loading vignette for details) will ensure that resulting data objects meet the requirements of glatos functions. For reference, the appendix provides data field definitions (data dictionary) of standard data files obtained from the GLATOS Data Portal.
glatos functions that accept detection data as input will typically require a data.frame with one or more of the following columns, named and defined exactly as described below:
Additionally, some functions will require at least one categorical column to identify location (or group of locations). These can be specified by the user, but examples of such columns in a GLATOS standard detection file are:
Any data.frame that contains the above columns should be compatible with all glatos functions that accept detection data as input. Use of the data loading functions read_glatos_detections and read_otn_detections will ensure that these columns are present, but can only be used on data in GLATOS and OTN formats. Data in other formats will need to be loaded using other functions (e.g., read.csv, fread, etc.) and compatibility with glatos functions will need to be carefully checked. For data loading examples, see the Data Loading vignette.
glatos functions that accept receiver location data as input will typically require a data.frame with one or more of the following columns, named and defined exactly as described below:
Additionally, some functions will require at least one categorical column to identify location (or group of locations). These can be specified by the user, but examples of such columns in a GLATOS standard receiver locations file are:
Use of the data loading function read_glatos_receivers will ensure that these columns are present, but can only be used on data in GLATOS format. Data in other formats will need to be loaded using other functions (e.g., read.csv, fread, etc.) and compatibility with glatos functions will need to be carefully checked. For data loading examples, see the Data Loading vignette.
There are currently no glatos functions that require animal tagging and biological data other than those columns present in the required detection data. Therefore, there are no formal requirements of such data in the package. Nonetheless, the read_glatos_workbook function can be used to facilitate loading animal tagging and biological data from a standard GLATOS project workbook (*.xlsm file) into an R session.
Use of the data loading function read_glatos_workbook will ensure that animal data are loaded efficiently and consistently among users, but can only be used on data in GLATOS format. Data in other formats will need to be loaded using other functions (e.g., read.csv, fread, etc.). Although there are currently no glatos requirements of animal data, any future requirements might be expected to be consistent with the glatos_animals class.
There are currently no glatos functions that require transmitter specification data. Therefore, there are no formal requirements of such data in the package. Nonetheless, the read_vemco_tag_specs function can be used to facilitate loading transmitter specification data from a standard VEMCO tag spec (*.xls) file provided to tag purchasers from VEMCO.
Use of the data loading function read_vemco_tag_specs will ensure that transmitter specification data are loaded efficiently and consistently among users, but can only be used on data in VEMCO standard format. Data in other formats will need to be loaded using other functions (e.g., read.csv, fread, etc.). Although there are currently no glatos requirements of transmitter specification data, any future requirements might be expected to be consistent with the output of read_vemco_tag_specs.
Most glatos data loading functions return an object with a glatos-specific S3 class name (e.g., glatos_detections) in addition to a more general class (e.g., data.frame). Currently, no methods exist for glatos classes and such classes are not explicitly required by any function, so glatos classes can merely be thought of as labels showing that the objects were produced by a glatos function and will therefore be compatible with other glatos functions. Beware, as with any S3 class, that it is possible to modify a glatos object to the point that is will no longer be compatible with glatos functions. Starting with glatos version 0.8.0, there are constructor and validator functions (e.g., glatos_detections(), as_glatos_detection(), validate_glatos_detections()) to help create and check glatos_animals, glatos_receivers, and glatos_detections objects.
Detection data from the GLATOS network are queried for each individual project and made available through the project-specific GLATOS Data Portal. Each detection export is a zipped folder that contains multiple files. This appendix describes the structure of two of the comma-separated-value files (.csv) contained in the standard export: detections and receiver locations. These files can be identified by file name. The file that contains “detectionsWithLocs” (e.g., “HECWL_detectionsWithLocs_20180627_172857.csv”) contains detections from acoustic receivers in the GLATOS network for all tags in a project. This file contains columns that identify when and where a fish was released and detected, some biological attributes of tagged fish, and tag model and specs. The .csv file with “receiverLocations” in the file name contains deployment and recovery operating schedules for all receivers in the GLATOS network. By combining the information in these two files, researchers are able determine when and where a tagged fish was detected in the GLATOS network and also locations where receivers were deployed that did not detect their tagged fish. Fields (columns) in both files are described below.
A comma-separated-values text file with the following columns:
A comma-separated-values text file with the following columns:
A macro-enabled Microsoft Excel workbook (*.xlsm) file containing the following worksheets:
For more details about the structure of this file, see the Data Submission Package in the GLATOS Data Portal.