schemas/vegbien.sql: taxonpath: descriptive comment: Clarified that this is the full path to a taxon, including all components of the taxonomic name
schemas/vegbien.sql: Replaced "scientific name" with "taxonomic name" for schema-wide consistency and for consistency with the taxon/taxonomic name vocabulary
schemas/vegbien.sql: taxonpath named ranks: Added descriptive comments for data dictionary
schemas/vegbien.sql: taxonpath columns other than named ranks: Added descriptive comments for data dictionary
schemas/vegbien.sql: taxonscope: descriptive comment: Reworded to make the first sentence a noun, for consistency with other descriptive table comments
schemas/vegbien.sql: taxon: descriptive comment: Added note that the taxonname stores only one rank (e.g. family) of the full identifying name
schemas/vegbien.sql: taxonpath: descriptive comment: Reworded to make the first sentence a noun, for consistency with other descriptive table comments. The convention is for the first "sentence" to be a noun which describes the entity that the table models.
schemas/vegbien.sql: comments: Removed units from comments on fields which already have a units suffix, to avoid having to keep the units in sync between the suffix and the comment. Note that the units were abbreviated equally in the suffixes and comments, so this did not result in a loss of information other than the ^ for a quantity squared (but it's obvious enough that m2 is m^2).
schemas/vegbien.sql: taxonscope: descriptive comment: Added period for consistency with other descriptive table comments
schemas/vegbien.sql: taxon: Added descriptive comment for data dictionary
schemas/vegbien.sql: VegBank-equivalent tables comments: Prepended "Equivalent to" before VegBank, so the equivalent tables statement can fit grammatically after a description of the table instead of having to be the first phrase in the descriptive table comment
schemas/vegbien.sql: taxon: VegBank-equivalent tables comment: Added plantName and applicable columns from plantStatus, which are also part of the taxon table
schemas/vegbien.sql: placepath: Added otherranks field, analogous to taxonpath.otherranks
schemas/vegbien.sql: taxonpath: Added descriptive comment for data dictionary
inputs/import.stats.xls: Updated import times
inputs/UNCC/Specimen/map.csv: accession: Documented that it's globally unique, although occasionally duplicated
inputs/REMIB/Specimen/map.csv: Remapped accession_number to catalogNumber because it is not globally unique, only (usually) unique within the institution providing the data ("acronym"). Note that there are nevertheless 11,869 rows where an accession_number appears multiple times within the same institution.
mappings/VegCore-VegBIEN.csv: Only use institutionCode+collectionCode+catalogNumber as the authorlocationcode (location-scoping ID) if there is actually a catalogNumber. Otherwise, the mapping process would attempt to create one location for each collection in the datasource, when there should be one location for each specimen.
schemas/py_functions.sql: _namePart(): Slice the first name from the beginning of the string to one word before the end, instead of one after the beginning, in order to avoid overlap with the last name, which starts one before the end, when there is only one word. Note that only one word means the name is assumed to be a last name. This assumption may not always be true, but when a datasource provides the name concatenated, an assumption must be made when not all name components are present.
schemas/vegbien.sql: party: Added check constraint to require at least an organizationname or surname. Previously, NULL entries for the collector or identifier incorrectly caused the creation of an empty party entry, hence the lower inserted row counts now that this is no longer created.
inputs/REMIB/Specimen/map.csv: Remapped acronym to institutionCode because this is an aggregator, and the field lists the datasource each record was aggregated from. Note that the inserted row count changes because of different duplicate elimination strategies in specimenreplicate and party (which institutionCode is placed in).
inputs/REMIB/Specimen/create.sql: Also filter out rows where acronym (collectionCode) is NULL because this is a required field for valid records
schemas/vegbien.sql: taxonpath: Renamed scientificnameauthor to author so the column name doesn't have "scientificname" in it, which made the term look confusingly like scientificname itself. Added descriptive comment that this is the author of the scientific name.
schemas/vegbien.sql: taxonpath: Renamed canon_id to canon_taxonpath_id to clarify that this is a recursive fkey. The convention is that a recursive fkey includes the table name plus a descriptive prefix.
schemas/filter_ERD.csv: Don't filter out fkeys from taxonpath to itself
schemas/vegbien.sql: taxonpath: Added canon_id for the canonical (scrubbed) taxonpath determined by TNRS
schemas/vegbien.sql: taxonpath: taxonpath_unique_within_datasource_by_name unique index: Added otherranks, so that ranks without a named column will be used in uniquely identifying the taxonpath
sql.py: DbConn.col_info(): Parse array types as sql_gen.ArrayType
sql_gen.py: EnsureNotNull: Support ArrayType types
strings.py: remove_prefix(), remove_suffix(): Added require param to raise aan exception if the string does not have the given prefix/suffix
sql.py: DbConn.col_info(): Moved parsing of user-defined datatypes to Python code, so that parsing for other composite types which also requires both data_type and udt_name can easily be added
sql_gen.py: Added ArrayType
schemas/vegbien.sql: Scope taxonpath instead of taxon with taxonscope, because a morphospecies name is specific to a datasource entity, so it should go in the datasource-specific taxonpath table instead of the datasource-general taxon table
schemas/vegbien.sql: taxonpath: Added otherranks array column to store ranked names without a named column. Documented that ranks with no named column should be stored in this new field instead of in a chain of taxons pointed to by taxon_id. This ensures that only the tree of life uses the taxon table.
schemas/vegbien.sql: Removed no longer used table stemtag, which has been replaced by stemobservation.tag, stemobservation.tags
inputs/ARIZ/Specimen/test.xml.ref: Updated after reinstalling staging table with new sql_io.null_strs
inputs/VegBank/: Added stemlocation/
inputs/VegBank/: Added stemcount/
sql_io.py: cleanup_table(): Fixed bug where couldn't run any update statement when no columns are text
csv2db: COPY FROM mode: Removed no longer needed explicit column list, now that the initial table has the exact width of the CSV (the row_num is added later)
csv2db: Add any row_num column after creating the table, so it does not interfere with row widths when using COPY FROM without explicit column names
csv2db: Fixed bug where tables without a row_num (such as *.src tables) were not properly supported when the CSV contained ragged rows, because the columns were truncated to # column names + 1 but there was no row_num to be the +1. This was solved by moving row_num to the end, so that it does not impact the column count whether it's there or not.
inputs/VegBank/: Added taxonimportance/
mappings/VegCore.csv: Added and mapped aggregateOccurrenceID
mappings/VegCore.csv: taxonOccurrenceID: Re-sourced to VegBank taxonobservation and DwC occurrenceID, because this is where the VegBIEN table name came from
tnrs_client: Support parsing multiple taxons at once, by specifying each as a command-line argument. Increased the max_pause to 10 min to support large batches. Limited the batch size to 5000 names, using the limit at <http://tnrs.iplantcollaborative.org/TNRSapp.html>. Note that when using xargs to pass many names, xargs will by default split its arguments into chunks of 5000. You can change this using the -n option.
Added tnrs_client. Note that obtaining an actual CSV requires four (!) steps: submit, retrieve, prepare download, and download. The output of the retrieve step is unusable because the array has different lengths depending on the taxonomic ranks present in the provided taxon name. This initial version runs one name at a time, but could later be expanded to batch process because TNRS can run multiple names at once.
streams.py: Line iteration: Added read_all()
inputs/Madidi/Plot/map.csv: Soil component measurements: Documented that units are assumed to be % based on the range of values
sql_io.py: null_strs: Added '-'
sql_io.py: cleanup_table(): Fixed bug where each column name needed to be converted to Unicode before being concatenated with other strings, to support non-ASCII characters
inputs/SALVIAS/plotMetadata/map.csv, inputs/SALVIAS-CSV/Plot/map.csv: Soil component measurements: Documented that units are assumed to be % based on the range of values
inputs/SALVIAS/plotMetadata/map.csv, inputs/SALVIAS-CSV/Plot/map.csv: Soil component measurements: Removed no longer needed old-style _units filter, now that unit conversion is handled by mappings/VegCore-VegBIEN.csv using _percent_to_fraction
inputs/VegBank/observation_/map.csv: soilObs fields: Cited data dictionary source of units
mappings/Veg+-VegCore.csv: Soil component measurements: Added unitless terms that automap to all alternatives of units
mappings/VegCore.csv: Added term with *_fraction units for every *_percent term
mappings/VegCore.csv: Soil component measurements: Added default units of percent (cmol_kg for cationExchangeCapacity). This involves translating the names everywhere and adding a _percent_to_fraction conversion in mappings/VegCore-VegBIEN.csv.
mappings/VegCore-VegBIEN.csv: Remapped verbatimLatitude/Longitude to locationcoords.verbatimlatitude/longitude because these fields now contain only non-decimal coordinates. This involves removing the _alt suffix on decimalLatitude/Longitude, which causes the VegBIEN.csvs to change.
inputs/*/*/map.csv: Remapped latitude/longitude to decimalLatitude/Longitude because these fields almost always have units of decimal degrees
inputs/SpeciesLink/Specimen/map.csv: Documented that dwc_geospatial_VerbatimLatitude/Longitude contain a mix of DMS and other verbatim coordinates
inputs/QMOR/Specimen/map.csv: Remapped verbatimLatitude/verbatimLongitude to latitude_DMS/longitude_DMS since these fields contain DMS values
inputs/Madidi/Plot/map.csv: Remapped Latitude/Longitude (DMS) to new latitude_DMS/longitude_DMS
mappings/VegCore-VegBIEN.csv: Mapped latitude_DMS, longitude_DMS
mappings/VegCore.csv: Added latitude_DMS, longitude_DMS
inputs/REMIB/Specimen/map.csv: Remapped lat_deg/long_deg to decimalLatitude/Longitude because these values are (integer) degrees suitable for decimalLatitude/Longitude. Note that the other DMS fields are not yet translated to decimal degrees.
mappings/Veg+-VegCore.csv: Remapped latitude/longitude to decimalLatitude/Longitude because these fields almost always have units of decimal degrees
mappings/VegCore-VegBIEN.csv: Added empty mappings for special values (OMIT, etc.), so that they don't show up in **/unmapped_terms.csv. Note that the VegBIEN.csvs only change because the "No join mapping" errors change to "No non-empty join mapping".
input.Makefile: Maps validation: %/unmapped_terms.csv, %/new_terms.csv: Don't automatically regenerate the aggregated unmapped_terms.csv, new_terms.csv because this almost doubles the remake time when a mappings/ prerequisite changes (41s -> 75s)
inputs/GBIF/Specimen/map.csv: Remapped VerbatimLatitude/Longitude to decimalLatitude/Longitude because DecimalLatitude/Longitude just contains VerbatimLatitude/Longitude cast to a low-resolution float, which created spurious repeating decimals
mappings/Makefile: .VegCore-VegBIEN.csv.last_cleanup: Generate VegCore-VegBIEN.unsourced_terms.csv whenever VegCore-VegBIEN.csv changes, to track VegCore terms that are mapped to VegBIEN but not documented in VegCore.csv. Note that this file is not svn:ignored, so it will show up with a ? when the user runs `svn st` if there are any unsourced terms.
mappings/Makefile: Changed catch-all `.%.last_cleanup: %` target to a specific target for VegCore-VegBIEN.csv, because it's the only file that uses this target
mappings/: Don't generate a for_review version of Veg+-VegCore.csv, because it is identical to the machine-readable Veg+-VegCore.csv (there are no output XPaths to simplify)
mappings/: Don't generate a for_review version of VegX-VegCore.csv, because it is identical to the machine-readable VegX-VegCore.csv (there are no output XPaths to simplify)
mappings/: Removed Veg+.unmapped_terms.csv because these terms are found in each datasource's new_terms.csv, which are updated regularly, while this file isn't, and which exist for every datasource, while this file only contained terms from a few datasources
inputs/ARIZ/Specimen/map.csv: Remapped VerbatimLatitude, VerbatimLongitude to UNUSED
Regenerated root unmapped_terms.csv, new_terms.csv
lib/mappings.Makefile: unmapped_terms.csv, new_terms.csv: Only remake if newer than existing %/unmapped_terms.csv, %/new_terms.csv which haven't been autoremoved. This avoids always remaking every unmapped_terms.csv, new_terms.csv whenever `make missing_mappings` is run. Note that these files will automatically be remade whenever their corresponding map.csv changes, so it is not necessary to actually remake %/unmapped_terms.csv, %/new_terms.csv; they are prerequisites only so that their modification time may be checked to determine whether unmapped_terms.csv, new_terms.csv needs to be remade.
input.Makefile: Maps validation: %/unmapped_terms.csv, %/new_terms.csv: Automatically regenerate aggregated unmapped_terms.csv, new_terms.csv when a subdir's corresponding file changes
inputs/: Regenerated aggregated unmapped_terms.csv, new_terms.csv
inputs/REMIB/: Moved nodes.make into Specimen.src/ so it's with the data it generates
inputs/TEAM/: Regenerated */new_terms.csv
inputs/TEAM/: Obtained new download of TEAM data. (Note that the new download has a slightly different schema.) Archived old data in _archive/. Added tables to import_order.txt. Renamed TeamPlotMetaData/ to TEAM_Sites/ to correspond with the section header in Vegetation-Tree-and-Liana-Metadata-1.5.pdf. Fixed TEAM_Sites mappings: Remapped CollectionDate to eventDate because it relates to the plot, not the organism. Mapped Name to plotName so TEAM_Sites data will match up with VL, VT data.
inputs/TEAM/VL, VT: Split concatenated flat files apart into separate parts each time a header is duplicated, so that the header would be autoremoved by cat_csv. Changed modified BIEN2 flat file headers back to original headers (the duplicated headers) so the headers of all part files would match up. (This is required for cat_csv header autoremoval to work properly.) This results in changes to the input column names in */map.csv.
sql_io.py: null_strs: Added 'nulo' (used by REMIB)
mappings/Veg+-VegCore.csv: DBH: Removed diameterBreastHeight_m alternative because datasources that don't append units to DBH almost always have units of cm or in
inputs/TEAM/*/map.csv: Remapped dbh from diameterBreastHeight_m to diameterBreastHeight_cm, using the units defined in Vegetation-Metadata-1.4.pdf
inputs/TEAM/: Added TeamPlotMetaData
inputs/TEAM/_src/: Added ci-team_extract/Vegetation-Metadata-1.4.pdf and symlink to it in the _src subdir
inputs/: Added aggregated unmapped_terms.csv, new_terms.csv which were not already under version control
inputs/SALVIAS-CSV/Organism/map.csv: Remapped stem_dbh from diameterBreastHeight_m to diameterBreastHeight_cm, assuming units based on the units for intercept_cm, which measures the same dimension
inputs/SALVIAS/stems/map.csv: Remapped stem_dbh from diameterBreastHeight_m to diameterBreastHeight_cm, assuming units based on the units for plotObservations.intercept_cm, which measures the same dimension
inputs/SALVIAS/plotObservations/map.csv: Remapped temp_dbh from diameterBreastHeight_m to diameterBreastHeight_cm, assuming units based on the units for intercept_cm, which measures the same dimension
inputs/Madidi/Organism/map.csv: Remapped Diameter from diameterBreastHeight_m to diameterBreastHeight_cm, assuming units based on the range and precision of values
inputs/FIA/Organism/map.csv: DBH: Changed units comment to include that assumption was also based on location inside the U.S., because some data outside the U.S. also uses fractional DBHs, but these are not likely to be inch measurements