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plotsdatabase 1.5
Breaking Changes
query_plots() Output is automatically structured based on inventory method using the new output styles system
Different styles organize data into separate tables: metadata, individuals, censuses, height-diameter, etc.
Action required : To preserve old behavior (flat data frame), use output_style = "full"
Rationale: Structured output makes it easier to work with complex plot data without overwhelming column counts
See documentation for ?query_plots
New Features
Configurable output styles system for query_plots()
6 predefined output styles: minimal, standard, permanent_plot, permanent_plot_multi_census, transect, full
Auto-detection of appropriate style based on method field (e.g., “1 ha plot” → permanent_plot)
Manual style selection via output_style parameter
Each style returns a structured list with relevant tables (e.g., $metadata, $individuals, $censuses)
Column renaming from database names to user-friendly names (e.g., ddlat → latitude, tax_sp_level → species)
New configuration files: R/output_styles_config.R, R/output_styles_helpers.R
Specialized output tables for permanent plots
$censuses table: plot_name, census_number, census_date, team_leader, principal_investigator
$height_diameter table: Paired height-diameter measurements (id_n, D, H, POM) with issue filtering
Handles multiple censuses with automatic pivoting from wide to long format
Census-specific column renaming (e.g., stem_diameter_census_1 → dbh_census_1)
Custom print method for query results
New S3 class plot_query_list with informative print method
Shows table dimensions, column names, and geometry type for sf objects
Makes it easy to understand query result structure
Preservation of spatial data
coordinates_sf table automatically included when show_all_coordinates = TRUE
Print method detects and displays sf geometry information
Code Refactoring
Modular output style configuration
Centralized style definitions in .plot_output_styles list
Method-to-style mapping in .method_to_style_map
Style auto-detection function .detect_style_from_method()
Easy to add new output styles by extending configuration
Improved metadata extraction
Uses res_meta_data table (created before individual extraction) for metadata source
Ensures all plot-level columns available even when extract_individuals = TRUE
Consistent variable naming and error handling
Bug Fixes
Fixed commented @export tag causing roxygen2 errors
Removed @export from commented-out subplot_list() R/subsplots_features_function.R
Prevents documentation build failures
plotsdatabase 1.4 (development version)
New Features
Traits enrichment module in taxonomic matching Shiny app
New tab “Enrich with Traits” allows enriching matched taxonomic names with trait data from the taxa database
Aggregates multiple input names that match to the same taxon into a single row
Concatenates all input names (e.g., “cola edulis | coula edrulis” → “Coula edulis”)
Configurable options for categorical trait aggregation (mode vs concatenation)
User can select which columns to include (original names, corrected names, IDs, metadata)
Downloads enriched data as Excel file
Filters out id_trait_measures columns for cleaner output
Module: mod_traits_enrichment_ui() mod_traits_enrichment_server()
Enhanced file upload in taxonomic matching Shiny app
CSV file support added (in addition to Excel .xlsx and .xls)
Excel sheet selector allows choosing which sheet to import from multi-sheet workbooks
Sheet selector appears dynamically after Excel file upload
Default sheet selection is the first sheet
CSV files are loaded directly without sheet selection
Bug Fixes
Fixed NA input names appearing in trait enrichment
Enrichment module now filters out rows where the input taxonomic name is NA or empty
Prevents invalid NA entries from being matched to taxa or included in enriched output
Applied in both trait fetching and result aggregation steps
Fixed incorrect input names in enrichment output
Enrichment now correctly uses the user-selected taxonomic name column (not first column of dataset)
column_name parameter now passed from main app to enrichment module
Ensures input_names column shows actual taxonomic names from the selected column
Code Refactoring
Optimized taxonomic name cleaning for faster matching
Name cleaning (removing “sp.”, “cf.”, “aff.”, etc.) now happens before batch exact matching
Previously, cleaning only occurred during slow fuzzy matching phase
Names like “Coula edulis sp.” now match exactly to “Coula edulis” in fast batch step
Significantly reduces number of names sent to slower fuzzy matching
Cleaning happens once at beginning, benefiting all matching steps (species, genus, family)
Both original and cleaned names preserved in matching pipeline
Added underscore replacement in clean_taxonomic_name()
Breaking Changes
query_taxa() exact_match parameter now defaults to TRUE (was FALSE)
Exact matching is now the default for family/genus/order queries to prevent unexpected fuzzy matching results
For species queries, if exact match fails, the function automatically falls back to intelligent fuzzy matching
Action required : Code relying on fuzzy matching by default should explicitly set exact_match = FALSE
Rationale: Higher taxonomic ranks are standardized names where fuzzy matching rarely helps and can introduce errors
New Features
Intelligent taxonomic name matching with genus-constrained fuzzy search
Auto fuzzy fallback for species queries
query_taxa()
Transparent user feedback shows match quality (similarity score)
Handles typos and spelling variations automatically
Only applies to species queries; family/genus/order use exact matching only
Database enhancement: tax_level field added to table_taxa
New column explicitly indicates taxonomic level: “species”, “genus”, “family”, “order”, “infraspecific”, “higher”
Indexed for query performance
Eliminates ambiguity between missing data and genus/family-level taxa
Script provided: add_tax_level_field.R for database migration
All query functions updated to use new field for cleaner, more reliable filtering
Code Refactoring
Complete rewrite of query_taxa() to use new intelligent matching functions
Eliminated redundancy with helpers.R functions
8 new modular helper functions replace complex inline logic
Cleaner separation of concerns: matching, filtering, synonym resolution, formatting, trait addition
~160 lines of code removed through better abstraction
Better maintainability and extensibility
Deprecated query_fuzzy_match() and query_exact_match() in favor of match_taxonomic_names()
Simplified taxonomic level filtering using tax_level field
Replaced complex multi-column checks (e.g., is.na(tax_esp) & is.na(tax_gen)) with simple tax_level == "family"
Applied in query_taxa()
Bug Fixes
Fixed query_taxa() only_family = TRUE
Previously, fuzzy matching by default caused empty results when filtering for family-level taxa
Now uses exact matching by default for higher taxonomic ranks
Dependencies
Added new package dependencies to DESCRIPTION:
cli - User-friendly command line interfaces (moved from Suggests to Imports)
lifecycle - Manage function lifecycle (deprecation warnings)
data.table - High-performance data manipulation
glue - String interpolation for SQL queries
RecordLinkage - String similarity calculations
plotsdatabase 1.0
Breaking Changes
Database schema change : Renamed column ind_num_sous_plot to tag in data_individuals and followup_updates_individuals tables
All R package functions updated to use new column name
Action required : External scripts accessing ind_num_sous_plot must be updated to use tag
Updated files: R/functions_manip_db.R, R/individual_features_function.R, R/functions_divid_plot.R, R/generate_plot_summary.Rmd, structure.yml
Default parameter in approximate_isolated_xy() tag = "ind_num_sous_plot" to tag = "tag"
New Features
Initial release of package structure with comprehensive database query functions
Enhanced update_ident_specimens() : Now shows summary of linked individuals before updating specimen identification
Displays which plots and how many individuals will inherit the new identification
Shows current taxonomic identification of linked individuals
Provides better context for informed decision-making before confirmation
New helper function .get_linked_individuals_summary()
Bug Fixes
Connection error with complex home paths : Fixed create_db_config() C:/Users/NOBUS CAPITAL/OneDrive/Documents/)
Added proper error handling with tryCatch()
Creates parent directories if they don’t exist
Falls back to in-memory configuration if file cannot be written
Users now get informative warnings instead of connection failures
Documentation
Added comprehensive README.md with package overview, quick start guide, and function reference
README includes prominent link to NEWS.md for tracking updates
Infrastructure
Added NEWS.md to track package changes and updates
Established git branching workflow for all code modifications
Code Refactoring
Major refactoring : Reorganized R/functions_manip_db.R (previously 10,528 lines) into modular, domain-specific files
Created R/growth_census_functions.R (556 lines) - Growth computation and census analysis functions
Created R/specimen_linking_functions.R (406 lines) - Herbarium specimen linking and querying functions
Created R/taxonomic_query_functions.R (944 lines) - Taxonomic query functions with synonym resolution
Created R/taxonomic_update_functions.R (838 lines) - Taxonomic data update and entry functions
Expanded R/connections_db.R with database query utilities (func_try_fetch, try_open_postgres_table)
Removed ~6,800 lines from R/functions_manip_db.R through extraction to specialized modules
All functions verified as moved (not duplicated) to new locations
Improved code maintainability and discoverability