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Data Cleaning and Standardization","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"\n# BIRDS \u003cimg src=\"https://github.com/GreenswayAB/BIRDS/raw/master/man/figures/logo.png\" align=\"right\" width=\"120\"/\u003e\n\n[![License: GPL\nv3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)\n[![Lifecycle:\nstable](https://img.shields.io/badge/lifecycle-stable-green.svg)](https://lifecycle.r-lib.org/articles/stages.html)\n[![CRAN\nStatus](https://www.r-pkg.org/badges/version/BIRDS)](https://cran.r-project.org/package=BIRDS)\n[![Downloads](https://cranlogs.r-pkg.org/badges/BIRDS?color=blue)](https://cranlogs.r-pkg.org/)\n[![R-CMD-check](https://github.com/GreenswayAB/BIRDS/workflows/R-CMD-check/badge.svg)](https://github.com/Greensway/BIRDS/actions)\n\n### A set of tools for Biodiversity Informatics in R\n\nThis is the Biodiversity Information Review and Decision Support package\nfor R!  \n**NB**: BIRDS is an acronym. This packages is not limited to birds' data\n(i.e. Aves) :smiley:\n\nThis set of tools has been developed for systematizing biodiversity data\nreview in order to evaluate whether a set of species observation are\nfit-for-use and help take decisions upon its use on further analysis.\n\nThis R-package was awarded the Third Prize on the [2019 GBIF Ebbe\nNielsen\nChallenge](https://www.gbif.org/en/news/2mixX9oDrJI2W3AqPFOxI3/wherenext-wins-2019-gbif-ebbe-nielsen-challenge#birds)\nfor which it was developed.\n\nThe set of tools provided are aimed to review and understand\nbiodiversity data quality in terms of completeness, and the data\ngeneration process (i.e. the observers' sampling behaviour). The `BIRDS`\npackage provides a systematic approach to evaluate biodiversity data –\nto enhance reproducibility and facilitate the review of data. The\n`BIRDS` package intends to provide the data user with knowledge about\nsampling effort (amount of effort expended during an event) and data\ncompleteness (data gaps) to help judge whether the data is\nrepresentative, valid and fit for the purpose of its intended use – and\nhence support for making decisions upon the use and further analysis of\nbiodiversity data.\n\nThe `BIRDS` package is most useful for heterogeneous data sets with\nvariation in the sampling process, i.e. where data have been collected\nand reported in variable ways, not conforming to the same sampling\nprotocol and therefore varying in sampling effort, leading to variation\nin data completeness (i.e. how well the reported observations describe\nthe \"true\" state). Primary biodiversity data (PBD) combining data from\ndifferent data sets, like e.g. GBIF mediated data, commonly vary in the\nways data has been generated - containing opportunistically collected\npresence-only data (no sampling protocol, no or inconsistent information\nabout absences, high sampling variability between observers), and data\nsets that have been collected using different sampling protocols. The\nset of tools provided by the `BIRDS` package is aimed at illuminating\nand understanding the process that generated the data (i.e. observing,\nrecording and reporting species into databases). It does this by a\nsystematic approach, and providing summaries that inform about sampling\neffort and data completeness (or data gaps).\n\nThe `BIRDS` package is **not** concerned with data accuracy, which can\nbe evaluated and improved using other existing packages (as outlined in\nthe [technical\ndetails](https://greenswayab.github.io/BIRDS/articles/technical_details.html)\nvignette), before processing the data using `BIRDS`.\n\nThe concepts and methods, and examples are described after a short\ndescription on how to install this package into R.\n\n### How to install `BIRDS`\n\nThis package is now published on CRAN. Therefore the easiest option to\ninstall it is `install.packages('BIRDS')`. Else, you can install the\ndevelopment version directly from GitHub using the package `remotes`.\nInstall `remotes` if you have not already installed it\n(`install.packages('remotes')`):\n\n``` r\nremotes::install_github('GreenswayAB/BIRDS')\nlibrary(BIRDS)\n```\n\n### Concepts and methods\n\n#### Systematic approach – a workflow for primary biodiversity data\n\nIn order to systematize and enhance reproducibility of the review\nprocess for PBD the `BIRDS` package takes a systematic approach. With\nthis package the date are systematically organised and reviewed. This\nsystematic approach actually starts before using `BIRDS` as we suggest\nsteps and tools for optionally cleaning the data before processing by\n`BIRDS`. Hence, before using biodiversity data for the intended analysis\nstart by optionally cleaning the data, then use `BIRDS` to organize,\nsummarize and review the data:\n\n\u003cimg src=\"https://github.com/GreenswayAB/BIRDS/raw/master/man/figures/BIRDs.png\"/\u003e\n\nThen, use your review to evaluate sampling effort and data gaps, and to\ninform decisions about whether the data are fit-for-purpose and how to\nfurther analyse the data.\n\n##### Field visit\n\nA central concept used by the `BIRDS` package is the \"visit\" – defining\nthe sampling unit as a sampling event by a unique observer (or group of\nobservers), at a unique unit of space and time (commonly a day). Visits\ncan help us to summarize the amount of effort expended in the field.\nDuring a visit, the observer commonly samples (i.e. observes and\nrecords) species by similar methods. The sampling effort can vary among\nvisits, with the amount of effort expended being greater when spending\nmore time, and reporting more of the observed species. The same number\nof observations (records of species) at a unique unit of time and space\ncould be made by either few observers reporting many species (greater\neffort by each observer) or many observers reporting few species (small\neffort by each observer). Using visits as sampling units allows\nseparation of sampling effort into the effort that can be expressed\nthrough the number of visits by different observers and the effort per\nvisit (e.g. species list length, or when available the time spent during\na visit). Hence, the quality (completeness) of the data can be judged by\nusing information for each visit and information from a collection of\nvisits.\n\nYou can examine this in the [technical\ndetails](https://greenswayab.github.io/BIRDS/articles/technical_details.html)\nvignette.\n\n##### Spatial grid and spillover\n\nDefined by a unique observer (or group of observers), at a unique unit\nof space and time visits can be identified by a unique combination of\nvariables: observer id, location, time. Often location is a named unit\nof space that has been visited during the same sampling event. For\nexample a botanist visiting and reporting species for a meadow, or a\nbird watcher visiting and reporting species for a lake.\n\nSometimes locations can be more accurate positions for individuals of\nspecies that have been observed and reported during the same field\nvisit. The botanist may have visited the meadow but reported species\nfrom a number of different sampling points in that meadow. Or the bird\nwatcher reported species for different parts of the lake. In that case\nthere is no common spatial identifier for the visit.\n\nIf there is no common spatial identifier to define the visit extent, and\nthe observer id is not enough to constrain observations spatially (e.g.\ngroup of observers from organisation where observer id = organisation\nname), then visits can be created *when* overlaying the observation data\nwith the spatial grid. A visit is then defined as all the observations\nfalling into the same grid cell. It is important to keep in mind to\nchoose a grid with a cell size that corresponds to (or at least is not\nsmaller than) the average spatial extent known (or assumed) to be\ntypical for field visits for the reference species group (see below).\nThis process can be repeated with a set of grids with different offset\nto explore the sensitivity of the results to the size of the grid cells.\n\nYou can examine this in the [technical\ndetails](https://greenswayab.github.io/BIRDS/articles/technical_details.html)\nvignette.\n\n##### Reference species group\n\nBecause visits result from the sampling process they can only be defined\nfor a reference species group, i.e. a group of species observed and\nrecorded by similar methods. The rationale for a reference species group\nis based on the assumption that species groups share similar bias: we\nassume that, despite varying field skills and accuracy, observers\nreporting observations for species of a reference species group share\nsimilar observer behavior and methods and, hence, generate data with\nsimilar sampling bias (Phillips et al. 2009). From this we can assume\nthat the larger the number of visits (or observations) reporting species\nfrom the reference group at a specific unit of space and time, the more\nlikely it is that the lack of visits for (or observations of) a\nparticular species reflects the absence of (or failure to detect) a\nfocal species rather than a lack of visits and reports made.\n\nIt is important to keep in mind that, to keep the sampling bias\nconsistent, the reference species group should only include species that\nare assumed to be sampled with the same methodology (Ponder et al.\n2001). For example, a reference group should not include all species in\nthe Order Lepidoptera because butterflies *sensu stricto* (superfamily\nPapilionoidea) are sampled in very different ways than most other\nspecies of Lepidoptera (mainly moths).\n\n##### Species list length (SLL)\n\nThe SLL per visit (i.e. the number of species observed and recorded per\nvisit) is a well known proxy for the time spent in the field and\nwillingness to report all species seen of a reference taxonomic group,\nSzabo et al. 2010). The `BIRDS` package therefore uses SLL as a proxy\nfor sampling effort.\n\n### What does the package do?\n\nWith the `BIRDS`' package set of tools PBD can be reviewed based on the\ninformation contained in the visits. Use `BIRDS` to organize the data,\nsummarize and review the data as shown above. The `BIRDS` package\norganizes the data into a spatially gridded visit-based format, from\nwhich summaries are retrieved for a number of variables describing the\nvisits across both spatial and temporal dimension. Those variables are\nthe number of visits, number of species, number of observations, average\nspecies list length per visit, number of units of space and time with\nvisits. The variables can be used to collectively describe the sampling\neffort and data completeness (data gaps), and can be examined spatially\n(e.g. viewed on maps) and temporally (e.g. plotted as time series).\n\n#### What does the package help us with?\n\nUsing the detailed information on sampling effort and data completeness\nprovided by the `BIRDS`' package summaries allows better inference on\nwhat the reported species observations mean. As a much of the PBD is\npresence-only data the provided information helps us judging to what\ndegree a lack of observations may be (1) due to the species not being\nobserved (absent, or failed to detect) or (2) due to a lack of reports\n(lack of visits, or lack of reports for observed species) (little\nsampling effort). We can be more confident about the first when there is\ngood sampling effort and data completeness, while evidence is shaky,\ni.e. high probability to have missed species, when there is little\nsampling effort and data completeness. In this way the user can judge\nwhether the data is fit-for-purpose for the intended use. Using this\ninformation about how the data has been collected the user can also\ndecide about how to analyse the data.\n\nIt helps you getting :world_map: :bar_chart: :chart_with_upwards_trend:\n:chart_with_downwards_trend: :page_facing_up: :bulb: about\n\n:dog2: :cat2: :pig2: :mouse2: :sheep: :cow2: :rat: :rabbit2: :goat:\n:baby_chick: :rooster: :wolf: :frog: :koala: :bear: :boar: :monkey:\n:camel: :elephant: :panda_face: :snake: :bird: :penguin: :turtle: :bug:\n:honeybee: :ant: :lady_beetle: :snail: :octopus: :tropical_fish:\n:blowfish: :fish: :shell: :whale: :dolphin: :water_buffalo: :tiger2:\n:leopard: :ox: :crocodile: :dromedary_camel:\n\nand\n\n:bouquet: :cherry_blossom: :tulip: :four_leaf_clover: :rose: :sunflower:\n:hibiscus: :maple_leaf: :leaves: :fallen_leaf: :herb: :mushroom:\n:cactus: :palm_tree: :evergreen_tree: :deciduous_tree: :chestnut:\n:seedling: :blossom: :ear_of_rice:\n\nbut, maybe not :dragon_face: :dragon: :christmas_tree:\n\n##### References:\n\nPhillips et al. 2009 Sample selection bias and presence‐only\ndistribution models: implications for background and pseudo‐absence\ndata, Ecol Appl 19:181-197.  \nPonder et al. 2001 Evaluation of Museum Collection Data for Use in\nBiodiversity Assessment, Cons Biol 15:648-657.  \nSzabo et al. 2010 Regional avian species declines estimated from\nvolunteer‐collected long‐term data using List Length Analysis, Ecol Appl\n20:2157-2169.\n\n### Overview of main components\n\nYou can find an overview of the `BIRDS` main components and functions,\norganised as an [overview workflow\nhere](https://github.com/GreenswayAB/BIRDS/raw/master/man/figures/BIRDs.png)\nand a [workflow highlighting the decisions to be taking when using BIRDS\nhere](https://github.com/GreenswayAB/BIRDS/raw/master/man/figures/BIRDsDecision.png).\n\n### Example\n\nThe [Intro to\nBIRDS](https://greenswayab.github.io/BIRDS/articles/BIRDS.html) vignette\nprovides a useful walk through the package tools using an example data\nset.\n\nA short introductory [video can be found\nhere](https://www.dropbox.com/s/fxg1t9vl4ainipy/BirdsLR.mp4?dl=0).\n\n### What is new - latest changes and additions\n\nWe continuously update and improve the BIRDS package. Check the\n[changelog](https://greenswayab.github.io/BIRDS/news/index.html)\n\n### In the TODO LIST\n\nCheck [here](https://github.com/GreenswayAB/BIRDS/projects/4) for a list\nof future features to be added, and don't hesitate sending your\nsuggestions by [e-mail](mailto:alejandro@greensway.se)\n\n### Acknowledgements\n\nThe development of the BIRDS package is part of a project 'Using\nopportunistic citizen science data for evaluations of environmental\nchange' financed by the Swedish Research Council Formas.\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["ala4r","data-quality-assertions","nbn"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/64163","html_url":"https://ost.ecosyste.ms/projects/64163"}