# ClimMobTools: API Client for the ‘ClimMob’ platform in R

#### Kauê de Sousa

## Overview

ClimMobTools is the API client for the ‘ClimMob’ platform in R. ClimMob is open-source software for decentralized large-N trials using the ‘tricot’ approach1,2. This approach facilitates the rapid assessment of technologies in target environments. Tricot turns the research paradigm on its head: instead of a few researchers designing complicated trials to compare several technologies in search of the best solutions, it enables many participants to carry out reasonably simple experiments that, taken together, can offer even more information.

## Usage

The `breadwheat` dataset is a data.frame from crowdsourced citizen science trials of bread wheat (Triticum aestivum L.) varieties in India. This sample data is available on the ClimMob platform and can be fetched using the `getDataCM()` function from ClimMobTools, along with an API key from the ClimMob user’s account.

    library("ClimMobTools")
    library("PlackettLuce")

    # the API key
    key = "d39a3c66-5822-4930-a9d4-50e7da041e77"

    dat = getDataCM(key = key,
                     project = "breadwheat",
                     userowner = "gosset")

    names(dat) = gsub("firstassessment_|package_|lastassessment_|registration_", "",
                       names(dat))

# Tricot data into rankings

The Plackett-Luce model is one approach to analyze the ClimMob data3. We coerce the farmers’ rankings into an object of class `rankings` from the package PlackettLuce using the function `rankTricot()`.

    R = rankTricot(dat,
                    items = c("item_A","item_B","item_C"),
                    input = c("overallperf_pos","overallperf_neg"))

    mod = PlackettLuce(R)

    summary(mod)

    ## Call: PlackettLuce(rankings = R)
    ##
    ## Coefficients:
    ##           Estimate Std. Error z value Pr(>|z|)
    ## CSW18       0.0000         NA      NA       NA
    ## WR544      -2.7875     0.3098  -8.999  < 2e-16 ***
    ## PBW343     -0.2207     0.3111  -0.709 0.478083
    ## HP1633     -2.8714     0.3103  -9.254  < 2e-16 ***
    ## HW2045     -2.8517     0.3112  -9.163  < 2e-16 ***
    ## DBW17      -1.1265     0.2987  -3.771 0.000162 ***
    ## HD2985     -1.6546     0.3059  -5.409 6.32e-08 ***
    ## DPW621-50  -1.8793     0.3096  -6.070 1.28e-09 ***
    ## HD2824     -2.8177     0.3152  -8.939  < 2e-16 ***
    ## RAJ4120    -2.7451     0.3161  -8.683  < 2e-16 ***
    ## PBW550     -2.7204     0.3075  -8.847  < 2e-16 ***
    ## K0307      -2.9835     0.3122  -9.558  < 2e-16 ***
    ## HI1563     -2.9342     0.3126  -9.386  < 2e-16 ***
    ## PBW502     -2.5704     0.3088  -8.325  < 2e-16 ***
    ## HD2932     -2.1726     0.3060  -7.099 1.26e-12 ***
    ## K9107       0.6579     0.3528   1.864 0.062260 .
    ## ---
    ## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
    ##
    ## Residual deviance:  1339.1 on 1464 degrees of freedom
    ## AIC:  1369.1
    ## Number of iterations: 20

For more analytical insights, please visit the documentation of the gosset package.

# References

1.
van Etten, J., Beza, E., Calderer, L., Van Duijvendijk, K., et al. First experiences with a novel farmer citizen science approach: crowdsourcing participatory variety selection through on-farm triadic comparisons of technologies (tricot). Experimental Agriculture 55, 275–296 (2019).
2.
de Sousa, K., van Etten, J., Manners, R., Abidin, E., et al. The tricot approach: An agile framework for decentralized on-farm testing supported by citizen science. A retrospective. Agronomy for Sustainable Development 44, (2024).
3.
Turner, H. L., Etten, J. van, Firth, D. & Kosmidis, I. Modelling rankings in R: the PlackettLuce package. Computational Statistics (2020). doi:10.1007/s00180-020-00959-3