Making research materials Findable, Accessible, Interoperable and Reusable

Abstract

To err is human. Yet, when it comes to creating research materials, mistakes can be reduced by sharing more of our work and by using some helpful tools. For instance, we can make our research materials FAIRer—that is, more Findable, Accessible, Interoperable and Reusable (Wilkinson et al., 2016)—. These practices facilitate the reproducibility, revision, modification and expansion of research materials, by the creators themselves and by other researchers, at any point in time, which is convenient due to the vital importance of methods in experimental research (Barsalou, 2019). In the current presentation, I will describe how documentation practices and open-source software (namely, R and OpenSesame) were used to prepare materials for an artificial language study that comprised several sessions and several grammatical properties (cf. Cross et al., 2021; González Alonso et al., 2020; Mitrofanova et al., 2023; Morgan-Short et al., 2012; Pereira Soares et al., 2022). The preparation of the stimuli in R drew on a modular framework formed of interoperable components (Snippet 1). This modularity will facilitate the expansion of the materials within the same languages or to other languages. Specifically, the minimal components of each language were contained in a base file in the ‘stimulus_preparation’ folder (Table 1). Furthermore, for the creation of the final stimuli, several controls were exerted to prevent spurious effects. For instance, gender and number were counterbalanced across experimental conditions, words were rotated across grammatical properties and sessions, and frequency of occurrence was controlled (Snippet 2). The final stimuli can be recreated using the script ‘compile_all_stimuli.R’, and the resulting stimuli are saved to the ‘session_materials’ folder. Furthermore, the final stimuli were presented using OpenSesame, which is a free-of-charge software supporting experiments in the social sciences. I will describe the implementation of several complex sessions in OpenSesame, which involved the use of conditions for controlling the engagement of certain items (Snippet 3). Last, I will describe a custom script in OpenSesame that enables the measurement of event-related potentials by time-locking electroencephalographic measures to the onset of specific stimuli (Snippet 4).

└── stimulus_preparation
    ├── Norway site, base stimuli.csv
    ├── Spain site, base stimuli.csv
    ├── base_images.R
    ├── R_functions
    │   ├── Session2_Pretraining_vocabulary.R
    │   ├── Session2_Training_gender_agreement.R
    │   ├── Session2_Test_gender_agreement.R
    │   ├── Session2_Experiment_gender_agreement.R
    ...
    ├── compile_all_stimuli.R

columns_to_check = c('noun1_gender', 'number', 'person', 
                     'verb', 'noun1', 'wrapup_noun')

for(i in seq_along(columns_to_check)) {
  column = columns_to_check[i]
  number_of_unique_frequencies = 
    combinations %>% 
    filter(complete.cases(get(column)), get(column) != '') %>% 
    group_by(get(column)) %>% tally() %>% select(n) %>% 
    n_distinct()
  if(number_of_unique_frequencies != 1) {
    warning(paste0('Some elements in the column `', column, 
                   '` appear more often than others.'))
  }
}

participant_parameters = 
  pd.read_csv(exp.get_file('../parameters per participant/' + 
              var.study_site + 
              ' site, parameters per participant.csv'))

var.resting_state_order = 
  participant_parameters.loc[
    participant_parameters['participant'] ==
    var.subject_nr]['Session2_resting_state_order'].iloc[0]

var.language = 
  participant_parameters.loc[participant_parameters['participant'] == 
                             var.subject_nr]['language'].iloc[0]

# Open the first serial port available
serialport = serial.Serial(serial.tools.list_ports.comports()[0].device)

# Send triggers to the port
def send_trigger(trigger):
    serialport.write(trigger.to_bytes(length = 1, byteorder = 'big'))
    # 10 ms separation from next trigger (see BrainVision Recorder manual)
    time.sleep(0.01) 
    # reset port
    serialport.write(int(0).to_bytes(length = 1, byteorder = 'big')) 
    return;