Databrary is a powerful tool for storing and sharing video data and
documentation with other researchers. With the databraryr
package, it becomes even more powerful. Rather than interact with
Databrary through a web browser, users can write their own code to
download participant data or even specific files.
I wrote databraryr so that I could better understand how
the site works under the hood, and so that I could streamline my own
analysis and data sharing workflows.
Let’s get started.
Registering
Access to most of the material on Databrary requires prior registration and authorization from an institution. The authorization process requires formal agreement by an institution. But you’ll create an account ID (email) and secure password when you register. Then, when you log in with your new credentials, you’ll select an existing institution (if yours is on the list), a new institution (if yours isn’t), or an existing authorized investigator (if you are a student, postdoc, or collaborator) to request authorization from.
Installation
Development release
- Install the devtools package from CRAN:
install.packages("devtools")if you have not already done so. - Load
devtoolsinto your local environment:library(devtools). - Install the databraryr package via
install_github("databrary/databraryr"). Required dependencies will be installed at this time.
First steps (while you await authorization)
But even before formal authorization is complete, a user can access the public materials on Databrary. For this vignette, we’ll assume you fall into this category.
Once you’ve installed the package following one of the above routes, it’s a good idea to check that your installation worked by loading it into your local workspace.
Then, try this command to pull data about one of Databrary’s founders:
# The default parameter settings return a very detailed set of information about
# a party that we do not need for this example.
party_6 <- databraryr::get_party_by_id(parents_children_access = FALSE)
party_6 |>
as.data.frame()
#> id sortname prename orcid affiliation
#> 1 6 Gilmore Rick O. 0000-0002-7676-3982 The Pennsylvania State University
#> url
#> 1 http://gilmore-lab.github.ioNote that this command returns a data frame with columns that include
the first name (prename), last name
(sortname), affiliation, lab or personal website, and ORCID
ID if available.
Databrary assigns a unique integer for each person and institution on the system called a ‘party id’. We can create a simple helper function to collect information about a larger group of people.
# Helper function
get_party_as_df <- function(party_id) {
this_party <- databraryr::get_party_by_id(party_id,
parents_children_access = FALSE)
if (!is.null(this_party)) {
as.data.frame(this_party)
} else {
NULL
}
}
# Party's 5, 6, and 7 are Databrary's founders
purrr::map(5:7, get_party_as_df, .progress = TRUE) |>
purrr::list_rbind()
#> id sortname prename affiliation
#> 1 5 Adolph Karen New York University
#> 2 6 Gilmore Rick O. The Pennsylvania State University
#> 3 7 Millman David New York University
#> url orcid
#> 1 http://www.psych.nyu.edu/adolph/ <NA>
#> 2 http://gilmore-lab.github.io 0000-0002-7676-3982
#> 3 <NA> <NA>You should see information about Databrary’s three founders.
You can also try seeing what’s new on Databrary. The
get_db_stats() command gives you information about the
newly authorized people, institutions, and newly uploaded datasets. Try
this:
databraryr::get_db_stats("stats")
#> # A tibble: 1 × 9
#> date investigators affiliates institutions datasets_total
#> <dttm> <int> <int> <int> <int>
#> 1 2024-09-18 12:26:19 1805 622 807 1754
#> # ℹ 4 more variables: datasets_shared <int>, n_files <int>, hours <dbl>,
#> # TB <dbl>
databraryr::get_db_stats("people")
#> # A tibble: 4 × 5
#> id sortname prename affiliation time
#> <int> <chr> <chr> <chr> <chr>
#> 1 10687 Addyman Caspar Stellenbosch University 2024-09-16T15:32:55.…
#> 2 22783 Mielke Alexander Queen Mary University of London 2024-09-16T14:13:57.…
#> 3 22864 Hojeij Zeina Zayed University 2024-09-13T12:14:27.…
#> 4 22658 Fusi Stefano Columbia University 2024-09-12T17:53:58.…
databraryr::get_db_stats("institutions")
#> # A tibble: 3 × 5
#> id sortname url institution time
#> <int> <chr> <chr> <lgl> <chr>
#> 1 22916 Stellenbosch University http://www.sun.ac.… TRUE 2024…
#> 2 22908 Zayed University https://www.zu.ac.… TRUE 2024…
#> 3 22880 University of Texas at San Antonio https://www.utsa.e… TRUE 2024…
databraryr::get_db_stats("datasets")
#> # A tibble: 9 × 8
#> id name body creation owners permission publicsharefull time
#> <int> <chr> <chr> <chr> <list> <int> <lgl> <chr>
#> 1 1800 DBN - Nort… "Thi… 2024-09… <named list> 1 FALSE 2024…
#> 2 1800 DBN - Nort… "Thi… 2024-09… <named list> 1 FALSE 2024…
#> 3 1800 DBN - Nort… "Thi… 2024-09… <named list> 1 FALSE 2024…
#> 4 1799 Test "Aud… 2024-09… <named list> 1 FALSE 2024…
#> 5 1798 IDCxContex… "The… 2024-09… <named list> 1 FALSE 2024…
#> 6 1797 DBN - Isra… "Thi… 2024-09… <named list> 1 FALSE 2024…
#> 7 1797 DBN - Isra… "Thi… 2024-09… <named list> 1 FALSE 2024…
#> 8 1797 DBN - Isra… "Thi… 2024-09… <named list> 1 FALSE 2024…
#> 9 1796 Global BAB… "Hom… 2024-09… <named list> 1 FALSE 2024…Depending on when you run this command and how often, there may or may not be new items.
Next steps
To see more about how to access data on Databrary using
databraryr visit the accessing
data vignette.
To see how to log in and log out once you have authorization, see the vignette for authorized users.