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.
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.
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 Databrary’s founders:
databraryr::list_people()
#> Downloading: 120 B Downloading: 120 B Downloading: 120 B Downloading: 120 B Downloading: 170 B Downloading: 170 B Downloading: 170 B Downloading: 170 B Downloading: 83 B Downloading: 83 B Downloading: 83 B Downloading: 83 B
#> 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>
Note that this command returns a data frame (tibble) 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’. When we run
list_people(1:25) we are asking the system to provide us
information about all of the people whose party id’s are
between 1 and 25. Let’s try it:
databraryr::list_people(people_list = 1:25)
#> Downloading: 75 B Downloading: 75 B Downloading: 75 B Downloading: 75 B Downloading: 72 B Downloading: 72 B Downloading: 72 B Downloading: 72 B Downloading: 72 B Downloading: 72 B Downloading: 72 B Downloading: 72 B Downloading: 120 B Downloading: 120 B Downloading: 120 B Downloading: 120 B Downloading: 170 B Downloading: 170 B Downloading: 170 B Downloading: 170 B Downloading: 83 B Downloading: 83 B Downloading: 83 B Downloading: 83 B Downloading: 94 B Downloading: 94 B Downloading: 94 B Downloading: 94 B
#> People info: ■■■■■■■■■■■■■■ 44% | ETA: 1s
#> Downloading: 72 B Downloading: 72 B Downloading: 72 B Downloading: 72 B Downloading: 130 B Downloading: 130 B Downloading: 130 B Downloading: 130 B Downloading: 81 B Downloading: 81 B Downloading: 81 B Downloading: 81 B Downloading: 57 B Downloading: 57 B Downloading: 57 B Downloading: 57 B Downloading: 42 B Downloading: 42 B Downloading: 42 B Downloading: 42 B Downloading: 44 B Downloading: 44 B Downloading: 44 B Downloading: 44 B Downloading: 100 B Downloading: 100 B Downloading: 100 B Downloading: 100 B Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 66 B Downloading: 66 B Downloading: 66 B Downloading: 66 B Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB Downloading: 3.7 kB
#> id sortname prename orcid
#> 1 1 Simon Dylan 0000-0002-2793-1679
#> 2 3 Steiger Lisa <NA>
#> 3 4 Byrne Andrea <NA>
#> 4 5 Adolph Karen <NA>
#> 5 6 Gilmore Rick O. 0000-0002-7676-3982
#> 6 7 Millman David <NA>
#> 7 11 Tamis-LeMonda Catherine <NA>
#> 8 13 Roy Lina Wictoren <NA>
#> 9 14 Franchak John <NA>
#> 10 16 Professor Suzanne Q. <NA>
#> 11 17 Jimenez-Robbins Carmen <NA>
#> 12 18 Coe Jon <NA>
#> 13 19 Foo Vicky <NA>
#> 14 20 Gordon Peter <NA>
#> 15 24 Chan Gladys <NA>
#> affiliation url
#> 1 <NA> <NA>
#> 2 Databrary <NA>
#> 3 Databrary <NA>
#> 4 New York University http://www.psych.nyu.edu/adolph/
#> 5 The Pennsylvania State University http://gilmore-lab.github.io
#> 6 New York University <NA>
#> 7 New York University <NA>
#> 8 NYU <NA>
#> 9 University of California, Riverside http://padlab.ucr.edu
#> 10 Databrary <NA>
#> 11 <NA> <NA>
#> 12 <NA> <NA>
#> 13 <NA> <NA>
#> 14 Teachers College, Columbia University <NA>
#> 15 NYU <NA>
It’s a bit slow, but you should see information about people
beginning with Dylan Simon, the developer who designed and built most of
the Databrary system, and ending with Gladys Chan, a graphic designer
who created the Databrary and Datavyu logos and other graphic identity
elements.
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 2024-04-18 08:29:19 1746 680 785 1682
#> # ℹ 4 more variables: datasets_shared <int>, n_files <int>, hours <dbl>,
#> # TB <dbl>
databraryr::get_db_stats("people")
#> # A tibble: 6 × 5
#> id sortname prename affiliation time
#> <int> <chr> <chr> <chr> <chr>
#> 1 12379 Looman Wendy University of Minnesota 2024…
#> 2 12070 Jones Stephanie Harvard University, Graduate School of … 2024…
#> 3 10313 Wang Tien-Ni National Taiwan University 2024…
#> 4 5908 Doebel Sabine George Mason University 2024…
#> 5 4778 Tummolini Luca National Research Council of Italy 2024…
#> 6 12403 Fausto-Sterling Anne Brown University 2024…
databraryr::get_db_stats("institutions")
#> # A tibble: 1 × 5
#> id sortname url institution time
#> <int> <chr> <chr> <lgl> <chr>
#> 1 12546 Vilnius University https://www.vu.lt/en/ TRUE 2024-04-03T17:51:5…
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 1727 DBN - Repu… "“Th… 2024-04… <named list> 1 FALSE 2024…
#> 2 1727 DBN - Repu… "“Th… 2024-04… <named list> 1 FALSE 2024…
#> 3 1727 DBN - Repu… "“Th… 2024-04… <named list> 1 FALSE 2024…
#> 4 1726 2024 Mindf… "Imp… 2024-04… <named list> 1 FALSE 2024…
#> 5 1722 How does s… "The… 2024-04… <named list> 1 TRUE 2024…
#> 6 1722 How does s… "The… 2024-04… <named list> 1 TRUE 2024…
#> 7 1721 Adjectives "Con… 2024-04… <named list> 1 FALSE 2024…
#> 8 1721 Adjectives "Con… 2024-04… <named list> 1 FALSE 2024…
#> 9 1721 Adjectives "Con… 2024-04… <named list> 1 FALSE 2024…
Depending on when you run this command and how often, there may or
may not be new items.