--- title: "Introduction to rspacer" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Introduction to rspacer} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- The goal of rspacer is to "wrap" the [RSpace API](https://community.researchspace.com/public/apiDocs), that is, allow you to use the API directly from R using convenience functions. **This package (and its documentation) is a work-in-progress. Contributions are welcome!** ## Setting up rspacer To use rspacer it needs to know two things: 1. The API URL for your RSpace instance (this is typically the URL of your RSpace instance followed by `api/v1`, e.g., `https://leiden.researchspace.com/api/v1`) 2. Your API key, which is an authentication token you can use instead of your username and password. To create an API key go to 'Manage API Key' section of your RSpace profile page (MyRSpace -> My Profile). **You should keep your API key private.** You can regenerate an API key at any time, which will invalidate the old key. You can use the `set_api_url()` and `set_api_key()` functions to make these available to rspacer in the current session. To make this information persistent you can store it in environment variables. An easy way to do this is with `usethis::edit_r_environ()`; in the file that opens, you should add the following lines (insert your own URL and key): ``` RSPACE_API_URL="https://leiden.researchspace.com/api/v1" RSPACE_API_KEY="" ``` After saving the file and restarting R, you should now be able to run ``` r library(rspacer) api_status() ``` ``` ## $message ## [1] "OK" ## ## $rspaceVersion ## [1] "1.109.2" ``` ## Functionality ### Folders Now you can use rspacer to interact with your RSpace Workspace. For example, `folder_tree()` will show you the content of your Workspace as a tibble: ``` r folder_tree() ``` ``` ## # A tibble: 10 × 9 ## id globalId name created lastModified parentFolderId type `_links` owner ## ## 1 356307 SD356307 Gerhard Burger 2024-01-17T14:5… 2024-01-17T… 7813 DOCU… ## 2 260004 FL260004 LACDR RDM 2023-11-06T10:1… 2023-11-06T… 7813 FOLD… ## 3 242175 FL242175 GABi001_EMP_regulation 2023-05-30T10:1… 2023-06-14T… 7813 FOLD… ## 4 242400 FL242400 Ontologies 2023-06-01T07:2… 2023-06-01T… 7813 FOLD… ## 5 242398 FL242398 Api Inbox 2023-06-01T07:2… 2023-06-01T… 7813 FOLD… ## 6 242182 FL242182 Publications 2023-05-30T11:0… 2023-05-30T… 7813 FOLD… ## 7 21961 FL21961 DDS2 Data management 2023-03-16T09:5… 2023-03-16T… 7813 FOLD… ## 8 7833 FL7833 Templates 2022-12-22T12:3… 2022-12-22T… 7813 FOLD… ## 9 7819 GF7819 Gallery 2022-12-22T12:3… 2022-12-22T… 7813 FOLD… ## 10 7814 FL7814 Shared 2022-12-22T12:3… 2022-12-22T… 7813 FOLD… ``` You can also specify an id or Unique ID (`globalId`) to show the contents of a specific folder: ``` r folder_tree(7819) ``` ``` ## # A tibble: 8 × 9 ## id globalId name created lastModified parentFolderId type `_links` owner ## ## 1 7828 GF7828 Snippets 2022-12-22T12:32:22.318Z 2022-12-22T12:… 7819 FOLD… ## 2 7827 GF7827 PdfDocuments 2022-12-22T12:32:22.315Z 2022-12-22T12:… 7819 FOLD… ## 3 7826 GF7826 Miscellaneous 2022-12-22T12:32:22.311Z 2022-12-22T12:… 7819 FOLD… ## 4 7825 GF7825 Documents 2022-12-22T12:32:22.308Z 2022-12-22T12:… 7819 FOLD… ## 5 7824 GF7824 Chemistry 2022-12-22T12:32:22.304Z 2022-12-22T12:… 7819 FOLD… ## 6 7823 GF7823 Videos 2022-12-22T12:32:22.301Z 2022-12-22T12:… 7819 FOLD… ## 7 7822 GF7822 Audios 2022-12-22T12:32:22.297Z 2022-12-22T12:… 7819 FOLD… ## 8 7820 GF7820 Images 2022-12-22T12:32:22.290Z 2022-12-22T12:… 7819 FOLD… ``` ### Documents #### Retrieve You can retrieve documents using ``` r res <- document_retrieve("SD356307") summary(res) ``` ``` ## Length Class Mode ## id 1 -none- numeric ## globalId 1 -none- character ## name 1 -none- character ## created 1 -none- character ## lastModified 1 -none- character ## parentFolderId 1 -none- numeric ## signed 1 -none- logical ## tags 0 -none- NULL ## tagMetaData 0 -none- NULL ## form 10 -none- list ## owner 10 -none- list ## fields 8 -none- list ## _links 1 -none- list ``` The result is json converted to an R list, to get the field information you could use ``` r library(tidyverse) tibble(fields = res$fields) |> unnest_wider(fields) |> select(name, type, content) ``` ``` ## # A tibble: 8 × 3 ## name type content ## ## 1 Template Used string "LACDR-ISA - Contact v0.2.0" ## 2 Name string "Gerhard A. Burger" ## 3 Email string "g.a.burger@lacdr.leidenuniv.nl" ## 4 Phone string "" ## 5 ORCID string "0000-0003-1062-5576" ## 6 Address text "

Gorlaeus … ## 7 Affiliation string "Leiden University" ## 8 Roles text "" ``` #### Create Creating (structured) documents is slightly more involved, see the Articles tab for more info.