Data is from the website of the Open Repair Alliance. The structure of the data follows the technical documentation of the Open Repair Data Standard (ORDS Version 0.21).
Besides the complete dataset repairs with 48,669 entries, I have also added four compiled datasets on batteries, mobiles, printers, and tablets with additional information about fault types.
Aims of repairData
The goal of the repairData package is
- to create a joint approach to documenting successes and challenges with post-warranty repairs
- to promote it as a standard available to other community repair networks and in the future to commercial repairers and others collecting repair data
- to enable coalition members and others to use the data from our joint work to produce insights, intending to demand more repairable products, improved support, and access to better repair services
- to explore jointly additional information we can all collect to help make a stronger case for increased repairability. (Slightly changed from Open Repair Data Standard.)
Eventually, these datasets should help to extend the reach to commercial repairers and others collecting repair data. This data will be used to tell stories about the positive impacts of repair and to inform advocacy. Together, we can make a stronger case for more easily repairable devices.
Installation
You can install the released version of repairData from CRAN with:
install.packages("repairData")And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("petzi53/repairData")Example
After loaded the package you have access to all datasets with the data() function.
library(repairData)
# simple example code
data(repairs)
# or all together
data(repairs, batteries, printers, mobiles, tablets)Data specifications
The following table stems from the documentation of the Open Repair Data Standard (ORDS Version 0.21). (In the last column, I report my changes to the variable type of some columns according to the ORDS Type description.)
| Title | Field name | Type | R Data Type |
|---|---|---|---|
| ID | id | Unique identifier from the partner organisation. Does not have to be unique across all partner data. | character |
| Partner category | partner_product_category | Option from partner codelist. | character |
| Product category | product_category | Option from ORDS product category codelist. | factor |
| Brand | brand | Free text. | character |
| Year of manufacture | year_of_manufacture | Year. YYYY. | character* |
| Problem | problem | Free text. Personal data should be removed, e.g. email addresses. | character |
| Repair status | repair_status | Option from ORDS repair status codelist. | factor |
| Repair barrier | repair_barrier_if_end_of_life | Option from ORDS repair barrier codelist. Optional. Only relevant where repair_status = “End of life”. | factor |
| Group identifier | group_identifier | String. Unique. A unique identifier across all partners that can identify the group responsible for the repair. | factor |
| Event date | event_date | Date. YYYY-MM-DD format. The date of the repair event that the repair took place at. | Date |
| Data provider | data_provider | Option from ORDS codelist. Name of partner organisation. | factor |
| Country | country | String. 3 letter ISO code, e.g. “GBR”. | factor |
| Record date | record_date | Date. YYYY-MM-DD format. The date that the record was last updated. | Date |
- Because of many NA’s written as “????” I chose to import this column as “character”.
