The Podcast Index is an independent and open catalog of podcasts feeds serving as the backbone of what is referred to as the Podcasting 2.0 initiative. The data contained in the Podcast Index is available through a robust REST API as well as a SQLite database updated every week.
The PodcastIndex Dashboard is my attempt to give back to the amazing Podcasting 2.0 initiative. A key concept that drives the engagement and enthusiasm in this community is the unique ways each of us can contribute time, talent, and treasure to benefit everyone.
In previous episodes of Podcasting 2.0, Dave Jones lamented that duplicate podcast entries in the Podcast Index can cause annoying issues for many podcast apps and other services relying on the integrity of the index. Seeing an opportunity to help this amazing project, I sent a boost to the show in episode 156 to offer up a new solution powered by the R statistical computing language for identifiying potential duplicates alongside other data quality issues. Hence the objectives of this dashboard are to highlight potential duplicate podcast entries as well as perform quality assessments of the index to highlight potential issues.
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Much like the ethos behind podcasting 2.0, the PodcastIndex Dashboard is proudly built on the foundations of open-source:
- Quarto technical publishing system with the new capability of dashboards.
- The R project for statistical computing with the following amazing packages:
{reclin2}: Record linkage toolkit for R.{pointblank}: Data quality assessment and metadata reporting for data frames and database tables.{reactable}: Interactive data tables for R, based on the React Table and made with{reactR}.{reactablefmtr}: Streamlined table styling and formatting for{reactable}tables.{dplyr}: A grammar of data manipulation
The duplicate records and data quality analysis pipelines are executed weekly (after the Podcast Index SQLite database is refreshed) as scheduled GitHub Action workflows. Visit the GitHub repository at https://github.com/rpodcast/pod-db-checker to find the following scripts:
duplicate_runner.R: Performs duplication analysis and necessary data pre-processing.pointblank_runner.R: Execute data quality checks with the{pointblank}package.