Analyzing HC-NJDG Data to Understand the Pendency in High Courts in India
Kshitiz Verma

TL;DR
This study analyzes data from Indian High Courts to identify issues in case pendency, data accuracy, and suggests improvements for judicial efficiency and data management.
Contribution
It provides a detailed analysis of HC-NJDG data, highlighting errors, trends, and proposing data and scheduling improvements for reducing case backlog.
Findings
Judicial workload varies significantly across courts.
Many statistics on NJDG are inaccurate or outdated.
Regular data updates and better scheduling can reduce pendency.
Abstract
Indian Judiciary is suffering from burden of millions of cases that are lying pending in its courts at all the levels. In this paper, we analyze the data that we have collected on the pendency of 24 high courts in the Republic of India as they were made available on High Court NJDG (HC-NJDG). We collected data on 73 days beginning August 31, 2017 to December 26, 2018, including these days. Thus, the data collected by us spans a period of almost sixteen months. We have analyzed various statistics available on the NJDG portal for High Courts, including but not limited to the number of judges in each high court, the number of cases pending in each high court, cases that have been pending for more than 10 years, cases filed, listed and disposed, cases filed by women and senior citizens, etc. Our results show that: 1) statistics as important as the number of judges in high courts have…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsArtificial Intelligence in Law · Legal Education and Practice Innovations · Judicial and Constitutional Studies
