Comprehensive assessment of open science practices in indoor positioning: open data, code, and material

Abstract

Transparency and verifiability have long been regarded as cornerstones of the scientific ethos and practice. However, persistent reproducibility challenges across numerous disciplines have brought renewed attention to the imperative for widespread adoption of Open Science practices. These considerations are particularly relevant to the research field of Indoor Positioning. Open Data and Open Code sharing are gradually gaining traction in the field, but are still far from standard practice. This study comprehensively evaluates the extent of the adoption of Open Science practices within the community of the International Conference on Indoor Positioning and Indoor Navigation (IPIN), by systematically analyzing all reference papers from the 2019 to 2024 editions of the IPIN conference. The work thoroughly examines the Open Data and Code usage, and the use of other types of Open Materials while performing a particular, close-up review of the Open Data that are leveraged in these studies. Our findings reveal that 21.7% of papers use Open Research Data (ORD), 8.3% utilize Open Code, and 20.2% incorporate other Open Materials. However, only 6.8% of papers provide both Open Data and Code. Moreover, emerging patterns and intuitive best practices are highlighted. The complete characterization of all reviewed publications is publicly available. This study brings to light the need for wider adoption of Open Science practices, to enhance the transparency, reproducibility, replicability, and reliability of research outcomes in the field of Indoor Positioning.