Human-Computer Interaction (HCI) research increasingly incorporates physiological signals, such as heart rate and brain activity, to enhance user experience and improve outcomes. However, sharing this data with others is crucial for repeatability, reproducibility, and replicability in scientific research. Currently, there are various platforms and frameworks available to facilitate open data sharing, but standardized documentation remains an essential aspect of the HCI field. This article discusses the importance of documenting physiological signal collection and interpretation processes and proposes a framework for standardized documentation.
The Need for Standardization
Standardized documentation allows researchers to share their methods and results more effectively, making it easier for others to understand how to use and interpret the data. Without standardization, data from individual, small-scale research projects (the "long tail of science") is challenging to utilize due to specific contexts or constraints in mind. Standardized documentation can also amplify scientific studies’ impact by drawing contributions from various disciplines.
The Proposed Framework
The authors propose a framework for standardized documentation based on existing efforts, such as the Open Science Framework and Zenodo. This framework includes guidelines for documenting how data should be shared and interpreted, emphasizing the importance of collaboration between researchers to create a comprehensive understanding of physiological signals. The authors also suggest using formal models detailing how the data should be shared and interpreted, such as Open-Neuro4 or ARTEM-IS.
The Importance of Collaboration
Collaboration is essential for creating a comprehensive understanding of physiological signals. Standardized documentation can help researchers share their methods and results more effectively, allowing for better collaboration and increased impact. By working together, the HCI community can develop a shared understanding of how to collect and interpret physiological signals, leading to more reliable and accurate research findings.
Conclusion
In conclusion, standardized documentation is crucial for ensuring the reliability and accuracy of physiological signal collection and interpretation in HCI research. The proposed framework provides a structure for collaboration between researchers, enabling them to share their methods and results more effectively. By working together, the HCI community can create a shared understanding of how to collect and interpret physiological signals, leading to more reliable and accurate research findings.
