Any form of scientific data collection and analysis comes with the responsibility to make unbias analysis and complete reporting to allow reproducibility. The aim of this page is to list some generic points of good sientific practice to consider for field of Microscopy and Image Analysis.
IMPORTANCE OF DOCUMENTATION:
Based on the alarming, survey of many prominent journals reported by G. Marques, T. and M. Sanders that showed that most microscopy-based experiments are severely under- and mis-reported in the literature. (https://elifesciences.org/articles/55133), we were triggered to initiate this website. Please consider the points addressed below to best allow reproducibility of your published data.
MICROSCOPY:
- Heddleston, J.M., Aaron, J.S., Khuon, S., Chew, T.-L. (2021) A guide to accurate reporting in digital image acquisition – can anyone replicate your microscopy data? (https://is.gd/kVisb4)
- Nature Method Focus Issue of 03 December 2021 featured a series of papers offering guidelines and tools for improving the tracking and reporting of microscopy metadata with an emphasis on reproducibility and data re-use → click
IMAGE ANALYSIS:
- Christopher Schmied et al, QUAREP-LiMi (2023) Community-developed checklists for publishing images and image analysis (arXiv:2302.07005)
- Aaron, J.S., Chew, T.-L. (2021) A guide to accurate reporting in digital image processing – can anyone reproduce your quantitative analysis? J. Cell Sci. doi:10.1242/jcs.254151(https://is.gd/PlGrnz)
- Visit Online Learning Tool for Research integrity and image Processing: learn about what is appropriate image processing in science and what is not – including video tutorials