@article{discovery10130698,
            note = {{\copyright} 2021 The Authors. Journal of Microscopy published by JohnWiley \& Sons Ltd on behalf of Royal Microscopical Society

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.},
          volume = {284},
           pages = {56--73},
           month = {October},
          number = {1},
         journal = {Journal of Microscopy},
           title = {QUAREP-LiMi: A community-driven initiative to establish guidelines for quality assessment and reproducibility for instruments and images in light microscopy},
            year = {2021},
        keywords = {Confocal, light microscopy, metadata, quality assessment, quality control, reproducibility,wide-field},
             url = {https://doi.org/10.1111/jmi.13041},
        abstract = {A modern day light microscope has evolved from a tool devoted to making primarily empirical observations to what is now a sophisticated, quantitative device that is an integral part of both physical and life science research. Nowadays, microscopes are found in nearly every experimental laboratory. However, despite their prevalent use in capturing and quantifying scientific phenomena, neither a thorough understanding of the principles underlying quantitative imaging techniques nor appropriate knowledge of how to calibrate, operate and maintain microscopes can be taken for granted. This is clearly demonstrated by the well-documented and widespread difficulties that are routinely encountered in evaluating acquired data and reproducing scientific experiments. Indeed, studies have shown that more than 70\% of researchers have tried and failed to repeat another scientist's experiments, while more than half have even failed to reproduce their own experiments1 . One factor behind the reproducibility crisis of experiments published in scientific journals is the frequent underreporting of imaging methods caused by a lack of awareness and/or a lack of knowledge of the applied technique2,3 . Whereas quality control procedures for some methods used in biomedical research, such as genomics (e.g., DNA sequencing, RNA-seq) or cytometry, have been introduced (e.g. ENCODE4 ), this issue has not been tackled for optical microscopy instrumentation and images. Although many calibration standards and protocols have been published, there is a lack of awareness and agreement on common standards and guidelines for quality assessment and reproducibility5 . In April 2020, the QUality Assessment and REProducibility for instruments and images in Light Microscopy (QUAREP-LiMi) initiative6 was formed. This initiative comprises imaging scientists from academia and industry who share a common interest in achieving a better understanding of the performance and limitations of microscopes and improved quality control (QC) in light microscopy. The ultimate goal of the QUAREP-LiMi initiative is to establish a set of common QC standards, guidelines, metadata models7,8 , and tools9,10 , including detailed protocols, with the ultimate aim of improving reproducible advances in scientific research. This White Paper 1) summarizes the major obstacles identified in the field that motivated the launch of the QUAREP-LiMi initiative; 2) identifies the urgent need to address these obstacles in a grassroots manner, through a community of stakeholders including, researchers, imaging scientists11 , bioimage analysts, bioimage informatics developers, corporate partners, funding agencies, standards organizations, scientific publishers, and observers of such; 3) outlines the current actions of the QUAREP-LiMi initiative, and 4) proposes future steps that can be taken to improve the dissemination and acceptance of the proposed guidelines to manage QC. To summarize, the principal goal of the QUAREP-LiMi initiative is to improve the overall quality and reproducibility of light microscope image data by introducing broadly accepted standard practices and accurately captured image data�metrics.},
          author = {Nelson, G and Boehm, U and Bagley, S and Bajcsy, P and Bischof, J and Brown, CM and Dauphin, A and Dobbie, IM and Eriksson, JE and Faklaris, O and Fernandez-Rodriguez, J and Ferrand, A and Gelman, L and Gheisari, A and Hartmann, H and Kukat, C and Laude, A and Mitkovski, M and Munck, S and North, AJ and Rasse, TM and Resch-Genger, U and Schuetz, LC and Seitz, A and Strambio-De-Castillia, C and Swedlow, JR and Alexopoulos, I and Aumayr, K and Avilov, S and Bakker, G-J and Bammann, RR and Bassi, A and Beckert, H and Beer, S and Belyaev, Y and Bierwagen, J and Birngruber, KA and Bosch, M and Breitlow, J and Cameron, LA and Chalfoun, J and Chambers, JJ and Chen, C-L and Conde-Sousa, E and Corbett, AD and Cordelieres, FP and Nery, ED and Dietzel, R and Eismann, F and Fazeli, E and Felscher, A and Fried, H and Gaudreault, N and Goh, WI and Guilbert, T and Hadleigh, R and Hemmerich, P and Holst, GA and Itano, MS and Jaffe, CB and Jambor, HK and Jarvis, SC and Keppler, A and Kirchenbuechler, D and Kirchner, M and Kobayashi, N and Krens, G and Kunis, S and Lacoste, J and Marcello, M and Martins, GG and Metcalf, DJ and Mitchell, CA and Moore, J and Mueller, T and Nelson, MS and Ogg, S and Onami, S and Palmer, AL and Paul-Gilloteaux, P and Pimentel, JA and Plantard, L and Podder, S and Rexhepaj, E and Royon, A and Saari, MA and Schapman, D and Schoonderwoert, V and Schroth-Diez, B and Schwartz, S and Shaw, M and Spitaler, M and Stoeckl, MT and Sudar, D and Teillon, J and Terjung, S and Thuenauer, R and Wilms, CD and Wright, GD and Nitschke, R}
}