MethodsJ2: a software tool to capture metadata and generate comprehensive microscopy methods text

Ryan, Joël; Pengo, Thomas; Rigano, Alex; Itano, Michelle S.; Cameron, Lisa; Marqués, Guillermo; Strambio‐De‐Castillia, Caterina; Sanders, Mark A.; Brown, Claire M.

doi:10.1038/s41592-021-01290-5

Cited by 10 publications

(7 citation statements)

References 22 publications

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“…These challenges are being tackled by multiple initiatives that have, for example, proposed a set of standard file formats for bioimaging, 10 , 27 a tiered system for metadata specifications, 51 and have created imaging-specific repositories. 23 – 25 For example, novel tools for metadata annotation 28 , 29 , 52 are now available to be tested and refined in use case scenarios. The survey results show that only a small percentage uses these and harvests their benefits.…”

Section: Discussionmentioning

confidence: 99%

Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

Schmidt

Hanne²,

Moore³

et al. 2022

F1000Res

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Background: Knowing the needs of the bioimaging community with respect to research data management (RDM) is essential for identifying measures that enable adoption of the FAIR (findable, accessible, interoperable, reusable) principles for microscopy and bioimage analysis data across disciplines. As an initiative within Germany's National Research Data Infrastructure, we conducted this community survey in summer 2021 to assess the state of the art of bioimaging RDM and the community needs. Methods: An online survey was conducted with a mixed question-type design. We created a questionnaire tailored to relevant topics of the bioimaging community, including specific questions on bioimaging methods and bioimage analysis, as well as more general questions on RDM principles and tools. 203 survey entries were included in the analysis covering the perspectives from various life and biomedical science disciplines and from participants at different career levels. Results: The results highlight the importance and value of bioimaging RDM and data sharing. However, the practical implementation of FAIR practices is impeded by technical hurdles, lack of knowledge, and insecurity about the legal aspects of data sharing. The survey participants request metadata guidelines and annotation tools and endorse the usage of image data management platforms. At present, OMERO (Open Microscopy Environment Remote Objects) is the best known and most widely used platform. Most respondents rely on image processing and analysis, which they regard as the most time-consuming step of the bioimage data workflow. While knowledge about and implementation of electronic lab notebooks and data management plans is limited, respondents acknowledge their potential value for data handling and publication. Conclusion: The bioimaging community acknowledges and endorses the value of RDM and data sharing. Still, there is a need for information, guidance, and standardization to foster the adoption of FAIR data handling. This survey may help inspiring targeted measures to close this gap.

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Section: Discussionmentioning

confidence: 99%

Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

Schmidt

Hanne²,

Moore³

et al. 2022

F1000Res

View full text Add to dashboard Cite

show abstract

“…Sharing metadata on public repositories can reduce the efforts in metadata mining directly from original publications or from the request to the authors since the both processes can be time-consuming and error-prone 11,[32][33][34] . Leveraging previously published data for novel biological discoveries could be facilitated when the metadata accompanying its raw omics data is reported, present in a standardized format, and made available in online repositories 10,35,36 . Improving the availability of metadata in public repositories could provide valuable and accurate information for downstream analyses, and further enhance the usefulness of the GEO database.…”

Section: Discussionmentioning

confidence: 99%

“…Sharing metadata on public repositories can reduce the efforts in metadata mining directly from the textual content of publications or from the request to the authors since the both processes can be time-consuming and error-prone 11,[33][34][35] . Leveraging previously published data for novel biological discoveries could be facilitated when the metadata accompanying its raw omics data is reported, present in a standardized format, and made available in online repositories 5,36,37 .…”

Section: Discussionmentioning

confidence: 99%

The systematic assessment of completeness of public metadata accompanying omics studies

Huang

Rajesh

Ayyala

et al. 2021

Preprint

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The scientific community has accumulated enormous amounts of genomic data stored in specialized public repositories. Genomic data is easily accessible and available from public genomic repositories allowing the biomedical community to effectively share the omics datasets. However, improperly annotated or incomplete metadata accompanying the raw omics data can negatively impact the utility of shared for secondary analysis. In this study, we perform a comprehensive analysis under 137 studies over 18,559 samples across six therapeutics fields to assess the completeness of metadata accompanying omics studies in both publication and its related online repositories across and make observations about how the process of data sharing could be made reliable. This analysis involved an initial literature survey in finding studies based on the seven therapeutic fields, that are Alzheimer’s disease, acute myeloid leukemia, cystic fibrosis, cardiovascular diseases, inflammatory bowel disease, sepsis, and tuberculosis. We carefully examined the availability of metadata over nine clinical variables, that included disease condition, age, organism, sex, tissue type, ethnicity, country, mortality, and clinical severity. By comparing the metadata availability in both original publications and online repositories, we observed discrepancies in sharing the metadata. We determine that the overall availability of metadata is 72.8%, where the most complete reported phenotypes are disease condition and organism, and the least is mortality. Additionally, we examined the completeness of metadata reported separately in original publications and online repositories. The completeness of metadata from the original publication across the nine clinical phenotypes is 71.1%. In contrast, the overall completeness of metadata information from the public repositories is 48.6%. Our study is the first one to assess the completeness of metadata accompanying raw data across a large number of studies and phenotypes and opens a crucial discussion about solutions to improve completeness and accessibility of metadata accompanying omics studies.

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“…42 Tools are available to support metadata annotation. [43][44][45] Tabular metadata collection formats are often used. 7,40 Optionally, core facilities can enforce metadata enrichment, especially for large data otherwise hard to manage.…”

Section: Experiments Planningmentioning

confidence: 99%

A practical guide to bioimaging research data management in core facilities

Schmidt,

Boissonnet,

Dohle

et al. 2024

Journal of Microscopy

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Bioimage data are generated in diverse research fields throughout the life and biomedical sciences. Its potential for advancing scientific progress via modern, data‐driven discovery approaches reaches beyond disciplinary borders. To fully exploit this potential, it is necessary to make bioimaging data, in general, multidimensional microscopy images and image series, FAIR, that is, findable, accessible, interoperable and reusable. These FAIR principles for research data management are now widely accepted in the scientific community and have been adopted by funding agencies, policymakers and publishers. To remain competitive and at the forefront of research, implementing the FAIR principles into daily routines is an essential but challenging task for researchers and research infrastructures. Imaging core facilities, well‐established providers of access to imaging equipment and expertise, are in an excellent position to lead this transformation in bioimaging research data management. They are positioned at the intersection of research groups, IT infrastructure providers, the institution´s administration, and microscope vendors. In the frame of German BioImaging – Society for Microscopy and Image Analysis (GerBI‐GMB), cross‐institutional working groups and third‐party funded projects were initiated in recent years to advance the bioimaging community's capability and capacity for FAIR bioimage data management. Here, we provide an imaging‐core‐facility‐centric perspective outlining the experience and current strategies in Germany to facilitate the practical adoption of the FAIR principles closely aligned with the international bioimaging community. We highlight which tools and services are ready to be implemented and what the future directions for FAIR bioimage data have to offer.

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MethodsJ2: a software tool to capture metadata and generate comprehensive microscopy methods text

Cited by 10 publications

References 22 publications

Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

The systematic assessment of completeness of public metadata accompanying omics studies

A practical guide to bioimaging research data management in core facilities

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