dataesr/scientific-paragraphs-categorization huggingface dataset:
Furthermore, it would provide clear guidance to the manufacturers of microscopy instruments, hardware components, and processing software about what information the scientific community requires to ensure scientific rigor so that they can be automatically provided during acquisition and written in the headers of image files. Last but not least, machine-actionable versions of the same information (  14 ) could be provided alongside image datasets on the growing number of public image data resources (3) that allow the deposition of raw image data associated with scientific manuscripts, a promise to emulate for light microscopy the successful path that has led to community standards in the field of genomics  (15) (16) (17) (18) (19) ) (e. g. , the IDR  (20) , EMPIAR  (21) , and Bioimage Archive  (22)  hosted at the EMBL -EBI; the European Movincell  (23) ; the Japanese SSBD hosted by RIKEN  (24) ; and, in the USA, the NIH-funded Cell Image Library  (25, 26) , BRAIN initiative's imaging resources  (27) , the Allen Cell Explorer (28), and the Human Cell Atlas  (29) (30) (31) (32) ).
Despite their value in indicating a path forward, guidelines, specifications, and standards on their own lack the one essential feature that would make them actionable by experimental scientists faced with the challenge of producing well-documented, high-quality, reproducible and re-usable datasets: namely easy-to-use software tools or even better-automated pipelines to extract all available metadata from microscope configuration and image data files. While some advances have been proposed, such as OMERO. forms  (45) , PyOmeroUpload  (46)  and MethodsJ  (5) , these tools only offer limited functionalities, are not integrated with community standards and are not per se future proof. To provide a way forward, in this and in two related manuscripts, we present a suite of three interoperable software tools (Supplemental Figure  1 ) that were developed to provide highly complementary, intuitive approaches for the bench-side collection of Image Metadata, with particular reference to Experimental Metadata and Microscopy Metadata  (37, 38).
Methods: Implementation and Availability Micro-Meta App is available in two JavaScript (JS) implementations. The first was designed to facilitate the incorporation of the software in existing third party web portals (i. e. , the 4DN Data Portal)  (34, 52)  and was developed using the JavaScript React library, which is widely used to build web-based user interfaces. Starting from this version, a stand-alone version of the App was developed by wrapping the React implementation using the JavaScript Electron library, with the specific purpose of lowering the barrier of adoption of the tool by labs that do not have access or prefer not to use imaging databases. More details about the implementation of Micro-Meta App are available in Supplemental Material. In order to promote the adoption of Micro-Meta App, incorporation in third party data portals and re-use of the source code by other developers, the executables and source code for both Javascript React and Electron implementations of Micro-Meta App are available on GitHub  (53, 54).
Micro-Meta App: an intuitive, highly visual interface to facilitate microscopy metadata collection While the establishment of data formats, metadata standards and QC procedures is important, it is not per se sufficient to make sure reporting and data quality guidelines are adopted by the community. To ensure their routine utilization, it is, therefore, necessary to produce software tools that expedite QC procedures and image data documentation and make it straightforward for investigators to reproduce results and make decisions regarding the utility of specific datasets for addressing their specific questions. However, despite the availability of the OME Data Model and Bioformats  (41, 43) , the lack of standards has resulted in a scarce adoption of minimal information criteria and as a result the metadata provided by instrument and software manufacturers is scarce (Supplemental Table  I  and II).
Micro-Meta App was developed to address this unmet need. Micro-Meta App consists of a Graphical User Interface (GUI)-based open-source and interoperable software tool to facilitate and (when possible) automate the annotation of fluorescence microscopy datasets. The App provides an interactive approach to navigate through the different steps required for documenting light microscopy experiments based on available OME-compatible community-sanctioned tiered systems of specifications. Thus, Micro-Meta App is not only capable of adapting to varying levels of imaging complexity and user experience but also to evolving data models that might emerge from the community. At the time of writing, the App implements the Core of the OME Data Model and the tiered 4DN-BINA-OME Basic extension  (36) (37) (38) 51).
JSON files (example available on Zenodo as illustrated in Supplemental Material)  (57)  that can be saved locally, used by existing third-party web-portals  (52) , integrated with other software tools (MethodsJ2) and shared with other scientists, thus significantly lowering the manual work required for rigorous record-keeping and enabling rapid uptake and widespread implementation. 3) When user is ready to collect metadata to document the acquisition of specific image data sets, the Manage Settings section of the App automatically imports Hardware Specifications metadata from previouslyprepared Microscope. JSON files and uses the BioFormats library  (43)  to extract available, OME-compatible metadata from an image data file of interest. From this basis, the App interactively guides the user to enter missing metadata specifying the tier-appropriate Settings used for a specific Image Acquisition session (Figures  2B  and 4 ).
4) As a final step, the App generates interoperable paired Microscope-and Settings-JSON files (example available on Zenodo as illustrated in Supplemental Material) (57) that together contain comprehensive documentation of the conditions utilized to produce individual microscopy datasets and can be stored locally or integrated by third-party data portals (i. e. , the 4D Nucleome Data Portal)  (58). Depending on the specific implementation of the Micro-Meta App being used (see Implementation section), the workflow varies slightly. The discussion below refers specifically to the stand-alone version of Micro-Meta App implemented in JavaScript Electron.
e. , Create Inverted from scratch or Create Upright from scratch), the user is presented with a blank microscope canvas of the selected type to work with (Figure  3E ). ii) When selecting Load from file, the user is asked to select a pre-existing Microscope. JSON (example available on Zenodo as illustrated in Supplemental Material) (57) file from the local file system. Such Microscope. JSON files could, for example, be a template file that was created by microscope custodians at the local microscopy core facility, shared by a colleague, or downloaded from a repository for local use. iii) Finally, a pre-existing Microscope. JSON file that has already been processed and saved to the local Micro-Meta App's Home Folder can be loaded for further editing using the Load from repository modality. Here existing Microscope.
4) Once all appropriate microscope hardware components for a given instrument have been added to the canvas and appropriately attended to, the resulting tier-specific microscope Hardware Specification descriptions are then output as structured and interoperable Microscope. JSON files (example available on Zenodo as illustrated in Supplemental Material)  (57). These files can be Saved locally (Figure  3G ) or used by existing third-party databases, such as the 4DN Data Portal (34, 58) (Figure  6 ), for later utilization during the Manage Settings modality of the Micro-Meta App (see next section). In addition, such files can be imported in MethodsJ2 and used to automatically generate the Methods and Acknowledgement sections of scientific publications as described in a parallel manuscript  (50).
Manage Image Acquisition Settings This modality is used to produce metadata-rich descriptions of the Image Acquisition Settings utilized to produce a given image dataset (Figure  4 ). In this modality, Micro-Meta App: 1) imports an existing Microscope. JSON file describing the instrument used to acquire the image data to be documented; 2) utilizes BioFormats  (43)  to read available OME-specified microscopy metadata stored in the header of the desired image file by the manufacturer of the microscope or of the acquisition software (Supplemental Tables I and II); 3) interactively guides the user through the collection of the missing, instrument-specific, tier-appropriate, 4DN-BINA-OME sanctioned Image Acquisition Settings utilized to produce the selected image data; and 4) produces structured Settings.
JSON files (example available on Zenodo as illustrated in Supplemental Material) (57) that can be stored locally or in appropriate data portals alongside the images and the appropriate Microscope. JSON file. More in detail, the Manage Settings modality of Micro-Meta App articulates around the following steps: 1) After selecting a documentation tier (Figure  3A ) and launching the App in the Manage Settings modality (Figure  4A ), the user selects an available Microscope. JSON file from the local file system or a suitable repository (Figure  4B ), selects an available image dataset to be annotated (Figure  4C ) and either creates a new Settings. JSON file or opens an existing file to edit (Figure  4D ). The integration of the Bio-Formats API  (43)  as part of Micro-Meta App permits the App to interpret image file headers, extract available metadata and populate Instrument-specific, OME-compatible, tier-appropriate metadata fields to facilitate metadata annotation.
2) As a result of the previous step, a diagrammatic representation of Image Acquisition Settings is displayed to the user and components or fields containing missing metadata values are highlighted in red to solicit the user's attention (Figure  4E ). After attending to all missing values, the user can then produce a validated 4DN-BINA-OME-compatible and tier-appropriate Settings. JSON file, which coupled with the corresponding Microscope. JSON file can be associated with the relevant image datasets in the local file system or on an appropriate repository, such as the 4DN Data Portal  (34, 52)   4F ,  [6. 2] ). The same Channel-specific interface can also be used to manage advanced Light Path features, such as in cases in which a custom-developed microscope has to be described (Figure  4G ).
Beta testing Micro-Meta App was developed in the context of community efforts organized around the 4DN Consortium need for imaging data dissemination and integration with omics datasets  (33, 34)  and the BINA (35) effort to improve rigor quality control and reproducibility in light microscopy. As part of this effort, several core facilities were identified to serve as reference beta-testing sites for Micro-Meta App (Supplemental Table  III ). To this aim, the stand-alone JavaScript Electron implementation of Micro-Meta App was locally deployed and microscope custodians at individual beta testing sites were trained both on the use of the App and on bug and feature request reporting. Such feedback was collected either directly or by taking advantage of the GitHub issue-reporting feature and incorporated into the main development branch in a close-iterative cycle ahead of the release of the initial production version of the software.
Utilization at core facilities In response to significant interest we observed in the community and after beta testing, microscope custodians at several light microscopy facilities (Supplemental Table  III ) volunteered to serve as case studies on the use of Micro-Meta App to document both microscope instrumentation and example published image datasets produced in microscopy platforms  (60) (61) (62) (63) (64) (65) (66) (67) (68) (69) (70) (71) (72) (73) (74) (75) (76) (77) (78) (79). The application was utilized by microscope custodians at 16 sites to document one of their microscopes alongside the settings utilized for published images based on the 4DN-BINA-OME model Core + Basic Extension (37, 38, 51) (Figure  5  and Supplemental Figures  2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 ). As indicated, the microscopes whose hardware was documented using Micro-Meta App comprised advanced custom-built microscopes, widefield microscopes and microscope stands associated with confocal systems, produced by all four major manufacturers.
As a further testament of the robustness of the approach, several different major categories of imaging experiments were covered in this case study including: 1) Immunofluorescence imaging of the three-dimensional distribution of HIV-1 retroviral particles in the nucleus of infected human cells (Figure  5 ; example Microscope-and Settings. JSON files for this use case are available on Zenodo as illustrated in Supplemental Material)  (57). 2) Three-dimensional visualization of superhydrophobic polymer-nanoparticles (Supplemental Figure  2 ). 3) Immunofluorescence imaging of cryosection of Mouse kidney (Supplemental Figure  4 ). 4) Three-dimensional immunofluorescence imaging of the phagocytic activity of human rhinovirus  16 (HRV16)  infected macrophages (Supplemental Figure  7 ). 5) Live-cell imaging of N.
The most striking result of these use cases was that in comparison with the metadata reporting baseline represented by the metadata fields made available using BioFormats alone, the use of Micro-Meta App significantly increased the uniformity of reported metadata fields. This facilitates the comparison of image data within and across different microscopes and imaging experiments. In addition, because the underlying data model utilized by Micro-Meta App is dynamically defined on the basis of shared guidelines that can evolve depending on needs and technological development, the use of this documentation method maximized reproducibility, quality and value and minimized effort on the part of individual scientists. The example set of Microscope-and Settings. JSON files produced for the use case illustrated in Figure  5 , alongside the associated image file are available on Zenodo as illustrated in Supplemental Material  (57).
Integration to 4DN Data Portal One of the initial impetus for the development of Micro-Meta App was the need to expedite and, when possible, automate the rigorous reporting of imaging experiments and quality control procedures. In this context, Micro-Meta App was developed to be directly integrated into the 4DN Data Portal  (34, 58). For this use, the App's data flow was adapted to allow the direct integration of the content of the Microscope-and Settings-JSON files into the portal database. This allows individual fields to be utilized for filtering and searching purposes and to be visualized directly on the portal (Figure  6 ). In addition to maximizing flexibility, interfaces were developed to allow the import of pre-existing files the user might have produced using the desktop version of the App.
g. , laser combiner with the wrong laser lines for the experiment and broadband source). At the same time the rest of the Microscope. JSON file could be kept at a very basic level to reduce grading complexity. In another example, a course might start on Day 1 with a Microscope. JSON file that only has a few components at Tier 1. On subsequent days, more components might be added, and the tier-level might be raised up to Tier 3 depending on the specific course teaching goals. In addition to the tested use-cases, Micro-Meta App might be used in teaching modules available online (e. g. , core facility user training) or used for flipped-classroom settings, where Micro-Meta App would be used for the practical application of microscopy concepts learned individually. Specifically, Micro-Meta App might be used to create snapshots of microscopes or as a guided sequence for familiarizing the user with the intricacies of specific instrument hardware configurations.
As a starting point, illumination and detector calibration metrics calculated using the open-hardware Meta-Max(  82 ) calibration tool will be automatically imported and used to annotate imaging datasets. 3) Further integration with MethodsJ2: Future development will: 1) integrate the Micro-Meta App software metadata Settings. JSON file so that it can serve as a source of Microscopy Metadata for MethodsJ2  (50). 2) Adapt Micro-Meta App to generate methods text directly so researchers can use their platform of choice. 4) Further OMERO and OMERO. mde integration: As part of the initial Micro-Meta App development endeavor, a partial-functionality, prototype OMERO-plugin version of the App was developed and integrated into the OMERO instance, which is available at the University of Massachusetts Medical School (UMMS)  (83).
In an effort to facilitate the wide adoption of Micro-Meta App by the imaging community, integration with OMERO will be completed, including the extracting experimental metadata as specified by extended specifications as developed using OMERO. mde  (49)  and saving 4DN-BINA-OME metadata  (38, 39)  as collections of key-value pairs associated with individual image datasets. 5) Creation of Instrument and Hardware components databases: While engaging with microscope hardware manufacturers to ensure the full automation of data provenance and quality control reporting for light microscopy, it will be necessary to further reduce the documentation burden imposed on bench-side scientists, therefore maximizing their adoption of community standards. To this purpose, we will work in the context of Bioimaging North America to develop sharable databases of Microscope.
Conclusions For this work to have a broad impact tools such as Micro Meta App are required so that biological scientists will be able to quickly adopt metadata recommendations and incorporate them in their everyday work without requiring an extensive time commitment and regardless of their imaging expertise. This means that tools will need to be developed, accessible and straightforward to use in order to be successful and implement the proposed guidelines and metadata standards broadly. Ultimately, this will lead to automating all aspects of the process utilized by members of the community to annotate and upload metadata-rich imaging datasets to both local repositories such as OMERO  (86)  and public repositories such as Image Data Resource (IDR)  (20)  or other public image archives  (22).
In addition to the development of community standards for microscopy, reaching this goal will entail the automated interpretation of metadata stored in image file headers, the development of a communitywide repository for the storage of metadata specifications for commercial and custom-made microscopy hardware commonly utilized by imaging laboratories, and the automated annotation of imaging datasets to be uploaded in imaging data portals or disseminated through other means. Availability, requirements, resources, and documentation • Operating system(s): MacOS and PC • Programming language: Javascript and Java • Other requirements: Java v1. 8. 0. In addition, see dependencies listed in Supplemental Material. • License: GNU GPL v3 (https://www. gnu. org/licenses/gpl-3. 0. html).
FIGURES Figure  1  | Micro-Meta App data processing workflows. Flow-chart depicting the two data-processing workflows available in Micro-Meta App. A) After selecting the documentation tier-level  [1]  appropriate for a given experiment-design and instrument-complexity as sanctioned by the 4DN-BINA-OME Microscopy Metadata Specifications  (38) , in the Manage Instrument section of the App the user is visually guided through the steps (Figures  2  and 3 ) required for the de novo creation a new Microscope hardware specifications file containing a list of components and associated 4DN-OME-BINAspecified metadata values. Alternatively, an existing Microscope-metadata file can be opened for validation, editing or revision. At the end of a given Manage Instrument session, the gathered hardware specifications metadata information is then saved in a Microscope JSON file that is used in the Manage Settings section of the App as the basis for the documentation of any image dataset acquired using the microscope in question.
B) When microscope users are ready to document the acquisition-settings associated with a given image dataset, the Manage Settings section of Micro-Meta App (Figure  1 ) is used to: 1) choose the appropriate documentation Tier-level  (38) ; 2) select an existing Microscope. JSON file describing the hardware configuration of the microscope used for acquisition; 3) open a representative image data file from the dataset of interest, and leverage BioFormats  (43)  to automatically retrieve available OME-compatible microscopy metadata from the header of the file; and 4) de novo create (or edit) a Settings. JSON file containing a detailed 4DN-BINA-OME-sanctioned description of the image acquisition metadata. This file is then saved in association with the image dataset either on the user's desktop or in an available third-party data portal, and, as an example, can be used to automatically produce Methods text using MethodsJ2  (50).
Example Microscope. JSON, Settings. JSON and associated image data file are available at: https://doi. org/10. 5281/zenodo. 4891883. (38). Specifically, the App allows users to drag-and-drop individual hardware components (i. e. , Light Sources, Objectives, Filters, Detectors, Lens, etc. ,) onto the App workspace, and subsequently enter Tier-specific 4DN-BINA-OME-specified metadata values associated with each of the components to be saved in a reusable Microscope. JSON file. In the depicted example, the user clicks on icons representing a given Objective, Filter Set and Camera component and enters 4DN-BINA-OME-sanctioned Hardware Specifications metadata values associated with each of the items (e. g. , Objective Manufacturer, Model, Magnification and Numerical Aperture). B) Using the Manage Settings section of Micro-Meta App the user opens a previously created Microscope metadata file and an image whose acquisition has to be documented.
E) In this example, the "Magnification" drop-down menu is opened  [1]  and an "Objective" is dragged and snapped-in-place in the designated position  [2]  on the workspace. F) In this example, an additional "Objective"  [3]  is dragged onto the workspace and relevant metadata fields are entered using the designated metadata entry form  [4]. G) Once all changes are entered, the microscope file can be saved to file or to the desired repository. (34, 52, 57). For this use the App's data flow was adapted to allow the direct ingestion of the content of the JSON Microscope-and Settings-files into the portal database, which allows individual fields to be utilized for filtering and searching purposes and to be visualized directly on the portal.
Acknowledgments We would like to thank  Lawrence Lifshitz  at the  Biomedical Imaging Group of the Program in Molecular Medicine at the University of Massachusetts Medical School  for invaluable intellectual input and countless fruitful discussions and for their friendship, advice, and steadfast support throughout the development of this project. We acknowledge  Matteo Luban  for critically reading and editing the manuscript. This project could never have been carried out without the leadership, insightful discussions, support and friendship of all OME consortium members, with particular reference to  Jason Swedlow ,  Josh Moore ,  Chris Allan ,  Jean Marie Burel , and  Will Moore. We are massively indebted to the  RIKEN  community for their fantastic work to bring open science into biology.