{"doi":"10.1093/gigascience/giaf127","title":"CryoDataBot: a pipeline to curate cryoEM datasets for AI-driven structural biology","abstract":"Cryogenic electron microscopy (cryoEM) has revolutionized structural biology by enabling atomic-resolution visualization of biomacromolecules. With artificial intelligence (AI) increasing role in newly developed cryoEM tools, task-specific datasets have become essential. Yet assembling such datasets often demands considerable effort and domain expertise, constraining AI-driven cryoEM tool development efforts. Here, we present CryoDataBot, an automated pipeline that addresses this gap. CryoDataBot streamlines data retrieval, preprocessing, and labeling, with fine-grained quality control and flexible customization, enabling efficient generation of robust datasets. CryoDataBot's effectiveness is demonstrated through improved training efficiency in U-Net models and rapid, effective retraining of CryoREAD, a widely used RNA modeling tool. By simplifying the workflow and offering customizable quality control, CryoDataBot enables researchers to easily tailor dataset construction to the specific objectives of their models, while ensuring high data quality and reducing manual workload. This flexibility supports tools development for a wide range of applications in AI-driven structural biology.","journal":"GigaScience","year":2025,"id":554417,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":22.178386323199504,"corpus_rank":9377,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8677,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":50.0,"fair_percentile":62.702537450321,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1451675,"name":"Leon Wu","orcid":"0009-0009-6227-8298","position":1,"is_corresponding":false},{"id":1451676,"name":"Michael Rebelo","orcid":"0009-0007-7732-9161","position":2,"is_corresponding":false},{"id":80413,"name":"Shi Feng","orcid":"0009-0009-5468-9791","position":3,"is_corresponding":false},{"id":1255862,"name":"Xinye Yu","orcid":"0000-0002-1764-1141","position":4,"is_corresponding":false},{"id":1336387,"name":"Farhanaz Farheen","orcid":"0009-0006-5683-6853","position":5,"is_corresponding":false},{"id":316939,"name":"Daisuke Kihara","orcid":"0000-0003-4091-6614","position":6,"is_corresponding":false},{"id":266761,"name":"Z. Hong Zhou","orcid":"0000-0002-8373-4717","position":7,"is_corresponding":false},{"id":1451674,"name":"Qibo Xu","orcid":"0000-0003-2084-3390","position":0,"is_corresponding":true}],"reference_count":34,"raw_metadata":null,"created_at":"2026-07-19T02:54:50.112989Z","pmid":"41124016","pmcid":"PMC12596181","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":61.1111,"fair_a":25.0,"fair_i":20.0,"fair_r":50.0,"fair_zscore":0.6155,"fair_rationale":{"fair_score":50.0,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":61.11,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"10.5524/102765","grounded":true,"rationale":"The dataset is assigned a DOI (10.5524/102765) in the reference list, which is a persistent identifier scheme.","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"All data that support this study are available in GigaScience repository, GigaDB [37].","grounded":false,"rationale":"GigaDB (GigaScience Database) is a named data repository. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","anchors":["RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed (","NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived","NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"All data that support this study are available in GigaScience repository, GigaDB [37].","grounded":false,"rationale":"The statement points to a repository record (GigaDB) with a reference entry, which is Colavizza category 3. [downgraded to 'partial' — no verifiable quote from the paper]","anchors":["Colavizza, Hrynaszkiewicz, Staden, Whitaker & McGillivray (2020), 'The citation advantage of li","Springer Nature research data policy — Data Availability Statements: standard statement templat","RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes"],"scored":false,"signal":null},{"key":"f_discovery_metadata","label":"Description of the dataset as an object","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"The entries of the cryoEM maps and their corresponding atomic models used in this study are listed in the supplementary tables.","grounded":true,"rationale":"The dataset's content (the list of EMDB entries) is described in a sentence, but no itemised inventory of the deposited dataset's files or variables is given. [majority verdict 'partial' (3/5 passes agreed)]","anchors":["RDA-F2-01M — 'Rich metadata is provided to allow discovery' (priority Essential)","FsF-F2-01M — F-UJI: 'Metadata includes descriptive core elements to support data findability'","FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'"],"scored":false,"signal":null},{"key":"f_dataset_cited","label":"Dataset formally cited","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"Xu Q, Wu L, Rebelo M, et al. Supporting data for “CryoDataBot: A Pipeline to Curate CryoEM Datasets for AI-Driven Structural Biology.” GigaScience Database. 2025. 10.5524/102765.","grounded":false,"rationale":"The dataset appears as a reference-list entry (reference 37) with a DOI. [downgraded to 'partial' — no verifiable quote from the paper]","anchors":["FORCE11 Joint Declaration of Data Citation Principles (2014) — data should be cited as a first-","RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes","FsF-F3-01M — F-UJI: 'Metadata includes the identifier of the data it describes'"],"scored":true,"signal":null}]},"A":{"name":"Accessible","score":25.0,"criteria":[{"key":"a_data_openly_accessible","label":"Access route free of preconditions","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"All data that support this study are available in GigaScience repository, GigaDB [37].","grounded":false,"rationale":"The statement points to a public repository with no precondition mentioned. [downgraded to 'partial' — no verifiable quote from the paper]","anchors":["RDA-A1.1-01D — 'Data is accessible through a free access protocol'","FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data'","NSTC Desirable Characteristics of Data Repositories (2022) — 'Free and Easy Access'"],"scored":true,"signal":null},{"key":"a_access_conditions_stated","label":"Access level labelled","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":"All data that support this study are available in GigaScience repository, GigaDB [37].","grounded":false,"rationale":"The paper states where the data can be obtained but does not apply an explicit access-level label such as 'open access' or 'freely available'. [downgraded to 'no' — no verifiable quote from the paper]","anchors":["FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data'","RDA-A1-01M — metadata contains information to enable the user to get access to the data","COAR Controlled Vocabularies — Access Rights v1.0 (open / embargoed / restricted / metadata-onl"],"scored":false,"signal":null},{"key":"a_controlled_access_for_sensitive","label":"Gatekeeper for sensitive data","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The data are not human-subject or sensitive, and no gatekeeper of any kind is named; the data are openly available.","anchors":["NIH Genomic Data Sharing Policy (NOT-OD-14-124) — controlled-access via a Data Access Committee","RDA-A1.2-01D — 'Data is accessible through an access protocol that supports authentication and ","NIH DMS Policy Element 5 (NOT-OD-21-014) — Access, Distribution, or Reuse Considerations (conse"],"scored":false,"signal":null},{"key":"a_timeline_retention","label":"Availability timing & retention","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No sentence in the paper states when the data become available (timing) or how long they persist (retention).","anchors":["NIH DMS Plan Element 4 (NOT-OD-21-014) — Data Preservation, Access, and Associated Timelines","NSTC Desirable Characteristics (2022), Organizational Infrastructure: 'Retention Policy'","RDA-A2-01M — 'Metadata is guaranteed to remain available after data is no longer available'"],"scored":false,"signal":null}]},"I":{"name":"Interoperable","score":20.0,"criteria":[{"key":"i_open_nonproprietary_format","label":"Open file format","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No file format is named for the released data. [majority verdict 'no' (4/5 passes agreed)]","anchors":["FsF-R1.3-02D — F-UJI: 'Data is available in a file format recommended by the target research co","RDA-R1.3-02D — data is expressed in a machine-understandable community standard","RDA-I1-01D — data uses a knowledge representation expressed in a standardised format"],"scored":true,"signal":null},{"key":"i_community_standard_vocabulary","label":"Community standard / vocabulary","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No data or metadata community standard (e.g., MIAME, GO, BIDS) is named as being applied to the study's own dataset. [majority verdict 'no' (4/5 passes agreed)]","anchors":["RDA-R1.3-01M — 'Metadata complies with a community standard' (priority Essential)","RDA-R1.3-01D — 'Data complies with a community standard'","RDA-I2-01M — '(Meta)data use vocabularies that follow FAIR principles'"],"scored":false,"signal":null},{"key":"i_qualified_references","label":"Identifiers for the resources the data depend on","kind":"llm","weight":0.5,"fraction":1.0,"verdict":"yes","evidence":"EMD-2875","grounded":true,"rationale":"The paper provides identifiers for third-party resources: EMDB IDs, PDB IDs, and the code repository (GitHub URL and WorkflowHub DOI).","anchors":["RDA-I3-01M — '(meta)data include references to other (meta)data'","RDA-I3-03M — 'metadata includes qualified references to other metadata'","FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'"],"scored":false,"signal":null}]},"R":{"name":"Reusable","score":50.0,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No reuse licence or terms document is named for the deposited dataset; the CC-BY licence applies only to the article.","anchors":["RDA-R1.1-01M — 'Metadata includes information about the licence under which the data can be reu","RDA-R1.1-02M — 'Metadata refers to a standard reuse licence'","RDA-R1.1-03M — 'Metadata refers to a machine-understandable reuse licence'"],"scored":true,"signal":null},{"key":"r_provenance_methods","label":"Provenance of the data","kind":"llm","weight":1.0,"fraction":1.0,"verdict":"yes","evidence":"We developed CryoDataBot","grounded":true,"rationale":"The tool (CryoDataBot) used to produce the data is named, along with specific software and parameters (e.g., CuPy, Python 3.10). [majority verdict 'yes' (4/5 passes agreed)]","anchors":["RDA-R1.2-01M — 'Metadata includes provenance information according to community- specific standa","FsF-R1.2-01M — F-UJI: 'Metadata includes provenance information about data creation or generati","W3C PROV-O (W3C Recommendation, 2013) — the entity/activity/agent model of provenance"],"scored":false,"signal":null},{"key":"r_documentation_codebook","label":"Documentation / codebook","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"Detailed metadata and a summary of the filtration process are provided in the supplementary tables.","grounded":true,"rationale":"Variable/file definitions are inside the article (supplementary tables), not shipped with the data. [majority verdict 'partial' (3/5 passes agreed)]","anchors":["RDA-R1-01M — '(Meta)data are richly described with a plurality of accurate and relevant attribu","FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'","NIH DMS Policy Element 3 (NOT-OD-21-014) — Standards (documentation and metadata to accompany t"],"scored":false,"signal":null},{"key":"r_versioning","label":"Snapshot identified","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No version token or date is given for the deposited dataset itself; only retrieval dates for the source data are stated. [majority verdict 'no' (3/5 passes agreed)]","anchors":["DataCite Metadata Schema 4.6 — the 'Version' property","RDA-R1.2-01M — provenance information (which version was used is provenance)","NSTC Desirable Characteristics of Data Repositories (2022) — 'Provenance', 'Retention Policy'"],"scored":true,"signal":null},{"key":"x_code_availability","label":"Analysis code available","kind":"llm","weight":1.0,"fraction":1.0,"verdict":"yes","evidence":"Project homepage: https://github.com/t00shadow/CryoDataBot","grounded":true,"rationale":"The study's code is available via a GitHub repository and a WorkflowHub DOI, both machine-resolvable locators.","anchors":["NIH DMS Policy Element 2 (NOT-OD-21-014) — 'Related Tools, Software and/or Code'","FAIR4RS Principles v1.0 (Chue Hong et al., 2022; RDA/FORCE11/ReSA) — FAIR Principles for Resear","FORCE11 Software Citation Principles (Smith, Katz & Niemeyer, 2016, PeerJ CS 2:e86)"],"scored":true,"signal":null},{"key":"x_funding_attribution","label":"Funder and award number","kind":"llm","weight":0.5,"fraction":1.0,"verdict":"yes","evidence":"R01GM071940","grounded":true,"rationale":"The paper provides specific grant numbers from the NIH and NSF.","anchors":["DataCite Metadata Schema 4.6 — 'FundingReference' property (funderName, funderIdentifier, award","Crossref Funder Registry — canonical funder identifiers for funding metadata","RDA-F2-01M — rich metadata provided to allow discovery (funding is part of the descriptive reco"],"scored":true,"signal":null}]}},"actions":[{"key":"r_reuse_license","dimension":"R","label":"Reuse licence","action":"Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No reuse licence or terms document is named for the deposited dataset; the CC-BY licence applies only to the article.","gain":16.67,"priority":"essential","scored":true},{"key":"f_repository_named","dimension":"F","label":"Named repository","action":"Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For structural biology data, deposit in the Protein Data Bank (PDB) or EMDB.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All data that support this study are available in GigaScience repository, GigaDB [37].","why":"GigaDB (GigaScience Database) is a named data repository. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","gain":8.33,"priority":"essential","scored":true},{"key":"a_data_openly_accessible","dimension":"A","label":"Access route free of preconditions","action":"Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For structural biology data, deposit in the Protein Data Bank (PDB) or EMDB.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All data that support this study are available in GigaScience repository, GigaDB [37].","why":"The statement points to a public repository with no precondition mentioned. [downgraded to 'partial' — no verifiable quote from the paper]","gain":8.33,"priority":"essential","scored":true},{"key":"i_open_nonproprietary_format","dimension":"I","label":"Open file format","action":"Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable. Prefer open structural biology formats such as mmCIF or MTZ.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No file format is named for the released data. [majority verdict 'no' (4/5 passes agreed)]","gain":8.33,"priority":"important","scored":true},{"key":"f_dataset_cited","dimension":"F","label":"Dataset formally cited","action":"Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the structural biology repository accession (e.g. from the Protein Data Bank (PDB) or EMDB) in the reference list.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"Xu Q, Wu L, Rebelo M, et al. Supporting data for “CryoDataBot: A Pipeline to Curate CryoEM Datasets for AI-Driven Structural Biology.” GigaScience Database. 2025. 10.5524/102765.","why":"The dataset appears as a reference-list entry (reference 37) with a DOI. [downgraded to 'partial' — no verifiable quote from the paper]","gain":4.17,"priority":"important","scored":true},{"key":"r_versioning","dimension":"R","label":"Snapshot identified","action":"Version the deposit and cite the exact version analysed (a version-specific DOI, or an accession with its version suffix). A reader reproducing your work against 'the current release' is reproducing it against a different dataset.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No version token or date is given for the deposited dataset itself; only retrieval dates for the source data are stated. [majority verdict 'no' (3/5 passes agreed)]","gain":4.17,"priority":"useful","scored":true},{"key":"f_data_availability_statement","dimension":"F","label":"Data-availability statement","action":"Replace the statement with the repository template: name the repository and give the accession or DOI (Colavizza category 3). This is the only DAS class associated with a measured citation advantage; 'available on reasonable request' and 'within the article' are not.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All data that support this study are available in GigaScience repository, GigaDB [37].","why":"The statement points to a repository record (GigaDB) with a reference entry, which is Colavizza category 3. [downgraded to 'partial' — no verifiable quote from the paper]","gain":0.0,"priority":"essential","scored":false},{"key":"f_discovery_metadata","dimension":"F","label":"Description of the dataset as an object","action":"Add a 'Data Records' section: itemise every file in the deposit and every variable or sample it holds, with counts and units. Describe the dataset as an object in its own right, not as a by-product of the findings — this is what makes it discoverable to someone who is not looking for your paper.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The entries of the cryoEM maps and their corresponding atomic models used in this study are listed in the supplementary tables.","why":"The dataset's content (the list of EMDB entries) is described in a sentence, but no itemised inventory of the deposited dataset's files or variables is given. [majority verdict 'partial' (3/5 passes agreed)]","gain":0.0,"priority":"essential","scored":false},{"key":"a_access_conditions_stated","dimension":"A","label":"Access level labelled","action":"State the access level in words, using the standard vocabulary: 'These data are open access' / 'These data are controlled access'. A reader — and a harvester — should not have to infer the access level from the presence of a download link.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"All data that support this study are available in GigaScience repository, GigaDB [37].","why":"The paper states where the data can be obtained but does not apply an explicit access-level label such as 'open access' or 'freely available'. [downgraded to 'no' — no verifiable quote from the paper]","gain":0.0,"priority":"important","scored":false},{"key":"i_community_standard_vocabulary","dimension":"I","label":"Community standard / vocabulary","action":"Adopt and NAME your domain's data standard — the minimum-information checklist, metadata schema, or ontology your community uses (MIAME/MINSEQE, ISA-Tab, BIDS, an OBO ontology, HL7 FHIR/OMOP) — and say which one you followed. A reporting checklist standardises your paper; it does nothing for your data. In structural biology, describe the data with mmCIF/PDBx.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No data or metadata community standard (e.g., MIAME, GO, BIDS) is named as being applied to the study's own dataset. [majority verdict 'no' (4/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"r_documentation_codebook","dimension":"R","label":"Documentation / codebook","action":"Ship a README and a data dictionary IN the deposit — every file, every variable, its units, its allowed values, its missing-value codes. It is the cheapest single thing that makes a dataset usable by someone who was not in the lab, and a table buried in the article does not travel with the data.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"Detailed metadata and a summary of the filtration process are provided in the supplementary tables.","why":"Variable/file definitions are inside the article (supplementary tables), not shipped with the data. [majority verdict 'partial' (3/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"a_controlled_access_for_sensitive","dimension":"A","label":"Gatekeeper for sensitive data","action":"Route sensitive data through an institutional gatekeeper — deposit in a controlled- access repository (dbGaP, EGA) with a Data Access Committee and a published DUA — rather than through the corresponding author's inbox. An author-gated dataset dies with the author's email address, and 'on reasonable request' has been shown repeatedly not to yield data.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The data are not human-subject or sensitive, and no gatekeeper of any kind is named; the data are openly available.","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No sentence in the paper states when the data become available (timing) or how long they persist (retention).","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For structural biology data, deposit in the Protein Data Bank (PDB) or EMDB.","Remove the precondition or justify it. Release the data at publication with no embargo, no registration wall, and no approval step — NIH's zero-embargo public- access rule (NOT-OD-25-101) has already made 'available at publication' the federal baseline for the article; the data should not lag behind it. For structural biology data, deposit in the Protein Data Bank (PDB) or EMDB.","Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable. Prefer open structural biology formats such as mmCIF or MTZ.","Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the structural biology repository accession (e.g. from the Protein Data Bank (PDB) or EMDB) in the reference list."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"epmc_xml"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"epmc_xml","fair_has_llm":true,"fair_computed_at":"2026-07-20T13:43:07.013410Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}