{"doi":"10.1016/j.mcpro.2025.101089","title":"Glycoprotein-Notebook: A Pan-Cancer Glycoproteomic Database and Toolkit for Analysis of Protein Glycosylation Changes Associated With Cancer Phenotypes","abstract":"Protein glycosylation plays a pivotal role in various biological processes, and the analysis of intact glycopeptides (IGPs) has emerged as a powerful approach for characterizing alterations in protein glycosylation associated with diseases. Despite the critical insights gained from IGP analysis, dedicated databases and specialized tools for comprehensive glycoproteomics remain scarce. In response to this deficiency, we developed \"Glycoprotein-Notebook,\" an online resource that consolidates the mass spectrometry evidence for IGPs identified from pan-cancer types studied in the Clinical Proteomic Tumor Analysis Consortium projects and provides analytical tools for in-depth glycopeptide characterization. Using pancreatic ductal adenocarcinoma as a case study, we validated and showcased the toolkit's analytical capabilities. Our results underscore the promise of IGPs as cancer-specific diagnostic and therapeutic targets. Accordingly, Glycoprotein-Notebook emerges as a valuable resource for cancer researchers exploring the intricate relationship between protein glycosylation and cancer phenotypes.","journal":"Molecular & Cellular Proteomics","year":2025,"id":535067,"datarank":0.16946783618494624,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.00467599288472979,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.00467599288472979,"corpus_percentile":32.89239576081071,"corpus_rank":8676,"citation_count":2,"citer_count":2,"citers_with_citation_signal":1,"citers_with_endowment":1,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8825,"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":54.1667,"fair_percentile":68.66401712014674,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":636283,"name":"Trung Hoàng","orcid":"0009-0004-4068-9065","position":1,"is_corresponding":false},{"id":51811,"name":"Yingwei Hu","orcid":"0000-0002-4629-0985","position":2,"is_corresponding":false},{"id":225711,"name":"Hui Zhang","orcid":"0000-0001-5793-8890","position":0,"is_corresponding":true}],"reference_count":57,"raw_metadata":null,"created_at":"2026-07-19T02:51:52.019261Z","pmid":"41093273","pmcid":"PMC12681939","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":72.2222,"fair_a":62.5,"fair_i":0.0,"fair_r":25.0,"fair_zscore":0.7804,"fair_rationale":{"fair_score":54.17,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":72.22,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"All processed data tables and precomputed results are stored at Zenodo ( https://zenodo.org/records/14019975 ).","grounded":true,"rationale":"The paper gives a web URL (https://zenodo.org/records/14019975) for the data, not a PID-scheme string (DOI, Handle, ARK, or repository accession). [majority verdict 'partial' (3/5 passes agreed)]","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":1.0,"verdict":"yes","evidence":"All processed data tables and precomputed results are stored at Zenodo ( https://zenodo.org/records/14019975 ).","grounded":true,"rationale":"Zenodo is a named repository that is listed in re3data and issues DOIs, fulfilling the 'yes' criterion.","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":1.0,"verdict":"yes","evidence":"All processed data tables and precomputed results are stored at Zenodo ( https://zenodo.org/records/14019975 ).","grounded":true,"rationale":"The data availability statement points to a repository record (Zenodo) with a persistent link, falling under Colavizza category 3.","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":"We identified 432,750 N-linked IGPs (sequence + glycan), 408,728 glycoforms, 26,277 glycosites, and 11,641 glycoproteins from the 10 cancer types, all under a glycopeptide-spectrum match FDR threshold of 0.01.","grounded":true,"rationale":"The dataset's content and size are described in running prose without an itemised inventory (section, table, or list) in the paper body. [majority verdict 'partial' (4/5 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":"All processed data tables and precomputed results are stored at Zenodo ( https://zenodo.org/records/14019975 ).","grounded":true,"rationale":"The dataset identifier appears only in the body text (Data Availability section), not as a reference-list entry. [majority verdict 'partial' (4/5 passes agreed)]","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":62.5,"criteria":[{"key":"a_data_openly_accessible","label":"Access route free of preconditions","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"All processed data tables and precomputed results are stored at Zenodo ( https://zenodo.org/records/14019975 ).","grounded":true,"rationale":"The paper states the data are stored at a public repository with no stated precondition (embargo, registration, or application). [majority verdict 'yes' (4/5 passes agreed)]","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":0.5,"verdict":"partial","evidence":"All processed data tables and precomputed results are stored at Zenodo ( https://zenodo.org/records/14019975 ).","grounded":true,"rationale":"The paper describes where data can be downloaded but does not label the access level with an explicit term such as 'open access' or 'freely available'. [majority verdict 'partial' (3/5 passes agreed)]","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 from human subjects (CPTAC) but deposited in open repositories with no gatekeeper or access procedure mentioned.","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":"The paper states neither how long the data will remain available nor any persistence commitment. [majority verdict 'no' (3/5 passes agreed)]","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":0.0,"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 token (open or proprietary) is named for the released data in the main text or supplementary materials.","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., MIAPE, MIAME, ontology) is named as applied to the data. The paper uses KEGG and GO for analysis but not as a standard for the data itself.","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":0.0,"verdict":"no","evidence":"Zeng W.-F., et al. Precise, fast and comprehensive analysis of intact glycopeptides and modified glycans with pGlyco3. Nat. Methods. 2021;18:1515–1523. doi: 10.1038/s41592-021-01306-0.","grounded":false,"rationale":"The paper cites external resources (e.g., pGlyco3) with DOIs in the reference list, providing identifiers for resources the data depend on. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (4/5 passes agreed)]","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":25.0,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No license or reuse terms are stated for the data. The CC BY license on the article does not apply to the data.","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":0.5,"verdict":"partial","evidence":"GPQuest 3.0 (Zhang Lab) (32, 33, 34).","grounded":false,"rationale":"The paper names specific software (GPQuest 3.0) and instruments used to produce the data, providing a proper-noun production record. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 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":0.0,"verdict":"no","evidence":"Statistics on identified glycopeptides and corresponding glycoproteins are summarized in Supplementary Table S1.","grounded":false,"rationale":"Variable definitions are provided inside the article (supplementary table), not as a separate documentation object shipped with the data. [downgraded to 'no' — no verifiable quote from the paper]","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":"Neither a version token nor a date is given for the dataset. The Zenodo record URL implies a specific version, but the paper does not explicitly state it. [majority verdict 'no' (4/5 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":0.5,"verdict":"partial","evidence":"Users can utilize access and run the Jupyter notebooks available in the Glycoprotein-Notebook GitHub repository ( https://github.com/huizhanglab-jhu/glycoproteinnotebook ).","grounded":false,"rationale":"The paper provides a machine-resolvable URL to a code repository (GitHub), fulfilling the 'yes' criterion. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","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":"This work was supported by the National Cancer Institute Clinical Proteomic Tumor Analysis Consortium, National Institutes of Health grant U24CA271079.","grounded":true,"rationale":"The paper includes a specific grant number (U24CA271079) attached to a named funder.","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 license or reuse terms are stated for the data. The CC BY license on the article does not apply to the data.","gain":16.67,"priority":"essential","scored":true},{"key":"f_dataset_pid","dimension":"F","label":"Persistent identifier for the data","action":"Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For proteomics data, deposit in PRIDE (PXD accession) or ProteomeXchange.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All processed data tables and precomputed results are stored at Zenodo ( https://zenodo.org/records/14019975 ).","why":"The paper gives a web URL (https://zenodo.org/records/14019975) for the data, not a PID-scheme string (DOI, Handle, ARK, or repository accession). [majority verdict 'partial' (3/5 passes agreed)]","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 proteomics formats such as mzML or mzIdentML.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No file format token (open or proprietary) is named for the released data in the main text or supplementary materials.","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 proteomics repository accession (e.g. from PRIDE (PXD accession) or ProteomeXchange) in the reference list.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"All processed data tables and precomputed results are stored at Zenodo ( https://zenodo.org/records/14019975 ).","why":"The dataset identifier appears only in the body text (Data Availability section), not as a reference-list entry. [majority verdict 'partial' (4/5 passes agreed)]","gain":4.17,"priority":"important","scored":true},{"key":"x_code_availability","dimension":"R","label":"Analysis code available","action":"Publish the analysis code in a public forge, archive a tagged release with a DOI (Zenodo/Software Heritage), and cite that DOI in the paper. NIH DMS Element 2 asks for the tools and code, not only the data — and 'available on request' is not a locator. Archive the analysis code in a versioned repository (GitHub + a Zenodo release DOI).","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"Users can utilize access and run the Jupyter notebooks available in the Glycoprotein-Notebook GitHub repository ( https://github.com/huizhanglab-jhu/glycoproteinnotebook ).","why":"The paper provides a machine-resolvable URL to a code repository (GitHub), fulfilling the 'yes' criterion. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","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":"Neither a version token nor a date is given for the dataset. The Zenodo record URL implies a specific version, but the paper does not explicitly state it. [majority verdict 'no' (4/5 passes agreed)]","gain":4.17,"priority":"useful","scored":true},{"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":"We identified 432,750 N-linked IGPs (sequence + glycan), 408,728 glycoforms, 26,277 glycosites, and 11,641 glycoproteins from the 10 cancer types, all under a glycopeptide-spectrum match FDR threshold of 0.01.","why":"The dataset's content and size are described in running prose without an itemised inventory (section, table, or list) in the paper body. [majority verdict 'partial' (4/5 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":"partial","current":0.5,"evidence":"All processed data tables and precomputed results are stored at Zenodo ( https://zenodo.org/records/14019975 ).","why":"The paper describes where data can be downloaded but does not label the access level with an explicit term such as 'open access' or 'freely available'. [majority verdict 'partial' (3/5 passes agreed)]","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 proteomics, describe the data with mzML or MIAPE.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No data or metadata community standard (e.g., MIAPE, MIAME, ontology) is named as applied to the data. The paper uses KEGG and GO for analysis but not as a standard for the data itself.","gain":0.0,"priority":"important","scored":false},{"key":"r_provenance_methods","dimension":"R","label":"Provenance of the data","action":"Name the instruments, kits, and software — with versions — that produced the data, not just the verbs. 'Reads were aligned' is not provenance; 'aligned with STAR v2.7.9a to GRCh38' is, because someone else can rerun it.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"GPQuest 3.0 (Zhang Lab) (32, 33, 34).","why":"The paper names specific software (GPQuest 3.0) and instruments used to produce the data, providing a proper-noun production record. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 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":"no","current":0.0,"evidence":"Statistics on identified glycopeptides and corresponding glycoproteins are summarized in Supplementary Table S1.","why":"Variable definitions are provided inside the article (supplementary table), not as a separate documentation object shipped with the data. [downgraded to 'no' — no verifiable quote from the paper]","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 from human subjects (CPTAC) but deposited in open repositories with no gatekeeper or access procedure mentioned.","gain":0.0,"priority":"useful","scored":false},{"key":"i_qualified_references","dimension":"I","label":"Identifiers for the resources the data depend on","action":"Cite by identifier every resource the data depend on — the source datasets' accessions, the reference build (GRCh38 / GCA_000001405.28), the cohort application number, the code DOI — and register those relations on the dataset record (IsDerivedFrom, IsSupplementTo). A name is not a link: it cannot be resolved, versioned, or followed by a machine.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"Zeng W.-F., et al. Precise, fast and comprehensive analysis of intact glycopeptides and modified glycans with pGlyco3. Nat. Methods. 2021;18:1515–1523. doi: 10.1038/s41592-021-01306-0.","why":"The paper cites external resources (e.g., pGlyco3) with DOIs in the reference list, providing identifiers for resources the data depend on. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (4/5 passes agreed)]","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":"The paper states neither how long the data will remain available nor any persistence commitment. [majority verdict 'no' (3/5 passes agreed)]","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.","Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For proteomics data, deposit in PRIDE (PXD accession) or ProteomeXchange.","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 proteomics formats such as mzML or mzIdentML.","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 proteomics repository accession (e.g. from PRIDE (PXD accession) or ProteomeXchange) in the reference list.","Publish the analysis code in a public forge, archive a tagged release with a DOI (Zenodo/Software Heritage), and cite that DOI in the paper. NIH DMS Element 2 asks for the tools and code, not only the data — and 'available on request' is not a locator. Archive the analysis code in a versioned repository (GitHub + a Zenodo release DOI)."],"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":"2026-07-20T13:30:43.711800Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}