[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-seo-195013-105":53,"doc-detail-195013-en":126},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":54,"data":55},"ok",{"site_id":56,"language":57,"slug":58,"title":59,"keywords":60,"description":61,"schema_data":62,"social_meta":119,"head_meta":121,"extra_data":123,"updated_unix":125},105,"en","document-metadata-extraction-multimodal-195013","Document Metadata Extraction (Multimodal)","","This document explores the critical role of metadata in enhancing the understandability and usability of datasets, particularly within the context of AI/ML and cultural heritage (CH). It critically evaluates various approaches to data documentation, including traditional datasheets, data cards, open datasheets, and a proposed \"Data-Envelope\" model. The Data-Envelope model is presented as a superior framework, emphasizing modularity, machine readability, comprehensive provenance tracking, clear target audience definition, adherence to FAIR principles, and explicit consideration of creator and annotator positionality. The document highlights the importance of contextual information, visualized along a spectrum from less to more, indicating that richer metadata empowers users more effectively. It details a 5-level hierarchy of metadata, starting from basic information and progressing to human perspectives, underscoring the multifaceted nature of effective data documentation for research and application.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":51,"@type":70,"position":76},"https://docshare.wps.com/template/general/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/document-metadata-extraction-multimodal-195013/195013/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/document-metadata-extraction-multimodal-195013/195013.png","ImageObject",442,249,{"name":88,"@type":89},"Ivy","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-02","2026-09-03",true,{"@type":98,"interactionType":99,"userInteractionCount":76},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"What is a Data-Envelope and why is it important?","Question",{"text":108,"@type":109},"A Data-Envelope is a proposed modular framework for data documentation that comprehensively covers aspects like structure, machine readability, provenance, target audience, FAIR principles adherence, and positionality, aiming to significantly improve data usability and understandability.","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"How do different data documentation approaches vary in machine readability and provenance?",{"text":113,"@type":109},"While traditional datasheets may not prioritize machine readability, the Data-Envelope and Open Datasheets are designed for full machine support. The Data-Envelope also extensively covers provenance, which is not as explicitly or sufficiently considered in other formats.",{"name":115,"@type":106,"acceptedAnswer":116},"What are the five levels of metadata described in the document?",{"text":117,"@type":109},"The five levels of metadata are: Level 1: Basic Information, Level 2: Basic Dataset Metadata, Level 3: Data (Content and Context), Level 4: Uses, and Level 5: Human Perspective.","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},195013,1790143748,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":50,"category_name":51,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":76,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":20,"language":135,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":136,"faqs":137,"seo_title":138,"seo_description":61,"update_tm":139,"read_time":47},549758252649,"https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819","| Parameter | Datasheets | Data Cards | Open\u003Cbr>Datasheets | Datasheets for DCH | Data-Envelope |\n| --- | --- | --- | --- | --- | --- |\n| Structure | Questionnaire format | Structured\u003Cbr>Summaries | JSON-based metadata | Tailored\u003Cbr>for DCH data | Modular with detailed sections |\n| Machine Readability | Not primary focus |  | Yes, fully\u003Cbr>supported | Not primary focus | Yes, Designed for machine readability |\n| Provenance | Not explicitly/sufficiently considered |  |  |  | Extensively covered |\n| Target Audience | ML/AI researchers |  |  | ML/AI researchers, CH Institutions | CH Institutions, ML community, legal institutions, broader public |\n| FAIR | Not directly addressed |  |  |  | Designed with FAIR in mind, with specific section devoted to datasets’ adherence\u003Cbr>to FAIR principles |\n| Positionality | Not emphasized, only mentioned for annotators |  |  |  | Explicit focus on creators,\u003Cbr>contributors, annotators’ positionality |","cbCaimdlrXyjnGmA","https://ap.wps.com/l/cbCaimdlrXyjnGmA","pdf",462438,"English","# Document Metadata Concepts\n## Data Documentation Approaches\n### Datasheets\n### Data Cards\n### Open Datasheets\n### Datasheets for DCH\n### Data-Envelope\n## Levels of Metadata","[{\"question\":\"What is a Data-Envelope and why is it important?\",\"answer\":\"A Data-Envelope is a proposed modular framework for data documentation that comprehensively covers aspects like structure, machine readability, provenance, target audience, FAIR principles adherence, and positionality, aiming to significantly improve data usability and understandability.\"},{\"question\":\"How do different data documentation approaches vary in machine readability and provenance?\",\"answer\":\"While traditional datasheets may not prioritize machine readability, the Data-Envelope and Open Datasheets are designed for full machine support. The Data-Envelope also extensively covers provenance, which is not as explicitly or sufficiently considered in other formats.\"},{\"question\":\"What are the five levels of metadata described in the document?\",\"answer\":\"The five levels of metadata are: Level 1: Basic Information, Level 2: Basic Dataset Metadata, Level 3: Data (Content and Context), Level 4: Uses, and Level 5: Human Perspective.\"}]","Document Metadata Extraction (Multimodal) | PDF",1788444694]