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PubMed2002

Metadata tables to enable dynamic data modeling and web interface design: the SEER example.

A wealth of information addressing health status, outcomes and resource utilization is compiled and made available by various government agencies. While exploration of the data is possible using existing tools, in general, would-be users of the resources must acquire CD-ROMs or download data from the web, and upload the data into their own database. Where web interfaces exist, they are highly structured, limiting the kinds of queries that can be executed. This work develops a web-based database interface engine whose content and structure is generated through interaction with a metadata table. The result is a dynamically generated web interface that can easily accommodate changes in the underlying data model by altering the metadata table, rather than requiring changes to the interface code. This paper discusses the background and implementation of the metadata table and web-based front end and provides examples of its use with the NCI's Surveillance, Epidemiology and End-Results (SEER) database.

Databases, Factual↗

PubMedDate not supplied

Automated diagnosis of data-model conflicts using metadata.

The authors describe a methodology for helping computational biologists diagnose discrepancies they encounter between experimental data and the predictions of scientific models. The authors call these discrepancies data-model conflicts. They have built a prototype system to help scientists resolve these conflicts in a more systematic, evidence-based manner. In computational biology, data-model conflicts are the result of complex computations in which data and models are transformed and evaluated. Increasingly, the data, models, and tools employed in these computations come from diverse and distributed resources, contributing to a widening gap between the scientist and the original context in which these resources were produced. This contextual rift can contribute to the misuse of scientific data or tools and amplifies the problem of diagnosing data-model conflicts. The authors' hypothesis is that systematic collection of metadata about a computational process can help bridge the contextual rift and provide information for supporting automated diagnosis of these conflicts. The methodology involves three major steps. First, the authors decompose the data-model evaluation process into abstract functional components. Next, they use this process decomposition to enumerate the possible causes of the data-model conflict and direct the acquisition of diagnostically relevant metadata. Finally, they use evidence statically and dynamically generated from the metadata collected to identify the most likely causes of the given conflict. They describe how these methods are implemented in a knowledge-based system called GRENDEL and show how GRENDEL can be used to help diagnose conflicts between experimental data and computationally built structural models of the 30S ribosomal subunit.

Algorithms↗

PubMed1999

The low availability of metadata elements for evaluating the quality of medical information on the World Wide Web.

A great barrier to the use of Internet resources for patient education is the concern over the quality of information available. We conducted a study to determine what information was available in Web pages, both within text and metadata source code, that could be used in the assessment of information quality. Analysis of pages retrieved from 97 unique sites using a simple keyword search for "breast cancer treatment" on a generic and a health-specific search engine revealed that basic publishing elements were present in low frequency: authorship (20%), attribution/references (32%), disclosure (41%), and currency (35%). Only one page retrieved contained all four elements. Automated extraction of metadata elements from the source code of 822 pages retrieved from five popular generic search engines revealed even less information. We discuss the design of a metadata-based system for the evaluation of quality of medical content on the World Wide Web that addresses current limitations in ensuring quality.

Breast Neoplasms↗

PubMed2005

Developing metadata to organize public health datasets.

The Centers for Disease Control and Prevention (CDC) has available a large number of datasets from previous and current surveillance and research.1 Until now, these datasets have not been catalogued. Metadata would organize these datasets and enhance CDC's ability to efficiently use this data to quickly gain the broader view of the nation's health status to effectively carry out public health activities. This project was to develop metadata for cataloguing CDC datasets and a system that would allow researchers to search at least 95% of databases within CDC based on the most relevant criteria for research. It also explored the need to involve stakeholders and users in the project. The resulting metadata and system are available only to CDC researchers on the CDC intranet.

Cataloging↗

PubMed2026

MetaServe: a lightweight, metadata-aware governance and delivery layer for pre-publication research omics data.

BACKGROUND: Institutional research teams and core facilities routinely manage pre-publication omics datasets that span heterogeneous file types, nested project structures, and multiple downstream uses. Public repositories mainly support post-publication dissemination, while workflow systems and enterprise data platforms do not directly provide a lightweight governance and delivery layer for internal research assets. RESULTS: We present MetaServe, an open-source governance and delivery layer for pre-publication research assets in institutional multi-omics settings. MetaServe registers and delivers heterogeneous assets, including sequencing files, processed matrices, imaging data, analysis-ready objects, tabular files, and documents, without requiring repository-grade standardization. Its metadata-aware design combines file-type recognition, partial automatic extraction for selected formats, manually supplied project and biological annotations, and indexed faceted retrieval. MetaServe supports authenticated web download, viewer-oriented handoff for compatible services such as cellxgene, and path-manifest export for downstream workflows under shared-storage assumptions. The current implementation combines role-based controls, explicit file-level sharing, path-constrained delivery, and operational traceability to support controlled institutional access. MetaServe has been deployed at the Chinese Institutes for Medical Research (CIMR) as part of an institutional multi-omics data-management system. CONCLUSIONS: MetaServe provides a practical layer between institutional storage and downstream analytical platforms for pre-publication research data. Its contribution is the integration of lightweight metadata-aware registration, permission-aware retrieval, and controlled delivery for heterogeneous institutional omics assets. Rather than replacing workflow engines, public repositories, or enterprise-scale research data platforms, MetaServe offers a deployable governance layer for core facilities and collaborative teams that need structured discovery and traceable delivery before public deposition or manuscript release.

Metadata↗

PubMed2005

Metadata-driven Delphi rating on the Internet.

Paper-based data collection and analysis for consensus development is inefficient and error-prone. Computerized techniques that could improve efficiency, however, have been criticized as costly, inconvenient and difficult to use. We designed and implemented a metadata-driven Web-based Delphi rating and analysis tool, employing the flexible entity-attribute-value schema to create generic, reusable software. The software can be applied to various domains by altering the metadata; the programming code remains intact. This approach greatly reduces the marginal cost of re-using the software. We implemented our software to prepare for the Conference on Guidelines Standardization. Twenty-three invited experts completed the first round of the Delphi rating on the Web. For each participant, the software generated individualized reports that described the median rating and the disagreement index (calculated from the Interpercentile Range Adjusted for Symmetry) as defined by the RAND/UCLA Appropriateness Method. We evaluated the software with a satisfaction survey using a five-level Likert scale. The panelists felt that Web data entry was convenient (median 4, interquartile range [IQR] 4.0-5.0), acceptable (median 4.5, IQR 4.0-5.0) and easily accessible (median 5, IQR 4.0-5.0). We conclude that Web-based Delphi rating for consensus development is a convenient and acceptable alternative to the traditional paper-based method.

Delphi Technique↗

PubMed2005

Creating and using the urgent metadata catalogue and thesaurus.

The Urban Regeneration and the Environment Research Programme (URGENT) required a system for cataloguing its datasets and enabling its scientific community to discover what data were available to it. This community was multidisciplinary in nature and therefore needed a range of facilities for searching. Of particular importance were facilities to help those unfamiliar with specialist terminology. To meet these needs, four applications were designed and developed: a Metadata Capture Tool for describing datasets in compliance with the National Geospatial Data Framework (NGDF) standard, a Term Entry Tool for creating an ISO compliant thesaurus, a Thesaurus Builder for merging thesauri and a Search Tool. To encourage users to help in cataloguing data, the capture tools were written as stand alone applications, which users could keep and use to build their own metadatabases. The tools contained export and import facilities that allowed the URGENT Data Centre to build a central database and publish it upon the web. During the development work, it was found necessary to extend the NGDF standard as it could not adequately describe time variant or 3-D atmospheric datasets. The four applications met their design objectives. However, a number of ergonomic issues will need to be addressed if the system is to meet the needs of the much larger up coming programmes. The main challenges will be moving from the NGDF standard to the ISO standard, hence bringing the work into line with the recommendations of the INSPIRE Project, and merging the metadatabase with the scientific database, which enable metadata maintenance to be semi-automated.

Cataloging↗

PubMed2002

Metadata-driven creation of data marts from an EAV-modeled clinical research database.

Generic clinical study data management systems can record data on an arbitrary number of parameters in an arbitrary number of clinical studies without requiring modification of the database schema. They achieve this by using an Entity-Attribute-Value (EAV) model for clinical data. While very flexible for creating transaction-oriented systems for data entry and browsing of individual forms, EAV-modeled data is unsuitable for direct analytical processing, which is the focus of data marts. For this purpose, such data must be extracted and restructured appropriately. This paper describes how such a process, which is non-trivial and highly error prone if performed using non-systematic approaches, can be automated by judicious use of the study metadata-the descriptions of measured parameters and their higher-level grouping. The metadata, in addition to driving the process, is exported along with the data, in order to facilitate its human interpretation.

Breast Neoplasms↗

PubMed1998

A metadata approach to query interoperation between molecular biology databases.

MOTIVATION: Molecular biology databases have been proliferating rapidly. Their heterogeneity and complexity pose a great challenge to efforts in database interoperation. To minimize the efforts of interoperating heterogeneous databases, it is useful to develop a system that lets a user of a particular genomic database access another related database as if the latter is structurally similar to the former. RESULTS: We extend a structurally simple model-the entity-attribute-value (EAV) model-to describe uniformly metadata relating to individual databases. Such metadata, which are necessary for performing database comparisons, include descriptions of primitive database objects (including entities, attributes, domain values and entity relationships) and specification of correspondences among the database objects. We show how to decompose SQL queries and map them from one database to another based on the EAV representation of the basic database objects. A prototype system is implemented to demonstrate query interoperation between two chromosome map databases. AVAILABILITY: Freely available (Cold Fusion source code and an Access database containing the mapping knowledge) upon request from the author. CONTACT: kei.cheung@yale.edu

Chromosome Mapping↗

PubMed2003

Classifying the precancers: a metadata approach.

BACKGROUND: During carcinogenesis, precancers are the morphologically identifiable lesions that precede invasive cancers. In theory, the successful treatment of precancers would result in the eradication of most human cancers. Despite the importance of these lesions, there has been no effort to list and classify all of the precancers. The purpose of this study is to describe the first comprehensive taxonomy and classification of the precancers. As a novel approach to disease classification, terms and classes were annotated with metadata (data that describes the data) so that the classification could be used to link precancer terms to data elements in other biological databases. METHODS: Terms in the UMLS (Unified Medical Language System) related to precancers were extracted. Extracted terms were reviewed and additional terms added. Each precancer was assigned one of six general classes. The entire classification was assembled as an XML (eXtensible Mark-up Language) file. A Perl script converted the XML file into a browser-viewable HTML (HyperText Mark-up Language) file. RESULTS: The classification contained 4700 precancer terms, 568 distinct precancer concepts and six precancer classes: 1) Acquired microscopic precancers; 2) acquired large lesions with microscopic atypia; 3) Precursor lesions occurring with inherited hyperplastic syndromes that progress to cancer; 4) Acquired diffuse hyperplasias and diffuse metaplasias; 5) Currently unclassified entities; and 6) Superclass and modifiers. CONCLUSION: This work represents the first attempt to create a comprehensive listing of the precancers, the first attempt to classify precancers by their biological properties and the first attempt to create a pathologic classification of precancers using standard metadata (XML). The classification is placed in the public domain, and comment is invited by the authors, who are prepared to curate and modify the classification.

Decision Support Systems, Clinical↗

PubMed2026

The SARS-CoV-2 Integrated Genomic Epidemiology Database (IGED): Linking viral genomes with patient-level metadata to advance statewide genomic surveillance in California.

In July 2021, the California Code of Regulations Title 17 required all laboratories performing SARS‑CoV‑2 whole genome sequencing (WGS) to report their sequencing results to the California Department of Public Health (CDPH). These viral genomic data and patient metadata were compiled into the Integrated Genomic Epidemiology Database (IGED). Linking anonymized viral sequences with patient‑level information enabled monitoring of infectiousness, pathogenicity, transmission dynamics, evolution, and vaccine evasion among emerging SARS‑CoV‑2 lineages. Laboratories performing SARS-CoV-2 WGS transmitted sequencing results to CDPH through Electronic Laboratory Reporting (ELR) and non-ELR pathways. CDPH applied uniform reporting requirements but allowed flexibility in specific data formats to accommodate diverse data systems. To preserve data quality and interoperability across heterogeneous sources, CDPH implemented standardization, validation, and deduplication protocols. Snowflake, a cloud‑based data storage and analytics platform, and Posit Connect, a cloud deployment and automation platform, supported the management, processing, and integration of data within the IGED. The IGED established links between SARS‑CoV‑2 WGS data and epidemiologic metadata for 801,418 sequences, representing 81.7% of all sequences reported in California. Lineages reported to the IGED showed strong concordance with lineage proportions in GISAID. Sequences reported to the IGED had average turnaround times longer than one month, and the majority of sequencing was performed in Southern California and Los Angeles. The IGED enhanced genomic surveillance through predictive modeling and monitoring concerning evolutionary trends such as recombination and saltations in persistent infections. Development of the IGED highlighted the need for standardized data requirements, sustained funding for sequencing, incentives for data submission, and interdisciplinary collaboration to build an effective genomic surveillance system. This framework for linking genomic and epidemiologic data has not only generated critical insights for SARS‑CoV‑2 but also provided the foundation for CDPH and other public health organizations to develop similar IGED‑like systems for other priority pathogens as genomic surveillance expands.

Journal Article↗

PubMed2001

A metadata vocabulary for self- and third-party labeling of health web-sites: Health Information Disclosure, Description and Evaluation Language (HIDDEL).

We describe HIDDEL (Health Information Disclosure, Description and Evaluation Language), formerly known as medPICS (platform for Internet content selection in medicine), a metadata vocabulary designed to enhance transparency, trust and quality of health information on the web. The vocabulary may be used (1) by webmasters to self-describe their contents and policies; (2) by infomediaries (e.g. Healthfinder, NHS Direct/NeLH), e.g. third party evaluators, rating or portal services, to annotate other websites; (3) and by users, to describe their preferences. As an XML application it conforms to the W3C's RDF Specification. The metadata vocabulary is primarily intended to enable descriptions of whole health websites or health information providers. The vocabulary is designed to provide a computer-readable electronic "label" of a health website, telling users who is behind the website, how the website is sponsored, what the con-tent, aim and target audience is, how the information was compiled, what risks the service bears, or what people say about the resource. Client-software can "read" this label automatically, compare it to the user s own set of preferences and needs, and alert and advise users.

Information Services↗

PubMed2003

Developing a metadata data model for the National Health and Nutrition Examination Survey (NHANES).

The National Health and Nutrition Examination Survey (NHANES), developed by the Centers for Disease Control and Prevention (CDC), is a large and comprehensive health survey utilizing leading edge technologies to produce national estimates of health measures and the nutritional status of the U.S. population. Early NHANES metadata models grouped data by categories with little specificity and often not capturing the complexity of the survey. Subsequently, existing models at the Census Bureau, CDC, and the EPA were evaluated in addition to industry standards, such as DDI, Dublin Core, and ISO 1179. For the NHANES metadata model, the DDI standard and CDC Public Health Conceptual Model were chosen as the backbone for constructing the data model. The new model has led to increased data accuracy and several value-added products for producing codebooks, automatically checking questionnaire skip patterns, and producing questionnaire instrumentation.

Catalogs as Topic↗

PubMed2006

Use of metadata registry for nursing: A customer-centered electronic health record.

An online metadata registry promotes cross-system and cross-organization descriptions of common units of health data. Nurses must have a method to share health information and transmit nursing data. Health information sharing through an online metadata registry allows nurses, health administrators, and hospital systems to make significant strides towards improving customer-centered electronic health records, patient safety, reducing errors, lowering healthcare costs, and strengthening public health and disaster preparedness initiatives.

Medical Records Systems, Computerized↗

PubMed2026

An integrated global resource of wetland microbiomes linking environmental metadata, community profiles, and genome-resolved metabolic traits.

Wetlands are biogeochemical hotspots pivotal to global carbon and nutrient cycling, yet genome-resolved studies across diverse wetland types remain limited. To address this, we constructed a global wetland metagenomic dataset, integrating environmental metadata, community profiles, and genome-resolved metabolic traits. This dataset comprises 1,962 samples-including 129 newly sequenced field-collected samples-from lakes, rivers, paddies, marshes, and coastal wetlands, spanning water, soil, and sediment habitats. We generated comprehensive taxonomic profiles for all 1,962 samples, and used 251 samples to reconstruct 5,704 sample-specific metagenome-assembled genomes (MAGs). These MAGs were subsequently dereplicated to establish a normalized, non-redundant catalog of 4,164 representative genomes. We further mapped gene repertoires to 549 KEGG modules to decode the metabolic potential of all 5,704 MAGs. This dataset depicts an overview of microbial genomic diversity across global wetlands and provides a comprehensive resource for understanding the metabolic capabilities, ecology, and evolution of wetland microbiomes.

Wetlands↗

PubMed1990

Metadata-based generation and management of knowledgebases from molecular biological databases.

Present-day knowledge-based systems (or expert systems) and databases constitute 'islands of computing' with little or no connection to each other. The use of software to provide a communication channel between the two, and to integrate their separate functions, is particularly attractive in certain data-rich domains where there are already pre-existing database systems containing the data required by the relevant knowledge-based system. Our evolving program, GENPRO, provides such a communication channel. The original methodology has been extended to provide interactive Prolog clause input with syntactic and semantic verification. This enables automatic generation of clauses from the source database, together with complete management of subsequent interfacing to the specified knowledge-based system. The particular data-rich domain used in this paper is protein structure, where processes which require reasoning (modelled by knowledge-based systems), such as the inference of protein topology, protein model-building and protein structure prediction, often require large amounts of raw data (i.e., facts about particular proteins) in the form of logic programming ground clauses. These are generated in the proper format by use of the concept of metadata.

Artificial Intelligence↗

PubMed1999

Metadata and computer-based patient records.

"Metadata" is the fundamental set of items in the organization of health-care information, at least in computer-based patient records. Computer-based patient records remain controversial, and thus, to a considerable extent, the truth of all assertions about these areas remains a matter of opinion. A set of opinions generated during 5 years of exclusive and intense work is presented.

Humans↗

PubMed1997

QAV: querying entity-attribute-value metadata in a biomedical database.

Entity-attribute-value (EAV) data organization is increasingly used for knowledge representation for complex heterogeneous biomedical databases. When delivered in relation form for production applications the simplicity of EAV storage is offset by difficulty of set-based data retrieval. We describe a client-server application, QAV, that is designed to perform set-based query on the Columbia MED dataset, a large medical metadata repository that has been the focus of much research. QAV interacts with the user through a graphical front end and generates a series of SQL statements that are sent to the server for the actual data retrieval.

Algorithms↗