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At least 217 records · Page 12Linked to original sources
PubMed2003

The tissue microarray data exchange specification: a community-based, open source tool for sharing tissue microarray data.

BACKGROUND: Tissue Microarrays (TMAs) allow researchers to examine hundreds of small tissue samples on a single glass slide. The information held in a single TMA slide may easily involve Gigabytes of data. To benefit from TMA technology, the scientific community needs an open source TMA data exchange specification that will convey all of the data in a TMA experiment in a format that is understandable to both humans and computers. A data exchange specification for TMAs allows researchers to submit their data to journals and to public data repositories and to share or merge data from different laboratories. In May 2001, the Association of Pathology Informatics (API) hosted the first in a series of four workshops, co-sponsored by the National Cancer Institute, to develop an open, community-supported TMA data exchange specification. METHODS: A draft tissue microarray data exchange specification was developed through workshop meetings. The first workshop confirmed community support for the effort and urged the creation of an open XML-based specification. This was to evolve in steps with approval for each step coming from the stakeholders in the user community during open workshops. By the fourth workshop, held October, 2002, a set of Common Data Elements (CDEs) was established as well as a basic strategy for organizing TMA data in self-describing XML documents. RESULTS: The TMA data exchange specification is a well-formed XML document with four required sections: 1) Header, containing the specification Dublin Core identifiers, 2) Block, describing the paraffin-embedded array of tissues, 3)Slide, describing the glass slides produced from the Block, and 4) Core, containing all data related to the individual tissue samples contained in the array. Eighty CDEs, conforming to the ISO-11179 specification for data elements constitute XML tags used in the TMA data exchange specification. A set of six simple semantic rules describe the complete data exchange specification. Anyone using the data exchange specification can validate their TMA files using a software implementation written in Perl and distributed as a supplemental file with this publication. CONCLUSION: The TMA data exchange specification is now available in a draft form with community-approved Common Data Elements and a community-approved general file format and data structure. The specification can be freely used by the scientific community. Efforts sponsored by the Association for Pathology Informatics to refine the draft TMA data exchange specification are expected to continue for at least two more years. The interested public is invited to participate in these open efforts. Information on future workshops will be posted at http://www.pathologyinformatics.org (API we site).

Community Health Services↗
PubMed2004

A web-based federated neuroinformatics model for surgical planning and clinical research applications in epilepsy.

There is an increasing need to efficiently share diverse clinical and image data among different clinics, labs, and departments of a medical center enterprise to facilitate better quality care and more effective clinical research. In this paper, we describe a web-based, federated information model as a viable technical solution with applications in medical refractory epilepsy and other neurological disorders. We describe four such online applications developed in a federated system prototype: surgical planning, image analysis, statistical data analysis, and dynamic extraction, transforming, and loading (ETL) of data from a heterogeneous collection of data sources into an epilepsy multimedia data warehouse (EMDW). The federated information system adopts a three-tiered architecture, consisting of a user-interface layer, an application logic layer, and a data service layer. We implemented two complementary federated information technologies, i.e., XML (eXtensible Markup Language) and CORBA (Common Object Request Broker Architecture), in the prototype to enable multimedia data exchange and brain images transmission. The preliminary results show that the federated prototype system provides a uniform interface, heterogeneous information integration and efficient data sharing for users in our institution who are concerned with the care of patients with epilepsy and who pursue research in this area.

Animals↗
PubMed1993

HIPIN--a generic HIS/RIS-PACS interface based on clinical radiodiagnostic procedures.

Within the EurIPACS HIPIN topic a generic HIS/RIS-PACS interface will be designed, implemented and evaluated. It is generally agreed that integration with the HIS/RIS is essential for the acceptance of PACS in a clinical environment. An interface between HIS/RIS and PACS allows more efficient usage of both systems, better integration of data, better consistency checking on shared data and better security and error handling. Also the PACS performance is improved by using HIS/RIS information to steer the image migration within the PACS. In this paper the functional specifications of the interface are described. These specifications are based on descriptions of clinical radiodiagnostic procedures. The generic interface consists of a common part, and of site specific adapters. The common part is identical for all incarnations and performs message scheduling, processing and logging. The adapters are specific for each communication standard, e.g. ACR-NEMA or HL7, and for each hospital. The interface will be implemented at the radiology department of the Philipps University Hospital in Marburg (Germany) and at the orthopaedic and neuroradiology departments of the hospital of the Free University in Brussels (Belgium).

Computer Communication Networks↗
PubMed2004

An object model and database for functional genomics.

MOTIVATION: Large-scale functional genomics analysis is now feasible and presents significant challenges in data analysis, storage and querying. Data standards are required to enable the development of public data repositories and to improve data sharing. There is an established data format for microarrays (microarray gene expression markup language, MAGE-ML) and a draft standard for proteomics (PEDRo). We believe that all types of functional genomics experiments should be annotated in a consistent manner, and we hope to open up new ways of comparing multiple datasets used in functional genomics. RESULTS: We have created a functional genomics experiment object model (FGE-OM), developed from the microarray model, MAGE-OM and two models for proteomics, PEDRo and our own model (Gla-PSI-Glasgow Proposal for the Proteomics Standards Initiative). FGE-OM comprises three namespaces representing (i) the parts of the model common to all functional genomics experiments; (ii) microarray-specific components; and (iii) proteomics-specific components. We believe that FGE-OM should initiate discussion about the contents and structure of the next version of MAGE and the future of proteomics standards. A prototype database called RNA And Protein Abundance Database (RAPAD), based on FGE-OM, has been implemented and populated with data from microbial pathogenesis. AVAILABILITY: FGE-OM and the RAPAD schema are available from http://www.gusdb.org/fge.html, along with a set of more detailed diagrams. RAPAD can be accessed by registration at the site.

Abstracting and Indexing↗
PubMedDate not supplied

Capturing and using clinical outcome data: implications for information systems design.

There is an urgent need to capture and record data related to clinical outcomes, but there are many barriers. The range of problems includes lack of agreement on conceptualization of the term "outcome," inadequate measures of outcomes, and inadequate information systems to capture and manipulate data that would reflect outcomes. This article focuses on information system requirements to capture, store, and utilize clinical outcome data. For greatest accuracy, outcome data should be captured as close to the source as possible, including direct data capture from patients themselves and from their families. To make maximum use of outcome data, systems must be designed to 1) store data in multipurpose databases; 2) share data across different platforms; 3) link outcome data to other data that might influence or explain outcomes; 4) allow querying of the data by authorized personnel; and 5) protect patient confidentiality.

Decision Support Systems, Management↗
PubMed1998

Pitfalls in neuroepidemiologic research.

In neuroepidemiologic research, there are many pitfalls to trap unwary investigators, whether the project is a survey, a case-control study, or some other type of study. We briefly discuss pitfalls relating to: research preliminaries (e.g., failure to decide on study objectives); personnel and training (e.g., deficient training); data collection (e.g., ineffective supervision); data ownership and data sharing (disagreement about how the data will be used), and report preparation (e.g., failure to interpret results in the context of uncertainties arising from the design and implementation of the research). Awareness of these pitfalls will reduce the likelihood of flawed or ineffective neuroepidemiologic research.

Data Collection↗
PubMed2006

DNA separations.

The use of two types of commercialized microfluidic chips for separation of double-stranded DNA (dsDNA), suitable for personal scale and high throughput use, is described. Compared with conventional approaches such as slab-gel and capillary electrophoresis (CE), these devices offer the advantages of faster separation times, better data reproducibility, greater ease of use, labor savings in quantitative analysis, and ease in data archiving and data sharing owing to the digital data format. With some simple precautions taken in keeping bubbles and particulates out of the microchannels, Lab-on-a-Chip devices have been adopted by many researchers in molecular biology and genomics laboratories to increase their productivity.

DNA↗
PubMed2006

Protein separations.

This chapter describes the use of two types of commercialized microfluidic chips for protein separation, suitable for personal scale and high-throughput use. Compared with conventional approaches, such as sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and capillary electrophoresis (CE), these devices offer the advantages of faster separation times, better data reproducibility, greater ease of use, labor savings in quantitative analysis, and ease in data archiving and data sharing owing to the digital data format. With some simple precautions taken to keep bubbles and particulates out of the microchannels, Lab-on-a-Chip devices have been adopted by many researchers in protein processing, protein engineering, and proteomics research laboratories to increase their productivity.

Electrophoresis, Microchip↗
PubMed2006

Proposal for an essential nursing data set to evaluate the health in home care elderly persons.

This paper presents a proposal for a set of computerized data to construct an instrument in initial evaluations of the overall state of health elderly persons. The objective is to establish a common system of language and data-sharing, and to make the data collected available. This is expected to enable better planning and promotion of the quality of the assistance provided to this population.

Aged↗
PubMed1999

Computing 2010: from black holes to biology.

By 2010, a click on the PC on your desktop will suffice to call up instantly all the computing power you need from what by then will be the world's largest supercomputer, the Internet itself. Supercomputing for the masses will trigger a revolution in the complexity of problems that are tackled, whole disciplines will go digital and, rather than spending time collecting their own data, scientists will organize themselves around shared data sets.

Computers↗
PubMed2005

[Research advance on lake ecosystem dynamic models].

Starting with the role of system analysis in lake ecosystem research, this paper summarized the tentative procedures and softwares for studying the dynamics of lake ecosystem. There are several main stages in modeling the dynamics of lake ecosystem, namely, problems identification, mathematical formulation, computation, validation, sensitive analysis, calibration, and verification. In the modeling, selecting temporal and spatial scales is essential but complex. Since 1960s, a rapid progress has been made in modeling the dynamics of lake ecosystem, being developed from simple zero-dimension models to complex ecological-aquatic-hydrodynamic ones, among which, exergy was applied popularly as an objective function in modeling. In this paper, LakeWeb and LEEDS (Lake Eutrophication, Effect, Dose, and Sensitivity model) were analyzed as examples. In China, the development of lake ecosystem dynamic models could be traced back to 1980s, and most of them were focused on Lake Dianch, Lake Taihu, Lake Chaohu and Lake Donghu. Some softwares such as CE-QUAL-ICM, WASP, AQUATOX, PAMOLARE and CAEDYM were developed to simulate lake ecosystem dynamics, among which, CE-QUAL-ICM is more suitable for long and narrow water bodies. WASP consists of three parts, i. e., DYNHYD, EUTRO, and TOXI. AQUATOX is an ecological risk model, and the parameters are mainly calibrated in U. S. A, which has limited its further application in China. The software ECOPATH for simulating the energy flows in lakes was also described in this paper. There are still many shortages in the lake ecosystem dynamic models, e. g., the lack of sufficient monitoring data for validation, insufficient consideration of uncertainties and the role of bacteria, and inconsistent relationship with watershed changes. The uncertainties are mainly from the intrinsic uncertainties in aquatic ecosystem, in modeling, in parameters selection, and also in forecast and application. Setting up long-term monitoring and data sharing mechanism, using interpolation to make data more densely, introducing objective functions, dealing with uncertainties, and constructing watershed-lake ecosystem dynamic model could be the available ways for overcoming the shortages.

China↗
PubMed1991

Use of a microcomputer database system in a statewide effort for data collection in medical genetics.

The Genetics Office Automation System (GOAS) is a database management system for the collection and reporting of medical genetics data. We have previously reported on its implementation in a single university center [1,2]. We report here on its implementation in a coordinated data collection effort for the State of Missouri. We discuss the current status of the data collection activities and procedures to share data collected at an individual center with state, regional, and national data collection efforts.

Data Collection↗
PubMed2004

Perspectives on integrated child health information systems: parents, providers, and public health.

The efforts of families, health care providers, and public health programs to optimize health care and health outcomes for children are often limited by the lack of timely, complete, and accurate health information. Families frequently serve as the messenger between providers in providing clinical details that they may not understand, because the paper record of previous care is unavailable. Providers believe in the value of good information, but haven't the time, training, or financial resources to create better data sharing methods. Public health programs often must rely on unacceptably slow, redundant, or otherwise limited data collection efforts to provide population-based assessments of child health problems that inform public policy and program development. Integrated child health information systems allow the appropriate, secure sharing of health data that are critical to improving these processes. Developing such systems will require a strong commitment from these 3 stakeholder groups and attention to human values as well as technical challenges.

Attitude↗
PubMed1992

Case vignette: to share or not to share.

For years, the notion that researchers should share data freely with fellow scientists has been discussed widely. Some argue that this is especially true when the data are generated in federally funded projects. A recent provision in the reauthorization bill for the National Institutes of Health (NIH) would ensconce this principle in law. NIH grantees would be required, on demand, to furnish their data to other researchers. According to the proposed legislation, research data would have to be preserved and made avilable for 3 years after the completion of a project, and for 5 years following publication of the results in a scientific journal. One objective, according to a congressional aide, would be to make it easier for scientists with dissenting views to obtain and reanalyze data collected with public funds. It would also facilitate publication of alternative analyses. Personal records and patent applications would be exempted, but other data from clinical, behavioral, or epidemiological research focused on the evaluation or efficacy of a drug, medical device, or treatment of any sort would be covered immediately. Is such mandatory sharing of data ethical and appropriate scholarship? Does it raise potential for abuse? Should colleagues be required to provide such access to data, whether or not federal support was used in its collection?

Behavioral Research↗
PubMed2026

Individual Differences in Cognitive Aging Rodent Datasets (ID-CARD): A collaborative platform for behavioral analysis across the lifespan.

Understanding cognitive aging requires approaches that capture individual variability while enabling integration across studies. In rodent models, behavioral data are central to this effort, yet cross-laboratory differences in experimental design limit comparability and constrain secondary analysis. To address this gap, we developed the Individual Differences in Cognitive Aging Rodent Datasets (ID-CARD), a first-of-its-kind collaborative repository aggregating trial-level Morris water maze data from multiple laboratories. ID-CARD is designed to support large-scale, integrative analyses and to facilitate secondary use of existing behavioral data in alignment with emerging data-sharing and transparency initiatives. Rather than imposing retrospective harmonization of experimental protocols, we implemented a normalization and modeling framework that enables comparison of learning trajectories while preserving meaningful variation across studies. Behavioral data from > 5000 rats spanning common strains, both sexes, and multiple ages were normalized in training and performance domains and fit with a logarithmic function to derive an error accumulation rate coefficient (EARC) as a measure of spatial learning. Age was strongly associated with increased EARC, indicating attenuated learning, even after adjusting for non-spatial cue performance. Analyses of goodness of fit revealed systematic structure in learning dynamics, where age was associated with reduced learning-curve conformity after accounting for overall performance. Inter-individual variability in spatial learning also increased with age, with strain-specific interactions. These findings demonstrate that integrated analysis of heterogeneous behavioral datasets can yield robust, individual-level insights into cognitive aging. ID-CARD provides a scalable resource and analytic framework to advance discovery in behavioral neuroscience by enabling reuse, integration, and comparative analysis of existing data.

Cognitive aging↗
PubMed2026

Conference report: the third Bacterial Genome Sequencing Pan-European Network conference.

The third Bacterial Genome Sequencing Pan-European Network conference, held in Engelberg, Switzerland (12-15 January 2026), brought together experts from six European countries to discuss the implementation of bacterial genome sequencing in clinical microbiology and public health. Key themes included regulatory frameworks (In Vitro Diagnostic Regulation, General Data Protection Regulation), standardization, quality control, data sharing, economic evaluation, and the integration of artificial intelligence and long-read sequencing into diagnostic workflows. Across presentations, panel discussions, and workshops, participants emphasized that successful implementation of genome sequencing requires more than technical capacity: it depends on robust validation, sustainable funding, interoperable data standards, ethical governance, and interdisciplinary collaboration. The meeting highlighted that sequencing should remain question-driven and clinically meaningful, balancing cost, turnaround time, and public health impact. Overall, the conference reinforced the need for coordinated European efforts to advance responsible, standardized, and sustainable genomic surveillance and diagnostics.

bacterial genome sequencing↗
PubMedDate not supplied

Enhancing performance measurement: NCQA's road map for a health information framework. National Committee for Quality Assurance.

Measuring the quality of health care delivery is one of the most critical challenges facing US health care. Performance measurement can be used to track the quality of care that health plans and medical groups deliver, but effective performance measurement requires timely access to detailed and accurate data. In 1996, the National Committee for Quality Assurance (NCQA) commissioned a report to learn what actions would improve health plans' capacity to electronically report performance data for the Health Plan Employer Data and Information Set (HEDIS). Tracking clinical performance will require not just clinical data stored in information systems, but an integrated health information framework. Seven features are essential to this framework: (1) it specifies data elements; (2) it establishes linkage capability among data elements and records; (3) it standardizes the element definitions; (4) it is automated to the greatest possible extent; (5) it specifies procedures for continually assessing data quality; (6) it maintains strict controls for protecting security and confidentiality of the data; and (7) it specifies protocols for sharing data across institutions under appropriate and well-defined circumstances. Health plans should anticipate the use of computerized patient records and prepare their data management for an information framework by (1) expanding and improving the capture and use of currently available data; (2) creating an environment that rewards the automation of data; (3) improving the quality of currently automated data; (4) implementing national standards; (5) improving clinical data management practices; (6) establishing a clear commitment to protecting the confidentiality of enrollee information; and (7) careful capital planning. Health care purchasers can provide the impetus for implementing the information framework if they demand detailed, accurate data on the quality of care.

Forms and Records Control↗