Semantic Standards Research Articles

Bioinformatics and crop information systems in rice research

The triple revolution in biotechnology, computing science, and communication technology has stimulated informatics applications in rice research. This review specifically covers the impact of biology-focused informatics (bioinformatics) in rice research on the discovery of genotype-phenotype relationships for priority traits, using diverse data sources. Bioinformatics is a scientific discipline lying at the intersection of biology, mathematics, computing science, and information technology. Bioinformatics can be discussed within the following frameworks: • Applications: What kind of research questions can be answered using bioinformatics? • Databases: What data sources and applicable semantic standards (ontology1) are pertinent to answering these research questions? • Protocols, algorithms, and tools: What analysis protocols, computing algorithms, and software tools can be applied to answer these research questions? • Infrastructure: What hardware, software, and networking systems are required to support the above? This review will focus primarily on germplasm-based crop research, although many of the same tools can be applied to current problems in soil microbiology, entomology, and other areas of crop research. Also, some of the design principles of bioinformatics information systems will be useful for other research fields, such as geographic and agronomic information systems.

Integrating mouse anatomy and pathology ontologies into a phenotyping database: Tools for data capture and training

The Mouse Disease Information System (MoDIS) is a data capture system for pathology data from laboratory mice designed to support phenotyping studies. The system integrates the mouse anatomy (MA) and mouse pathology (MPATH) ontologies into a Microsoft Access database facilitating the coding of organ, tissue, and disease process to recognized semantic standards. Grading of disease severity provides scores for all lesions that can then be used for quantitative trait locus (QTL) analyses and haplotype association gene mapping. Direct linkage to the Pathbase online database provides reference definitions for disease terms and access to photomicrographic images of similar diagnoses in other mutant mice. MoDIS is an open source and freely available program (http://research.jax.org/faculty/sundberg/index.html). This provides a valuable tool for setting up a mouse pathology phenotyping program.

Progress in updating the European Radiobiology Archives

Purpose: The European Radiobiology Archives (ERA), together with corresponding Japanese and American databases, hold data from nearly all experimental animal radiation biology studies carried out between 1960 and 1998, involving more than 300,000 animals. The Federal Office for Radiation Protection, together with the University of Cambridge have undertaken to transfer the existing ERA archive to a web-based database to maximize its usefulness to the scientific community and bring data coding and structure of this legacy database into congruence with currently accepted semantic standards for anatomy and pathology.Methods: The accuracy of the primary data input was assessed and improved. The original rodent pathology nomenclature was recoded to replace the local ‘DIS-ROD’ (Disease Rodent) formalism with Mouse Pathology (MPATH) and Mouse Anatomy (MA) ontology terms. A pathology panel sampled histopathological slide material and compared the original diagnoses with currently accepted diagnostic criteria.Results: The overall non-systematic error rate varied among the studies between 0.26% and 4.41%, the mean error being 1.71%. The errors found have been corrected and the studies thus controlled have been annotated. The majority of the original pathology terms have been successfully translated into a combination of MPATH and MA ontology terms.Conclusions: ERA has the potential of becoming a world-wide radiobiological research tool for numerous applications, such as the re-analysis of existing data with new approaches in the light of new hypotheses and techniques, and using the database as an information resource for planning future animal studies. When the database is opened for new data it may be possible to offer long-term storage of data from recent and future animal studies.

The Mouse Genome Database (MGD): mouse biology and model systems.

The Mouse Genome Database, (MGD, http://www.informatics.jax.org/), integrates genetic, genomic and phenotypic information about the laboratory mouse, a primary animal model for studying human biology and disease. MGD data content includes comprehensive characterization of genes and their functions, standardized descriptions of mouse phenotypes, extensive integration of DNA and protein sequence data, normalized representation of genome and genome variant information including comparative data on mammalian genes. Data within MGD are obtained from diverse sources including manual curation of the biomedical literature, direct contributions from individual investigator's laboratories and major informatics resource centers such as Ensembl, UniProt and NCBI. MGD collaborates with the bioinformatics community on the development of data and semantic standards such as the Gene Ontology (GO) and the Mammalian Phenotype (MP) Ontology. MGD provides a data-mining platform that enables the development of translational research hypotheses based on comparative genotype, phenotype and functional analyses. Both web-based querying and computational access to data are provided. Recent improvements in MGD described here include the association of gene trap data with mouse genes and a new batch query capability for customized data access and retrieval.

Data integration and standardization in cross-border hydrogeological studies: a novel approach to hydrostratigraphic model development

Data integration—or the merging of multiple source data sets—is central to hydrogeological studies. In cross-border situations, data heterogeneities are the source of most integration problems. Semantic integration of the subsurface geological terms is undertaken for the Abbotsford–Sumas aquifer, a cross-border (trans-national) aquifer, which is equally shared by British Columbia (Canada) and Washington State (US). Subsurface information is largely derived from water well information submitted to the respective governments. Use of this information is constrained due to inconsistent use of geological terms in water well reports. Lack of standardized methodology resulted in 6,000 unique geological descriptions for the aquifer alone. Semantic standardization of geological descriptions progressed from database interpretation to domain expert interpretation. Despite the poor quality of water well information, trends were observed that facilitated the development of a hydrostratigraphic model that honors the generalized early conceptual models of the aquifer, but provides a much higher degree of resolution in the stratigraphy necessary for groundwater flow modeling. The standardization protocols introduced support the model creation despite the constraint of poor quality data.

Public Trust and Privacy in Shared Electronic Health Records

The development of information and communication technology in health care, also called eHealth, is expected to improve patient safety and facilitate more efficient use of limited resources. The introduction of electronic health records (EHRs) can make possible immediate, even automatic transfer of patient data, for health care as well as other purposes, across any kind of institutional, regional or national border. Data can thus be shared and used more effectively for quality assurance, disease surveillance, public health monitoring and research. eHealth may also facilitate patient access to health information and medical treatment, and is seen as an effective tool for patient empowerment. At the same time, eHealth solutions may jeopardize both patient safety and patients' rights, unless carefully designed and used with discretion. The success of EHR systems will depend on public trust in their compatibility with fundamental rights, such as privacy and confidentiality. Shared European EHR systems require interoperability not only with regard to technological and semantic standards, but also concerning legal, social and cultural aspects. Since the area of privacy and medical confidentiality is far from harmonized across Europe, we are faced with a diversity that will make fully shared EHR systems a considerable challenge.

Particularist semantic normativity

We sketch the view we call contextual semantics. It asserts that truth is semantically correct affirmability under contextually variable semantic standards, that truth is frequently an indirect form of correspondence between thought/language and the world, and that many Quinean commitments are not genuine ontological commitments. We argue that contextualist semantics fits very naturally with the view that the pertinent semantic standards are particularist rather than being systematizable as exceptionless general principles.

The mouse genome database (MGD): new features facilitating a model system

The mouse genome database (MGD, ), the international community database for mouse, provides access to extensive integrated data on the genetics, genomics and biology of the laboratory mouse. The mouse is an excellent and unique animal surrogate for studying normal development and disease processes in humans. Thus, MGD's primary goals are to facilitate the use of mouse models for studying human disease and enable the development of translational research hypotheses based on comparative genotype, phenotype and functional analyses. Core MGD data content includes gene characterization and functions, phenotype and disease model descriptions, DNA and protein sequence data, polymorphisms, gene mapping data and genome coordinates, and comparative gene data focused on mammals. Data are integrated from diverse sources, ranging from major resource centers to individual investigator laboratories and the scientific literature, using a combination of automated processes and expert human curation. MGD collaborates with the bioinformatics community on the development of data and semantic standards, and it incorporates key ontologies into the MGD annotation system, including the Gene Ontology (GO), the Mammalian Phenotype Ontology, and the Anatomical Dictionary for Mouse Development and the Adult Anatomy. MGD is the authoritative source for mouse nomenclature for genes, alleles, and mouse strains, and for GO annotations to mouse genes. MGD provides a unique platform for data mining and hypothesis generation where one can express complex queries simultaneously addressing phenotypic effects, biochemical function and process, sub-cellular location, expression, sequence, polymorphism and mapping data. Both web-based querying and computational access to data are provided. Recent improvements in MGD described here include the incorporation of single nucleotide polymorphism data and search tools, the addition of PIR gene superfamily classifications, phenotype data for NIH-acquired knockout mice, images for mouse phenotypic genotypes, new functional graph displays of GO annotations, and new orthology displays including sequence information and graphic displays.

From information to understanding: the role of model organism databases in comparative and functional genomics

Data integration is key to functional and comparative genomics because integration allows diverse data types to be evaluated in new contexts. To achieve data integration in a scalable and sensible way, semantic standards are needed, both for naming things (standardized nomenclatures, use of key words) and also for knowledge representation. The Mouse Genome Informatics database and other model organism databases help to close the gap between information and understanding of biological processes because these resources enforce well-defined nomenclature and knowledge representation standards. Model organism databases have a critical role to play in ensuring that diverse kinds of data, especially genome-scale data sets and information, remain useful to the biological community in the long-term. The efforts of model organism database groups ensure not only that organism-specific data are integrated, curated and accessible but also that the information is structured in such a way that comparison of biological knowledge across model organisms is facilitated.

The Mouse Genome Database (MGD): updates and enhancements

The Mouse Genome Database (MGD) integrates genetic and genomic data for the mouse in order to facilitate the use of the mouse as a model system for understanding human biology and disease processes. A core component of the MGD effort is the acquisition and integration of genomic, genetic, functional and phenotypic information about mouse genes and gene products. MGD works within the broader bioinformatics community to define referential and semantic standards to facilitate data exchange between resources including the incorporation of information from the biomedical literature. MGD is also a platform for computational assessment of integrated biological data with the goal of identifying candidate genes associated with complex phenotypes. MGD is web accessible at . Recent improvements in MGD described here include the incorporation of an interactive genome browser, the enhancement of phenotype resources and the further development of functional annotation resources.

The Mouse Genome Database (MGD): from genes to mice--a community resource for mouse biology

The Mouse Genome Database (MGD) forms the core of the Mouse Genome Informatics (MGI) system (http://www.informatics.jax.org), a model organism database resource for the laboratory mouse. MGD provides essential integration of experimental knowledge for the mouse system with information annotated from both literature and online sources. MGD curates and presents consensus and experimental data representations of genotype (sequence) through phenotype information, including highly detailed reports about genes and gene products. Primary foci of integration are through representations of relationships among genes, sequences and phenotypes. MGD collaborates with other bioinformatics groups to curate a definitive set of information about the laboratory mouse and to build and implement the data and semantic standards that are essential for comparative genome analysis. Recent improvements in MGD discussed here include the enhancement of phenotype resources, the re-development of the International Mouse Strain Resource, IMSR, the update of mammalian orthology datasets and the electronic publication of classic books in mouse genetics.

Biological Information Standards

Biological Information Standards

What’s Wrong with Contextualism, and a Noncontextualist Resolution of the Skeptical Paradox

Skeptics try to persuade us of our ignorance with arguments like the following: 1. I don’t know that I am not a handless brain-in-a-vat [BIV]. 2. If I don’t know that I am not a handless BIV, then I don’t know that I have hands. Therefore, 3. I don’t know that I have hands. The BIV argument is valid, its premises are intuitively compelling, and yet, its conclusion strikes us as absurd. Something has to go, but what? Contextualists contend that an adequate solution to the skeptical problem must: (i) retain epistemic closure, (ii) explain the intuitive force of skeptical arguments by explaining why their premises initially seem so compelling, and (iii) account for the truth of our commonsense judgment that we do possess lots of ordinary knowledge. Contextualists maintain that the key to such a solution is recognizing that the semantic standards for ‘knows’ vary from context to context such that in skeptical contexts the skeptic’s premises are true and so is her conclusion; but in ordinary contexts, her conclusion is false and so is her first premise. Despite its initial attractiveness, the contextualist solution comes at a significant cost, for contextualism has many counterintuitive results. After presenting the contextualist solution, I identify a number of these costs. I then offer a noncontextualist solution that meets the adequacy constraint identified above, while avoiding the costs associated with contextualism. Hence, one of the principal reasons offered for adopting a contextualist theory of knowledge — its supposedly unique ability to adequately resolve the skeptical problem — is undermined. The intense view of these manifold contradictions and imperfections in human reason has so wrought upon me, and heated my brain, that I am ready to reject all belief and reasoning, and can look upon no opinion even as more probable or likely than another. Where am I, or what? ...; Most fortunately it happens, that since reason is incapable of dispelling these clouds, nature herself suffices to that purpose, and cures me of this philosophical melancholy and delirium, either by relaxing this bent of mind, or by some avocation, and lively impression of my senses, which obliterate all these chimeras. I dine, I play a game of back-gammon. I converse, and am merry with my friends; and when after three or four hour’s amusement, I wou’d return to these speculations, they appear so cold, and strained, and ridiculous, that I cannot find in my heart to enter into them any farther (Hume, 1739, p. 268f). There is an inconvenience which attends all abstruse reasoning, that it may silence, without convincing an antagonist, … When we leave our closet, and engage in the common affairs of life, its conclusions seem to vanish, like the phantoms of the night on the appearance of the morning (Hume, 1739, p. 455).

The Mouse Genome Database (MGD): integrating biology with the genome.

The Mouse Genome Database (MGD) is one component of the Mouse Genome Informatics (MGI) system (http://www.informatics.jax.org), a community database resource for the laboratory mouse. MGD strives to provide a comprehensive knowledgebase about the mouse with experiments and data annotated from both literature and online sources. MGD curates and presents consensus and experimental data representations of genetic, genotype (sequence) and phenotype information including highly detailed reports about genes and gene products. Primary foci of integration are through representations of relationships between genes, sequences and phenotypes. MGD collaborates with other bioinformatics groups to curate a definitive set of information about the laboratory mouse and to build and implement the data and semantic standards that are essential for comparative genome analysis. Recent developments in MGD discussed here include an extensive integration of the mouse sequence data and substantial revisions in the presentation, query and visualization of sequence data.

Flexible Standardization: Making Interoperability Accessible to Agencies with Limited Resources

Semantic standardization is an integral part of sharing data for GIS and spatial analysis. It is part of a broader rubric of interoperability or the ability to share geographic information across multiple platforms and contexts. GIScience researchers have made considerable progress towards understanding and addressing the multiple challenges involved in achieving interoperability. For local government agencies interested in sharing spatial data, however, current interoperability approaches based on object-oriented data models represent idealistic solutions to problems of semantic heterogeneity that often exceed the level of sophistication and funding available. They are waiting for the market to decide how interoperability should be resolved. In order to assist in this transition, this paper presents a rule-based Visual Basic application to standardize the semantics of simple spatial entities using several classification systems. We use the example of well-log data, and argue that this approach enables agencies to share and structure data effectively in an interim period during which market and research standards for semantic interoperability are being determined. It contributes to a geospatial data infrastructure, while allowing agencies to share spatial data in a manner consistent with their level of expertise and existing data structures.

温室環境の遠隔計測・制御・解析用ソフトウェアの開発促進を目的とした環境計測制御システムにおける標準操作規約

Computerized environmental measurement and control systems for greenhouses have been developed and used in Japan since 1974. In 1995, 2566 sets such systems operated for protected plant production in Japan, and the total floor area of computer controlled greenhouses was 3.44 km2. The selling systems of more than 20 corporations could not be operated by the same software in the personal computers connected with the systems, because the systems do not have the common remote operation standard from personal computers. We realized that a more convenient measurement and control for advanced plant production is indispensable to develop advanced software in personal computers. Allowing remote operation of any systems by the same software decreases software development costs and increases the usefulness of the systems and software developers. Therefore, we proposed a standard operation protocol for the environmental measurement and control systems. The standard operation protocol was determined by the following process; (1) A questionnaire research, (2) Testing by a prototype system, (3) Hearing from concerned makers, and (4) Verification of the protocol practicality. Elements of the standard operation protocol were (1) Transferal standardization, (2) Identical standardization, and (3) Semantic standardization. The primary concepts to perform the protocol functions were a virtual controller and a map file. The virtual controller permitted the realization of the protocol by only emulating software. The map file worked unification and localization of measurement and control items easily. The practicality of the standard operation protocol was confirmed by verification tests. It is considered that standard operation protocol contributes to promote development of personal computer software for remote measurement, control, and analysis of the greenhouse environment.

Using interdependence as a predictor of data standards. Theoretical and measurement issues

The standardization of data semantics (definitions, names, identifiers, domains, and constraints) across organizational units and systems is one means of coordinating the activities of these units. Since the need for subunit coordination is considered a function of the level of interdependence among subunits, many authors have hypothesized a positive relationship between subunit interdependence and the use of semantic standards. Empirically testing this relationship revealed two surprising results. First, commonly used operational definitions of interdependence from previous research were found to measure different dimensions and hence could not be used interchangeably. Second, no relationship between any of the operational definitions of subunit interdependence and the use of data standards was found. These findings lead us to believe that more precise conceptualizations of interdependence and better models of the tradeoffs between standardization and alternative means of dealing with inconsistent data semantics are required to better understand how investments in standardized data impact organizational outcomes.

IAIMS and sharing

The Integrated Academic Information Management System (IAIMS) concept is about sharing resources and information, and about improving the decision-making ability of health care professionals by integrating information. At Columbia-Presbyterian Medical Center, the IAIMS project has established an information architecture based on common, shared computing and networking resources. The institutional computing culture has been changed with increased sharing of information and, consequently, improved quality of information. Several classes of information in the areas of clinical, scholarly, administrative, basic research, and core resources have been identified for better understanding of information responsibility. Technical problems such as heterogeneity on workstation platforms and lack of universal syntactic and semantic standards for health care information exchange still impede interinstitutional sharing of information.

Semantic Standards for the Representation of Medical Records

Physicians developed their sublanguage (a system to represent medical concepts and their relations) to store and transmit general medical knowledge and patient-related information. Adequate formalisms are needed to obtain a standard representation of semantics of medical expressions for computer use. Comparison of the semantic contents of two expressions is possible only if a unique canonical form is defined; the transmission of medical facts or patient-related information is really meaningful only by defining a set of primitives (semantic categories and links) and the domains of values (concepts). These primitives must be harmonized to yield a "common core subset" of semantic categories and links. This subset provides a common basis; a procedure to register extension sets of primitives must also be defined, to comply with specific representation needs of specialties and classes of application software.

Using convert to transform source code

AbstractThere are a number of reasons why one might wish to transform the source code of an operational program: To make the program conform to a standard layout. To make the program conform to syntax and semantics standards. To improve the performance of the program. The primary advantage of transforming source code into a standard form is that the programs become easier to maintain. The cost‐benefit of standardization is thus realized at a later stage in the lifetime of the programs. Alternatively the cost‐benefit of improving performance is immediate.The desirability of transforming source code is affected by several parameters: The benefit to be realized from transformation. The cost of transformation. The time involved in transformation. The risk associated with transformation. If the benefit of transformation is significant, the cost, time and risk associated with the process can be considerably reduced by automating the process.In this paper, application of the CONVERT language to the transformation problem is discussed. CONVERT was developed as a vehicle for writing automatic language and dialect converters. Clearly, the features useful for converters are also applicable when the application involves transformation of source code.