[When an image does not reveal everything: analysis of the discourse of the Family Health Strategy logo in the light of the concept of the contemporary family]. / Quando uma imagem não diz tudo: análise do discurso da logomarca da Estratégia Saúde da Família à luz do conceito de família contemporânea.

This article deals with exploratory research with the objective of analyzing the discourse of the Family Health Strategy (ESF) logo in the light of the concept of the contemporary family. The analysis was made using the "Semiolinguistic" theory of Patrick Charaudeau of the French School of Discourse. The result revealed a discursive framework with important restrictions regarding the act of language as the monologue aspect of the process and a subject of non-institutional speech constituted by the advertising agent hired by the Ministry of Health. In the analysis, a discrepancy was found between the verbal content that shows the expression "Family Health" tending to the comprehensiveness of the policy implemented by the ESF, when compared with the image aspect, the elements of which demonstrated the predominance of the traditional family. The relevance of multiple contexts, such as cultural, social and gender aspects, which influenced the interpretation of mixed texts, was studied. The need to reformulate the brand was pointed out to make it more comprehensive and consistent with the new contemporary family formats. Future studies are suggested that address the limiting character implicit in the concept behind the logo in a more critical and incisive manner.

O artigo trata de uma pesquisa exploratória com o objetivo de analisar o discurso da logomarca da Estratégia Saúde da Família (ESF) à luz do conceito de família contemporânea. A análise se deu pela teoria Semiolinguística de Patrick Charaudeau da Escola Francesa do Discurso. O resultado mostrou um quadro discursivo com importantes restrições quanto ao ato de linguagem como o aspecto monologal do processo e um sujeito de fala não institucional constituído pelo agente publicitário contratado pelo Ministério da Saúde. Na análise evidenciou-se uma discrepância entre o conteúdo verbal que mostra a expressão "Saúde da Família" tendendo à abrangência da política implementada pela ESF quando comparado à parte imagética cujos elementos demonstraram o predomínio da família tradicional. Trabalhou-se a relevância de múltiplos contextos como o cultural, o social e o de gênero que influenciam na interpretação de textos mistos. Apontou-se a necessidade de reformulação da marca para torná-la mais abrangente e condizente com os novos formatos de família na contemporaneidade. Sugere-se estudos futuros que explorem, de maneira mais crítica e incisiva, o caráter limitante implícito na visão da logomarca.

Quando uma imagem não diz tudo: análise do discurso da logomarca da Estratégia Saúde da Família à luz do conceito de família contemporânea / When an image does not reveal everything: analysis of the discourse of the Family Health Strategy logo in the light of the concept of the contemporary family

Resumo O artigo trata de uma pesquisa exploratória com o objetivo de analisar o discurso da logomarca da Estratégia Saúde da Família (ESF) à luz do conceito de família contemporânea. A análise se deu pela teoria Semiolinguística de Patrick Charaudeau da Escola Francesa do Discurso. O resultado mostrou um quadro discursivo com importantes restrições quanto ao ato de linguagem como o aspecto monologal do processo e um sujeito de fala não institucional constituído pelo agente publicitário contratado pelo Ministério da Saúde. Na análise evidenciou-se uma discrepância entre o conteúdo verbal que mostra a expressão "Saúde da Família" tendendo à abrangência da política implementada pela ESF quando comparado à parte imagética cujos elementos demonstraram o predomínio da família tradicional. Trabalhou-se a relevância de múltiplos contextos como o cultural, o social e o de gênero que influenciam na interpretação de textos mistos. Apontou-se a necessidade de reformulação da marca para torná-la mais abrangente e condizente com os novos formatos de família na contemporaneidade. Sugere-se estudos futuros que explorem, de maneira mais crítica e incisiva, o caráter limitante implícito na visão da logomarca.

Abstract This article deals with exploratory research with the objective of analyzing the discourse of the Family Health Strategy (ESF) logo in the light of the concept of the contemporary family. The analysis was made using the "Semiolinguistic" theory of Patrick Charaudeau of the French School of Discourse. The result revealed a discursive framework with important restrictions regarding the act of language as the monologue aspect of the process and a subject of non-institutional speech constituted by the advertising agent hired by the Ministry of Health. In the analysis, a discrepancy was found between the verbal content that shows the expression "Family Health" tending to the comprehensiveness of the policy implemented by the ESF, when compared with the image aspect, the elements of which demonstrated the predominance of the traditional family. The relevance of multiple contexts, such as cultural, social and gender aspects, which influenced the interpretation of mixed texts, was studied. The need to reformulate the brand was pointed out to make it more comprehensive and consistent with the new contemporary family formats. Future studies are suggested that address the limiting character implicit in the concept behind the logo in a more critical and incisive manner.

The Ontology for Biomedical Investigations.

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

The mouse-human anatomy ontology mapping project.

The overall objective of the Mouse-Human Anatomy Project (MHAP) was to facilitate the mapping and harmonization of anatomical terms used for mouse and human models by Mouse Genome Informatics (MGI) and the National Cancer Institute (NCI). The anatomy resources designated for this study were the Adult Mouse Anatomy (MA) ontology and the set of anatomy concepts contained in the NCI Thesaurus (NCIt). Several methods and software tools were identified and evaluated, then used to conduct an in-depth comparative analysis of the anatomy ontologies. Matches between mouse and human anatomy terms were determined and validated, resulting in a highly curated set of mappings between the two ontologies that has been used by other resources. These mappings will enable linking of data from mouse and human. As the anatomy ontologies have been expanded and refined, the mappings have been updated accordingly. Insights are presented into the overall process of comparing and mapping between ontologies, which may prove useful for further comparative analyses and ontology mapping efforts, especially those involving anatomy ontologies. Finally, issues concerning further development of the ontologies, updates to the mapping files, and possible additional applications and significance were considered. DATABASE URL: http://obofoundry.org/cgi-bin/detail.cgi?id=ma2ncit.

The NCI Thesaurus quality assurance life cycle.

The National Cancer Institute Enterprise Vocabulary Services (NCI EVS) uses a wide range of quality assurance (QA) techniques to maintain and extend NCI Thesaurus (NCIt). NCIt is a reference terminology and biomedical ontology used in a growing number of NCI and other systems that extend from translational and basic research through clinical care to public information and administrative activities. Both automated and manual QA techniques are employed throughout the editing and publication cycle, which includes inserting and editing NCIt in NCI Metathesaurus. NCI EVS conducts its own additional periodic and ongoing content QA. External reviews, and extensive evaluation by and interaction with EVS partners and other users, have also played an important part in the QA process. There have always been tensions and compromises between meeting the needs of dependent systems and providing consistent and well-structured content; external QA and feedback have been important in identifying and addressing such issues. Currently, NCI EVS is exploring new approaches to broaden external participation in the terminology development and QA process.

Representing the NCI Thesaurus in OWL DL: Modeling tools help modeling languages.

The National Cancer Institute's (NCI) Thesaurus is a biomedical reference ontology. The NCI Thesaurus is represented using Description Logic, more specifically Ontylog, a Description logic implemented by Apelon, Inc. We are exploring the use of the DL species of the Web Ontology Language (OWL DL)-a W3C recommended standard for ontology representation-instead of Ontylog for representing the NCI Thesaurus. We have studied the requirements for knowledge representation of the NCI Thesaurus, and considered how OWL DL (and its implementation in Protégé-OWL) satisfies these requirements. In this paper, we discuss the areas where OWL DL was sufficient for representing required components, where tool support that would hide some of the complexity and extra levels of indirection would be required, and where language expressiveness is not sufficient given the representation requirements. Because many of the knowledge-representation issues that we encountered are very similar to the issues in representing other biomedical terminologies and ontologies in general, we believe that the lessons that we learned and the approaches that we developed will prove useful and informative for other researchers.

caCORE version 3: Implementation of a model driven, service-oriented architecture for semantic interoperability.

One of the requirements for a federated information system is interoperability, the ability of one computer system to access and use the resources of another system. This feature is particularly important in biomedical research systems, which need to coordinate a variety of disparate types of data. In order to meet this need, the National Cancer Institute Center for Bioinformatics (NCICB) has created the cancer Common Ontologic Representation Environment (caCORE), an interoperability infrastructure based on Model Driven Architecture. The caCORE infrastructure provides a mechanism to create interoperable biomedical information systems. Systems built using the caCORE paradigm address both aspects of interoperability: the ability to access data (syntactic interoperability) and understand the data once retrieved (semantic interoperability). This infrastructure consists of an integrated set of three major components: a controlled terminology service (Enterprise Vocabulary Services), a standards-based metadata repository (the cancer Data Standards Repository) and an information system with an Application Programming Interface (API) based on Domain Model Driven Architecture. This infrastructure is being leveraged to create a Semantic Service-Oriented Architecture (SSOA) for cancer research by the National Cancer Institute's cancer Biomedical Informatics Grid (caBIG).

Development of FuGO: an ontology for functional genomics investigations.

The development of the Functional Genomics Investigation Ontology (FuGO) is a collaborative, international effort that will provide a resource for annotating functional genomics investigations, including the study design, protocols and instrumentation used, the data generated and the types of analysis performed on the data. FuGO will contain both terms that are universal to all functional genomics investigations and those that are domain specific. In this way, the ontology will serve as the "semantic glue" to provide a common understanding of data from across these disparate data sources. In addition, FuGO will reference out to existing mature ontologies to avoid the need to duplicate these resources, and will do so in such a way as to enable their ease of use in annotation. This project is in the early stages of development; the paper will describe efforts to initiate the project, the scope and organization of the project, the work accomplished to date, and the challenges encountered, as well as future plans.

The MGED Ontology: a resource for semantics-based description of microarray experiments.

MOTIVATION: The generation of large amounts of microarray data and the need to share these data bring challenges for both data management and annotation and highlights the need for standards. MIAME specifies the minimum information needed to describe a microarray experiment and the Microarray Gene Expression Object Model (MAGE-OM) and resulting MAGE-ML provide a mechanism to standardize data representation for data exchange, however a common terminology for data annotation is needed to support these standards. RESULTS: Here we describe the MGED Ontology (MO) developed by the Ontology Working Group of the Microarray Gene Expression Data (MGED) Society. The MO provides terms for annotating all aspects of a microarray experiment from the design of the experiment and array layout, through to the preparation of the biological sample and the protocols used to hybridize the RNA and analyze the data. The MO was developed to provide terms for annotating experiments in line with the MIAME guidelines, i.e. to provide the semantics to describe a microarray experiment according to the concepts specified in MIAME. The MO does not attempt to incorporate terms from existing ontologies, e.g. those that deal with anatomical parts or developmental stages terms, but provides a framework to reference terms in other ontologies and therefore facilitates the use of ontologies in microarray data annotation. AVAILABILITY: The MGED Ontology version.1.2.0 is available as a file in both DAML and OWL formats at http://mged.sourceforge.net/ontologies/index.php. Release notes and annotation examples are provided. The MO is also provided via the NCICB's Enterprise Vocabulary System (http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do). CONTACT: Stoeckrt@pcbi.upenn.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The caCORE Software Development Kit: streamlining construction of interoperable biomedical information services.

BACKGROUND: Robust, programmatically accessible biomedical information services that syntactically and semantically interoperate with other resources are challenging to construct. Such systems require the adoption of common information models, data representations and terminology standards as well as documented application programming interfaces (APIs). The National Cancer Institute (NCI) developed the cancer common ontologic representation environment (caCORE) to provide the infrastructure necessary to achieve interoperability across the systems it develops or sponsors. The caCORE Software Development Kit (SDK) was designed to provide developers both within and outside the NCI with the tools needed to construct such interoperable software systems. RESULTS: The caCORE SDK requires a Unified Modeling Language (UML) tool to begin the development workflow with the construction of a domain information model in the form of a UML Class Diagram. Models are annotated with concepts and definitions from a description logic terminology source using the Semantic Connector component. The annotated model is registered in the Cancer Data Standards Repository (caDSR) using the UML Loader component. System software is automatically generated using the Codegen component, which produces middleware that runs on an application server. The caCORE SDK was initially tested and validated using a seven-class UML model, and has been used to generate the caCORE production system, which includes models with dozens of classes. The deployed system supports access through object-oriented APIs with consistent syntax for retrieval of any type of data object across all classes in the original UML model. The caCORE SDK is currently being used by several development teams, including by participants in the cancer biomedical informatics grid (caBIG) program, to create compatible data services. caBIG compatibility standards are based upon caCORE resources, and thus the caCORE SDK has emerged as a key enabling technology for caBIG. CONCLUSION: The caCORE SDK substantially lowers the barrier to implementing systems that are syntactically and semantically interoperable by providing workflow and automation tools that standardize and expedite modeling, development, and deployment. It has gained acceptance among developers in the caBIG program, and is expected to provide a common mechanism for creating data service nodes on the data grid that is under development.

Modeling a description logic vocabulary for cancer research.

The National Cancer Institute has developed the NCI Thesaurus, a biomedical vocabulary for cancer research, covering terminology across a wide range of cancer research domains. A major design goal of the NCI Thesaurus is to facilitate translational research. We describe: the features of Ontylog, a description logic used to build NCI Thesaurus; our methodology for enhancing the terminology through collaboration between ontologists and domain experts, and for addressing certain real world challenges arising in modeling the Thesaurus; and finally, we describe the conversion of NCI Thesaurus from Ontylog into Web Ontology Language Lite. Ontylog has proven well suited for constructing big biomedical vocabularies. We have capitalized on the Ontylog constructs Kind and Role in the collaboration process described in this paper to facilitate communication between ontologists and domain experts. The artifacts and processes developed by NCI for collaboration may be useful in other biomedical terminology development efforts.

Overview and utilization of the NCI thesaurus.

The NCI Thesaurus is a reference terminology covering areas of basic and clinical science, built with the goal of facilitating translational research in cancer. It contains nearly 110 000 terms in approximately 36000 concepts, partitioned in 20 subdomains, which include diseases, drugs, anatomy, genes, gene products, techniques, and biological processes, among others, all with a cancer-centric focus in content, and originally designed to support coding activities across the National Cancer Institute. Each concept represents a unit of meaning and contains a number of annotations, such as synonyms and preferred name, as well as annotations such as textual definitions and optional references to external authorities. In addition, concepts are modelled with description logic (DL) and defined by their relationships to other concepts; there are currently approximately 90 types of named relations declared in the terminology. The NCI Thesaurus is produced by the Enterprise Vocabulary Services project, a collaborative effort between the NCI Center for Bioinformatics and the NCI Office of Communications, and is part of the caCORE infrastructure stack (http://ncicb.nci.nih.gov/NCICB/core). It can be accessed programmatically through the open caBIO API and browsed via the web (http://nciterms.nci.nih.gov). A history of editing changes is also accessible through the API. In addition, the Thesaurus is available for download in various file formats, including OWL, the web ontology language, to facilitate its utilization by others.

caCORE: a common infrastructure for cancer informatics.

MOTIVATION: Sites with substantive bioinformatics operations are challenged to build data processing and delivery infrastructure that provides reliable access and enables data integration. Locally generated data must be processed and stored such that relationships to external data sources can be presented. Consistency and comparability across data sets requires annotation with controlled vocabularies and, further, metadata standards for data representation. Programmatic access to the processed data should be supported to ensure the maximum possible value is extracted. Confronted with these challenges at the National Cancer Institute Center for Bioinformatics, we decided to develop a robust infrastructure for data management and integration that supports advanced biomedical applications. RESULTS: We have developed an interconnected set of software and services called caCORE. Enterprise Vocabulary Services (EVS) provide controlled vocabulary, dictionary and thesaurus services. The Cancer Data Standards Repository (caDSR) provides a metadata registry for common data elements. Cancer Bioinformatics Infrastructure Objects (caBIO) implements an object-oriented model of the biomedical domain and provides Java, Simple Object Access Protocol and HTTP-XML application programming interfaces. caCORE has been used to develop scientific applications that bring together data from distinct genomic and clinical science sources. AVAILABILITY: caCORE downloads and web interfaces can be accessed from links on the caCORE web site (http://ncicb.nci.nih.gov/core). caBIO software is distributed under an open source license that permits unrestricted academic and commercial use. Vocabulary and metadata content in the EVS and caDSR, respectively, is similarly unrestricted, and is available through web applications and FTP downloads. SUPPLEMENTARY INFORMATION: http://ncicb.nci.nih.gov/core/publications contains links to the caBIO 1.0 class diagram and the caCORE 1.0 Technical Guide, which provide detailed information on the present caCORE architecture, data sources and APIs. Updated information appears on a regular basis on the caCORE web site (http://ncicb.nci.nih.gov/core).

Enhancing quality of retrieval through concept edit history.

The NCI Thesaurus is a public domain description logic-based terminology produced by the National Cancer Institute. The NCI Thesaurus is used to support storage and retrieval of scientific, clinical and research administration data. The content of the NCI Thesaurus evolves rapidly. We have developed a representation of concept change over time and have implemented software to capture concept change in our multi-editor concurrent vocabulary development environment. We are now implementing software to extend our vocabulary server, public APIs and our file-based distributions of the Thesaurus to provide access to the concept-level history information.