907 research outputs found

    The INCF Digital Atlasing Program: Report on Digital Atlasing Standards in the Rodent Brain

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    The goal of the INCF Digital Atlasing Program is to provide the vision and direction necessary to make the rapidly growing collection of multidimensional data of the rodent brain (images, gene expression, etc.) widely accessible and usable to the international research community. This Digital Brain Atlasing Standards Task Force was formed in May 2008 to investigate the state of rodent brain digital atlasing, and formulate standards, guidelines, and policy recommendations.

Our first objective has been the preparation of a detailed document that includes the vision and specific description of an infrastructure, systems and methods capable of serving the scientific goals of the community, as well as practical issues for achieving
the goals. This report builds on the 1st INCF Workshop on Mouse and Rat Brain Digital Atlasing Systems (Boline et al., 2007, _Nature Preceedings_, doi:10.1038/npre.2007.1046.1) and includes a more detailed analysis of both the current state and desired state of digital atlasing along with specific recommendations for achieving these goals

    Report on the 2015 NSF Workshop on Unified Annotation Tooling

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    On March 30 & 31, 2015, an international group of twenty-three researchers with expertise in linguistic annotation convened in Sunny Isles Beach, Florida to discuss problems with and potential solutions for the state of linguistic annotation tooling. The participants comprised 14 researchers from the U.S. and 9 from outside the U.S., with 7 countries and 4 continents represented, and hailed from fields and specialties including computational linguistics, artificial intelligence, speech processing, multi-modal data processing, clinical & medical natural language processing, linguistics, documentary linguistics, sign-language linguistics, corpus linguistics, and the digital humanities. The motivating problem of the workshop was the balkanization of annotation tooling, namely, that even though linguistic annotation requires sophisticated tool support to efficiently generate high-quality data, the landscape of tools for the field is fractured, incompatible, inconsistent, and lacks key capabilities. The overall goal of the workshop was to chart the way forward, centering on five key questions: (1) What are the problems with current tool landscape? (2) What are the possible benefits of solving some or all of these problems? (3) What capabilities are most needed? (4) How should we go about implementing these capabilities? And, (5) How should we ensure longevity and sustainability of the solution? I surveyed the participants before their arrival, which provided significant raw material for ideas, and the workshop discussion itself resulted in identification of ten specific classes of problems, five sets of most-needed capabilities. Importantly, we identified annotation project managers in computational linguistics as the key recipients and users of any solution, thereby succinctly addressing questions about the scope and audience of potential solutions. We discussed management and sustainability of potential solutions at length. The participants agreed on sixteen recommendations for future work. This technical report contains a detailed discussion of all these topics, a point-by-point review of the discussion in the workshop as it unfolded, detailed information on the participants and their expertise, and the summarized data from the surveys

    2010 New England Technical Services Librarians Spring Conference: Crosswalks to the Future: Library Metadata on the Move

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    Report on the 2010 New England Technical Services Librarians (NETSL) Spring Conference, held on April 15, 2010 at the College of the Holy Cross in Worcester, Massachusetts

    The GenomeMatrix : data mining from biological databases and data sources for building integrated functional genomics information

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    Search improvement within the geospatial web in the context of spatial data infrastructures

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    El trabajo desarrollado en esta tesis doctoral demuestra que es posible mejorar la búsqueda en el contexto de las Infraestructuras de Datos Espaciales mediante la aplicación de técnicas y buenas prácticas de otras comunidades científicas, especialmente de las comunidades de la Web y de la Web Semántica (por ejemplo, Linked Data). El uso de las descripciones semánticas y las aproximaciones basadas en el contenido publicado por la comunidad geoespacial pueden ayudar en la búsqueda de información sobre los fenómenos geográficos, y en la búsqueda de recursos geoespaciales en general. El trabajo comienza con un análisis de una aproximación para mejorar la búsqueda de las entidades geoespaciales desde la perspectiva de geocodificación tradicional. La arquitectura de geocodificación compuesta propuesta en este trabajo asegura una mejora de los resultados de geocodificación gracias a la utilización de diferentes proveedores de información geográfica. En este enfoque, el uso de patrones estructurales de diseño y ontologías en esta aproximación permite una arquitectura avanzada en términos de extensibilidad, flexibilidad y adaptabilidad. Además, una arquitectura basada en la selección de servicio de geocodificación permite el desarrollo de una metodología de la georreferenciación de diversos tipos de información geográfica (por ejemplo, direcciones o puntos de interés). A continuación, se presentan dos aplicaciones representativas que requieren una caracterización semántica adicional de los recursos geoespaciales. El enfoque propuesto en este trabajo utiliza contenidos basados en heurísticas para el muestreo de un conjunto de recursos geopesaciales. La primera parte se dedica a la idea de la abstracción de un fenómeno geográfico de su definición espacial. La investigación muestra que las buenas prácticas de la Web Semántica se puede reutilizar en el ámbito de una Infraestructura de Datos Espaciales para describir los servicios geoespaciales estandarizados por Open Geospatial Consortium por medio de geoidentificadores (es decir, por medio de las entidades de una ontología geográfica). La segunda parte de este capítulo desglosa la aquitectura y componentes de un servicio de geoprocesamiento para la identificación automática de ortoimágenes ofrecidas a través de un servicio estándar de publicación de mapas (es decir, los servicios que siguen la especificación OGC Web Map Service). Como resultado de este trabajo se ha propuesto un método para la identificación de los mapas ofrecidos por un Web Map Service que son ortoimágenes. A continuación, el trabajo se dedica al análisis de cuestiones relacionadas con la creación de los metadatos de recursos de la Web en el contexto del dominio geográfico. Este trabajo propone una arquitectura para la generación automática de conocimiento geográfico de los recursos Web. Ha sido necesario desarrollar un método para la estimación de la cobertura geográfica de las páginas Web. Las heurísticas propuestas están basadas en el contenido publicado por os proveedores de información geográfica. El prototipo desarrollado es capaz de generar metadatos. El modelo generado contiene el conjunto mínimo recomendado de elementos requeridos por un catálogo que sigue especificación OGC Catalogue Service for the Web, el estandar recomendado por deiferentes Infraestructuras de Datos Espaciales (por ejemplo, the Infrastructure for Spatial Information in the European Community (INSPIRE)). Además, este estudio determina algunas características de la Web Geoespacial actual. En primer lugar, ofrece algunas características del mercado de los proveedores de los recursos Web de la información geográfica. Este estudio revela algunas prácticas de la comunidad geoespacial en la producción de metadatos de las páginas Web, en particular, la falta de metadatos geográficos. Todo lo anterior es la base del estudio de la cuestión del apoyo a los usuarios no expertos en la búsqueda de recursos de la Web Geoespacial. El motor de búsqueda dedicado a la Web Geoespacial propuesto en este trabajo es capaz de usar como base un motor de búsqueda existente. Por otro lado, da soporte a la búsqueda exploratoria de los recursos geoespaciales descubiertos en la Web. El experimento sobre la precisión y la recuperación ha demostrado que el prototipo desarrollado en este trabajo es al menos tan bueno como el motor de búsqueda remoto. Un estudio dedicado a la utilidad del sistema indica que incluso los no expertos pueden realizar una tarea de búsqueda con resultados satisfactorios

    Crowdsourcing for image metadata : a comparison between game-generated tags and professional descriptors

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    One way to address the challenge of creating metadata for digitized image collections is to rely on user-created index terms, typically by harvesting tags from the collaborative information services known as folksonomies or by allowing the users to tag directly in the catalog. An alternative method, only recently applied in cultural heritage institutions, is Human Computation Games, a crowdsourcing tool that relies on user-agreement to create valid tags. This study contributes to the research by investigating tags (at various degrees of validation) generated by a Human Computation Game and comparing them to descriptors assigned to the same images by professional indexers. The analysis is done by classifying tags and descriptors by term-category, as well as by measuring overlap on both syntactic (matching on terms) and semantic (matching on meaning) level between the tags and the descriptors. The findings shows that validated tags tend to describe ‘artifacts/objects’ and that game-generated tags typically will represent what is in the picture, rather than what it is about. Descriptors also primarily belonged to this term-category but also had a substantial amount of ‘Proper nouns’, mainly named locations. Tags generated by the game, not validated by player-agreement, had a higher frequency of ‘subjective/narrative’ tags, but also more errors. It was determined that the exact (character-for-character) overlap i.e. the number of common terms compared to the entire pool of tags and descriptors was slightly less than 5% for all types of tags. By extending the analysis to include fuzzy (word-stem) matching, the overlap more than doubled. The semantic overlap was established with thesaurus relations between a sample of tags and descriptors and adapting this - more inclusive - view of overlap resulted in an increase in percentage of tags that were matched to descriptors. More than half of the validated tags had some thesaurus relation to a descriptor added by a professional indexer. Approximately 60% of the thesaurus relations between descriptors and valid tags were either ‘same’ or ‘equivalent’ and roughly 20% were associative and 20% were hierarchical. For the hierarchical relations it was found that tags typically describe images at a less specific level than descriptors.Joint Master Degree in Digital Library Learning (DILL

    Evolutionary Subject Tagging in the Humanities; Supporting Discovery and Examination in Digital Cultural Landscapes

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    In this paper, the authors attempt to identify problematic issues for subject tagging in the humanities, particularly those associated with information objects in digital formats. In the third major section, the authors identify a number of assumptions that lie behind the current practice of subject classification that we think should be challenged. We move then to propose features of classification systems that could increase their effectiveness. These emerged as recurrent themes in many of the conversations with scholars, consultants, and colleagues. Finally, we suggest next steps that we believe will help scholars and librarians develop better subject classification systems to support research in the humanities.NEH Office of Digital Humanities: Digital Humanities Start-Up Grant (HD-51166-10

    Methods and systems of artificial intelligence

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    The textbook is aimed at the formation of a basic set of knowledge for students of the specialty 122 Computer Science and student-oriented preparation of a bachelor's degree. The tutorial discusses the models and methods used in artificial intelligence systems. Considerable attention is paid to the design of artificial intelligence systems, the consideration of intelligent systems based on knowledge and means of representing and processing knowledge. The material is presented in accordance with the program of the discipline. Contains theoretical material, tasks for independent work of students and examples of their implementation, questions for selfcontrol. The tutorial can be used by teachers, students and graduate students in the field of computer science
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