1st INCF Workshop on Global Portal Services for Neuroscience

The goal of this meeting was to map out existing portal services for neuroscience, identify their features and future plans, and outline opportunities for synergistic developments. The workshop discussed alternative formats of future global and integrated portal services

Mejorando la Ciencia Abierta Usando Datos Abiertos Enlazados: Caso de Uso CONICET Digital

Los servicios de publicación científica están cambiando drásticamente, los investigadores demandan servicios de búsqueda inteligentes para descubrir y relacionar publicaciones científicas. Los editores deben incorporar información semántica para organizar mejor sus activos digitales y hacer que las publicaciones sean más visibles. En este documento, presentamos el trabajo en curso para publicar un subconjunto de publicaciones científicas de CONICET Digital como datos abiertos enlazados. El objetivo de este trabajo es mejorar la recuperación y la reutilización de datos a través de tecnologías de Web Semántica y Datos Enlazados en el dominio de las publicaciones científicas. Para lograr estos objetivos, se han tenido en cuenta los estándares de la Web Semántica y los esquemas RDF (Dublín Core, FOAF, VoID, etc.). El proceso de conversión y publicación se basa en las pautas metodológicas para publicar datos vinculados de gobierno. También describimos como estos datos se pueden vincular a otros conjuntos de datos como DBLP, Wikidata y DBPedia. Finalmente, mostramos algunos ejemplos de consultas que responden a preguntas que inicialmente no permite CONICET Digital.Scientific publication services are changing drastically, researchers demand intelligent search services to discover and relate scientific publications. Publishersneed to incorporate semantic information to better organize their digital assets and make publications more discoverable. In this paper, we present the on-going work to publish a subset of scientific publications of CONICET Digital as Linked Open Data. The objective of this work is to improve the recovery andreuse of data through Semantic Web technologies and Linked Data in the domain of scientific publications.To achieve these goals, Semantic Web standards and reference RDF schema?s have been taken into account (Dublin Core, FOAF, VoID, etc.). The conversion and publication process is guided by the methodological guidelines for publishing government linked data. We also outline how these data can be linked to other datasets DBLP, WIKIDATA and DBPEDIA on the web of data. Finally, we show some examples of queries that answer questions that initially CONICET Digital does not allowFil: Zárate, Marcos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; ArgentinaFil: Carlos Buckle. Universidad Nacional de la Patagonia "San Juan Bosco"; ArgentinaFil: Mazzanti, Renato. Universidad Nacional de la Patagonia "San Juan Bosco"; ArgentinaFil: Samec, Gustavo Daniel. Universidad Nacional de la Patagonia "San Juan Bosco"; Argentin

Augmented Memory for Conference Attendees

Human memory at its best can perform astonishing feats - the tiniest snippet of information can trigger whole chains of associations, ending at an item long-believed forgotten. While modern information systems excel at systematic manipulation of structured or semi-structured information or even vast repositories of unstructured textual information, they are still far from these capabilities

Research on conceptual modeling: Themes, topics, and introduction to the special issue

Conceptual modeling continues to evolve as researchers and practitioners reflect on the challenges of modeling and implementing data-intensive problems that appear in business and in science. These challenges of data modeling and representation are well-recognized in contemporary applications of big data, ontologies, and semantics, along with traditional efforts associated with methodologies, tools, and theory development. This introduction contains a review of some current research in conceptual modeling and identifies emerging themes. It also introduces the articles that comprise this special issue of papers from the 32nd International Conference on Conceptual Modeling (ER 2013).This article was supported, in part, by the J. Mack Robinson College of Business at the Georgia State University, the Marriott School of Management at Brigham Young University (EB-201313), and by the GEODAS-BI (TIN2012-37493-C03-03) project from the Spanish Ministry of Education and Competitivity

Special Issue on Smart Data and Semantics in a Sensor World

Introduction Since its first inception in 2001, the application of the Semantic Web [1, 2] has carried out an extensive use of ontologies [3–5], reasoning, and semantics in diverse fields, such as Information Integration, Software Engineering, Bioinformatics, eGovernment, eHealth, and social networks. This widespread use of ontologies has led to an incredible advance in the development of techniques to manipulate, share, reuse, and integrate information across heterogeneous data sources. In recent years, the growth of the IoT (Internet of Things) required to face the challenges of “Big Data” [6–10]. The cost of sensors is decreasing, while their use is expanding. Moreover, the use of multiple personal smart devices is an emerging trend and all of them can embed sensors to monitor the surrounding environment. Therefore, the number of available sensors is exploding. On the one hand, the flows of sensor data are massive and continuous, and the data could be obtained in real time or with a delay of just a few seconds. Then, the volume of sensor data is increasing continuously every day. On the other hand, the variety of data being generated is also increasing, due to plenty of different devices and different measures to record. There are many kinds of structured and unstructured sensor data in diverse formats. Moreover, data veracity, which is the degree of accuracy or truthfulness of a data set, is an important aspect to consider. In the context of sensor data, it represents the trustworthiness of the data source and the processing of data. The need for more accurate and reliable data was always declared, but often overlooked for the sake of larger and cheaper..

I'm sorry to say, but your understanding of image processing fundamentals is absolutely wrong

The ongoing discussion whether modern vision systems have to be viewed as visually-enabled cognitive systems or cognitively-enabled vision systems is groundless, because perceptual and cognitive faculties of vision are separate components of human (and consequently, artificial) information processing system modeling.Comment: To be published as chapter 5 in "Frontiers in Brain, Vision and AI", I-TECH Publisher, Viena, 200

Discovering Knowledge through Highly Interactive Information Based Systems

[EN] The new Internet era has increased a production of digital data. The mankind had an easy way to the knowledge access never before, but at the same time the rapidly increasing rate of new data, the ease of duplication and transmission of these data across the Net, the new available channels for information dissemination, the large amounts of historical data, questionable quality of the existing data and so on are issues for information overload that causes more difficult to make decision using the right data. Soft-computing techniques for decision support systems and business intelligent systems present pretty interesting and necessary solutions for data management and supporting decision-making processes, but the last step at the decision chain is usually supported by a human agent that has to process the system outcomes in form of reports or visualizations. These kinds of information representations are not enough to make decisions because of behind them could be hidden information patterns that are not obvious for automatic data processing and humans must interact with these data representation in order to discover knowledge. According to this, the current special issue is devoted to present nine experiences that combine visualization and visual analytics techniques, data mining methods, intelligent recommendation agents, user centered evaluation and usability patterns, etc. in interactive systems as a key issue for knowledge discovering in advanced and emerging information systems.[ES] La nueva era de Internet ha aumentado la producción de datos digitales. Nunca nates la humanidad ha tenido una manera más fácil el acceso a los conocimientos, pero al mismo tiempo el rápido aumento de la tasa de nuevos datos, la facilidad de duplicación y transmisión de estos datos a través de la red, los nuevos canales disponibles para la difusión de información, las grandes cantidades de los datos históricos, cuestionable calidad de los datos existentes y así sucesivamente, son temas de la sobrecarga de información que hace más difícil tomar decisiones con la información correcta. Técnicas de Soft-computing para los sistemas de apoyo a las decisiones y sistemas inteligentes de negocios presentan soluciones muy interesantes y necesarias para la gestión de datos y procesos de apoyo a la toma de decisiones, pero el último paso en la cadena de decisiones suele ser apoyados por un agente humano que tiene que procesar los resultados del sistema de en forma de informes o visualizaciones. Este tipo de representaciones de información no son suficientes para tomar decisiones debido detrás de ellos podrían ser patrones de información ocultos que no son obvios para el procesamiento automático de datos y los seres humanos deben interactuar con estos representación de datos con el fin de descubrir el conocimiento. De acuerdo con esto, el presente número especial está dedicado a nueve experiencias actuales que combinan técnicas de visualización y de análisis visual, métodos de minería de datos, agentes de recomendación inteligentes y evaluación centrada en el usuario y patrones de usabilidad, etc. En sistemas interactivos como un tema clave para el descubrimiento de conocimiento en los sistemas de información avanzados y emergentes

Design Research and Domain Representation

While diverse theories about the nature of design research have been proposed, they are rarely considered in relation to one another across the broader disciplinary field. Discussions of design research paradigms have tended to use overarching binary models for understanding differing knowledge frameworks. This paper focuses on an analysis of theories of design research and the use of Web 3 and open content systems to explore the potential of building more relational modes of conceptual representation. The nature of this project is synthetic, building upon the work of other design theorists and researchers. A number of theoretical frameworks will be discussed and examples of the analysis and modelling of key concepts and information relationships, using concept mapping software, collaborative ontology building systems and semantic wiki technologies will be presented. The potential of building information structures from content relationships that are identified by domain specialists rather than the imposition of formal, top-down, information hierarchies developed by information scientists, will be considered. In particular the opportunity for users to engage with resources through their own knowledge frameworks, rather than through logically rigorous but largely incomprehensible ontological systems, will be explored in relation to building resources for emerging design researchers. The motivation behind this endeavour is not to create a totalising meta-theory or impose order on the ‘ill structured’ and ‘undisciplined’, domain of design. Nor is it to use machine intelligence to ‘solve design problems’. It seeks to create dynamic systems that might help researchers explore design research theories and their various relationships with one another. It is hoped such tools could help novice researchers to better locate their own projects, find reference material, identify knowledge gaps and make new linkages between bodies of knowledge by enabling forms of data-poesis - the freeing of data for different trajectories. Keywords: Design research; Design theory; Methodology; Knowledge systems; Semantic web technologies.</p