Towards a Visual SPARQL-DL Query Builder

Querying ontologies is an every-day activity that users need. This interaction will improve when the query is more expressive and easier to develop. For this purpose, a visual query language is an ideal mean for users and ontology engineers for creating queries taking advantage of the easy-to-understand and low time and cost characteristics, specially, for users which does not know textual query languages. On the other side, SPARQL-DL is a powerful and expressive textual query language for OWL-DL based ontologies that can combine TBox/ABox/RBox queries. Considering the advantage of both, we present in this work a visual query language that can be interpreted as SPARQL-DL sentences and thus being used for querying ontologies for its structure and/or instance information. Altogether, we use this idea to create a modified version of crowd, a Web modelling tool with reasoning support, that enables to implement and tests the presented graphical language along with the needed SPARQL-DL support for solving queries with the user’s provided OWL 2 ontologies in any of its linearisations.X Workshop Innovación en Sistemas de Software (WISS)Red de Universidades con Carreras en Informática (RedUNCI

Towards Conceptual Modelling Interoperability in a Web Tool for Ontology Engineering

The definition of suitable visual paradigms for ontology modelling is still an open issue. Despite obvious differences between the expressiveness of conceptual modelling (CM) languages and ontologies, many proposed tools have been based on UML, EER and ORM. Additionally, all of these tools support only one CM as visual language, reducing even more their modelling capabilities. In previous works, we have presented crowd as a Web architecture for graphical ontology designing in UML and logical reasoning to verify the relevant properties of these models. The aim of this tool is to extend the reasoning capabilities on top of visual representations as much as possible. In this paper, we present an extended crowd architecture and a new prototype focusing on an ontology-driven metamodel to enable different CMs visual languages for ontology modelling. Thus facilitating inter-model assertions across models represented in different languages, converting between modelling languages and reasoning on them. Finally, we detail the new architecture and demonstrate the usage of the prototype with simple examples.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Towards Conceptual Modelling Interoperability in a Web Tool for Ontology Engineering

The definition of suitable visual paradigms for ontology modelling is still an open issue. Despite obvious differences between the expressiveness of conceptual modelling (CM) languages and ontologies, many proposed tools have been based on UML, EER and ORM. Additionally, all of these tools support only one CM as visual language, reducing even more their modelling capabilities. In previous works, we have presented crowd as a Web architecture for graphical ontology designing in UML and logical reasoning to verify the relevant properties of these models. The aim of this tool is to extend the reasoning capabilities on top of visual representations as much as possible. In this paper, we present an extended crowd architecture and a new prototype focusing on an ontology-driven metamodel to enable different CMs visual languages for ontology modelling. Thus facilitating inter-model assertions across models represented in different languages, converting between modelling languages and reasoning on them. Finally, we detail the new architecture and demonstrate the usage of the prototype with simple examples.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Towards a Visual SPARQL-DL Query Builder

Querying ontologies is an every-day activity that users need. This interaction will improve when the query is more expressive and easier to develop. For this purpose, a visual query language is an ideal mean for users and ontology engineers for creating queries taking advantage of the easy-to-understand and low time and cost characteristics, specially, for users which does not know textual query languages. On the other side, SPARQL-DL is a powerful and expressive textual query language for OWL-DL based ontologies that can combine TBox/ABox/RBox queries. Considering the advantage of both, we present in this work a visual query language that can be interpreted as SPARQL-DL sentences and thus being used for querying ontologies for its structure and/or instance information. Altogether, we use this idea to create a modified version of crowd, a Web modelling tool with reasoning support, that enables to implement and tests the presented graphical language along with the needed SPARQL-DL support for solving queries with the user’s provided OWL 2 ontologies in any of its linearisations.X Workshop Innovación en Sistemas de Software (WISS)Red de Universidades con Carreras en Informática (RedUNCI

Predicting melatonin suppression by light in humans:Unifying photoreceptor-based equivalent daylight illuminances, spectral composition, timing and duration of light exposure

Light‐induced melatonin suppression data from 29 peer‐reviewed publications was analysed by means of a machine‐learning approach to establish which light exposure characteristics (ie photopic illuminance, five α‐opic equivalent daylight illuminances [EDIs], duration and timing of the light exposure, and the dichotomous variables pharmacological pupil dilation and narrowband light source) are the main determinants of melatonin suppression. Melatonin suppression in the data set was dominated by four light exposure characteristics: (1) melanopic EDI, (2) light exposure duration, (3) pupil dilation and (4) S‐cone‐opic EDI. A logistic model was used to evaluate the influence of each of these parameters on the melatonin suppression response. The final logistic model was only based on the first three parameters, since melanopic EDI was the best single (photoreceptor) predictor that was only outperformed by S‐cone‐opic EDI for (photopic) illuminances below 21 lux. This confirms and extends findings on the importance of the metric melanopic EDI for predicting biological effects of light in integrative (human‐centric) lighting applications. The model provides initial and general guidance to lighting practitioners on how to combine spectrum, duration and amount of light exposure when controlling non‐visual responses to light, especially melatonin suppression. The model is a starting tool for developing hypotheses on photoreceptors’ contributions to light's non‐visual responses and helps identifying areas where more data are needed, like on the S‐cone contribution at low illuminances

Towards Conceptual Modelling Interoperability in a Web Tool for Ontology Engineering

The definition of suitable visual paradigms for ontology modelling is still an open issue. Despite obvious differences between the expressiveness of conceptual modelling (CM) languages and ontologies, many proposed tools have been based on UML, EER and ORM. Additionally, all of these tools support only one CM as visual language, reducing even more their modelling capabilities. In previous works, we have presented crowd as a Web architecture for graphical ontology designing in UML and logical reasoning to verify the relevant properties of these models. The aim of this tool is to extend the reasoning capabilities on top of visual representations as much as possible. In this paper, we present an extended crowd architecture and a new prototype focusing on an ontology-driven metamodel to enable different CMs visual languages for ontology modelling. Thus facilitating inter-model assertions across models represented in different languages, converting between modelling languages and reasoning on them. Finally, we detail the new architecture and demonstrate the usage of the prototype with simple examples.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Una arquitectura cliente-servidor para modelado conceptual asistido por razonamiento automático

Esta línea de investigación se desarrolla en forma colaborativa entre docentes-investigadores de la Universidad Nacional del Comahue y de la Universidad Nacional del Sur, en el marco de proyectos de investigación financiados por las universidades antes mencionadas. El objetivo general del trabajo de investigación es desarrollar una herramienta Web que permita la integración del soporte gráfico y el razonamiento automático en un ambiente de modelado conceptual. Se pretende trabajar en un arquitectura cliente-servidor y en la definición de un entorno gráfico con primitivas basadas en UML. De esta forma se podrán visualizar todas las deducciones relevantes modificando la apariencia del diagrama gráfico original y, dejando al usuario, la decisión de preservar o descartar dichos cambios.Eje: Innovación en Sistemas de SoftwareRed de Universidades con Carreras en Informática (RedUNCI

crowd: A Tool for Conceptual Modelling assisted by Automated Reasoning : Preliminary Report

There is an increment on the complexity of the information systems derived from new paradigms, for example Semantic Web, Big Data, e-government, etc. which require high quality solutions to tackle complex problems such as information integration. This quality is widely determined by the conceptual level. In this work, we present crowd as a novel tool for designing both conceptual models and ontologies based on visual representations with assistance of logic-based reasoning services. The challenge and the intention behind this work is to define graphicallogical methodologies as effective solutions for the description of interest domains at conceptual level. We detail the tool and demonstrate the usage of an initial prototype with some simple examples. Moreover, we identify limitations and potential issues about modelling and propose some partial solutions to tackle them. Currently, we are working to release the first beta version of crowd.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Towards a Visual SPARQL-DL Query Builder

Querying ontologies is an every-day activity that users need. This interaction will improve when the query is more expressive and easier to develop. For this purpose, a visual query language is an ideal mean for users and ontology engineers for creating queries taking advantage of the easy-to-understand and low time and cost characteristics, specially, for users which does not know textual query languages. On the other side, SPARQL-DL is a powerful and expressive textual query language for OWL-DL based ontologies that can combine TBox/ABox/RBox queries. Considering the advantage of both, we present in this work a visual query language that can be interpreted as SPARQL-DL sentences and thus being used for querying ontologies for its structure and/or instance information. Altogether, we use this idea to create a modified version of crowd, a Web modelling tool with reasoning support, that enables to implement and tests the presented graphical language along with the needed SPARQL-DL support for solving queries with the user’s provided OWL 2 ontologies in any of its linearisations.X Workshop Innovación en Sistemas de Software (WISS)Red de Universidades con Carreras en Informática (RedUNCI