Giving meaning to tweets in emergency situations: a semantic approach for filtering and visualizing social data

In this paper, we propose a semantic approach for monitoring information publishedon social networks about a specific event. In the era of Big Data, when an emergencyoccurs information posted on social networks becomes more and more helpful foremergency operators. As direct witnesses of the situation, people share photos, videosor text messages about events that call their attention. In the emergency operationcenter, these data can be collected and integrated within the management processto improve the overall understanding of the situation and in particular of the citizenreactions. To support the tracking and analyzing of social network activities, there arealready monitoring tools that combine visualization techniques with geographicalmaps. However, tweets are written from the perspective of citizens and the informationthey provide might be inaccurate, irrelevant or false. Our approach tries to dealwith data relevance proposing an innovative ontology-based method for filteringtweets and extracting meaningful topics depending on their semantic content. In thisway data become relevant for the operators to make decisions. Two real cases used totest its applicability showed that different visualization techniques might be neededto support situation awareness. This ontology-based approach can be generalizedfor analyzing the information flow about other domains of application changing theunderlying knowledge base.This work is supported by the project emerCien grant funded by the Spanish Ministry of Economy and Competitivity (TIN2012-09687)

SEMA4A : a knowledge base for accessible evacuation and alert notifications in emergencies

When an emergency occurs or is going to occur, the aim of organizations and agencies involved in the response phase is to restore quickly a safe situation and reduce the number of victims and damages. The notification of information about the kind of emergency, its characteristics, the location of safe places and available procedures for reaching them has a crucial role in order to facilitate the evacuation of citizens. Several organizations and agencies have been promoting the development of Information Technology (IT) tools, called Emergency Response Information Systems (ERIS) for the management of the activities performed in response to the emergencies. In particular, these systems provide modules for collecting, updating and notifying information about imminent disasters to potential affected people. Such notifications can be communicated through different channels, like websites, emails, text or voice messages. But to effectively inform people about an emergency, the notifications should be adapted automatically to each user’s profile (e.g. functional or contextual disabilities, elderly, children), the kind of emergency (e.g. typhoon, earthquake, tornado), the communication channel (e.g. PDAs, smartphones, pagers) and any other exceptional circumstances (e.g. interrupted roads, collapsed exit, dangerous area). For example, when a fire occurs in a building, a blind person should be alerted by audio signals or text messages (assuming she has a text-to-speech software on her device). Moreover, information can guide her to an assistant that can help her in reaching the exit. The efficacy of emergency notifications depends also on how different Emergency Notification Systems (ENS) communicate and interoperate with each other in order to share information even with different terminologies and types of disasters. For avoiding semantic incompatibilities, a common language is needed to improve the coordination not only among systems, but also among users. In fact, codifying the semantics of shared information in an accessible way could help citizens in interpreting notifications without misunderstandings and emergency operators in communicating among them. Modelling knowledge on alerting and evacuation processes, using expert systems, neural networks or ontologies, can help in personalizing emergency notifications and evacuation procedures. In particular, we posit that the knowledge base required for the personalization mechanism should cover at least four domains: accessibility, technology, emergency and evacuation procedures. These domains cover the factors to take into account for adapting the notifications. Consequently, the accessibility is considered a representation for the user’s profile, technology for the interactive devices and the communication channel, emergency for the characteristics of the situation and evacuation procedures for the escaping measures. In this thesis, we propose the design of an ontology called SEMA4A (Simple Emergency Alerts 4 [for] All). The ontology is a knowledge representation based on semantic rules that allows to model articulated knowledge through the definition of complex relations among concepts from different domains. This choice is also related to the possibility of using specific tools based on first order logic for verifying the validity and the integrity of the proposed representation. The development of the ontology has to meet the objectives that motivated this research work: consistency, completeness, understandability and interoperability with existent systems and protocols. For the consistency, we have run a reasoner tool called Pellet obtaining that there are not redundancies and the mapping is syntactically coherent. Concerning completeness and understandability, we have performed a quantitative and a qualitative evaluation. The goal of the quantitative evaluation is to compute three well-known functions in the domain of ontological engineering: precision, coverage and accuracy. These three measures evaluate how much the ontology is representative respect to the domains of interest (i.e. accessibility, emergency, evacuation and technology). In the qualitative evaluation, we have involved international experts in accessibility, evacuation and emergency to test the validity of the proposed mapping with respect to their expertise. Finally, the interoperability has been guaranteed codifying SEMA4A with a standard language called OWL (Ontology Web Language) and following formal recommendations published as an initiative of the W3C (World Wide Web Consortium). Taking into account the results obtained from the evaluations, we posit that the proposed ontology addresses needed information for sharing and integrating alert notifications about emergencies and evacuation procedures into existent solutions (i.e. notification mechanisms, information systems, communication protocols). As proof of this, we have developed three use cases in collaboration with the DEI Group of the University Carlos III of Madrid. SEMA4A has been applied for adapting available information considering several factors: the user’s profile, the kind of emergency, the communication channel and other exceptional circumstances. The first use case, called CAPONES, sends emergency alerts adapting the content and the visualization to the needs of involved users. The second system is NERES which aims at generating and notifying personalized evacuation routes. The last case is the EmergenSYS platform that provides three different mobile tools for sending alerts in two directions: from citizens to emergency operators and from emergency operators to citizens. -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Durante una emergencia, el objetivo de las organizaciones y agencias involucradas es de responder a la misma para restaurar rápidamente una situación segura y reducir el número de las víctimas y los daños. En este ámbito es fundamental enviar a los ciudadanos afectados notificaciones sobre la emergencia especificando el tipo, las características, la ubicación de los lugares seguros y cómo llegar a ellos. De esta forma se pueden facilitar el desalojo y la evacuación de la área peligrosa. Varias organizaciones y agencias han estado colaborando en el desarrollo de los Sistemas Informativos para la Gestión de Emergencias (SIGEs). Estos sistemas proporcionan deferentes servicios basados en las Tecnologías de la Información y la Comunicación (TIC). Uno de ellos es la gestión de la información relacionada con la situación y su consecuente notificación a los ciudadanos a través de diferentes canales, como por ejemplo sitios web, correos electrónicos, mensajes de voz y texto. Para que las notificaciones sean efectivas, es necesario proporcionar un mecanismo de personalización que adapte automáticamente la información a enviar teniendo en cuenta el perfil de cada usuario (por ejemplo, discapacidades funcionales o contextuales, ancianos y niños), el tipo de emergencia (por ejemplo, incendios, terremotos y tornados), el canal de comunicación (por ejemplo dispositivos móviles, dispositivos inteligentes y correo electrónicos) y cualquier otra circunstancia que se pueda considerar relevante (por ejemplo, carreteras cortadas o colapsadas y zonas peligrosas). Por ejemplo, cuando se produce un incendio en un edificio, una persona invidente puede ser alertada por una señal audio o un mensaje de texto si tiene instalado en su teléfono un convertidor de texto a voz. No solo el tipo de alerta, si no también el contenido de la misma tiene que adaptarse. En el caso del invidente, la información recibida le guiará hacia un asistente que le pueda ayudar a llegar a la salida. La eficacia de las notificaciones de emergencia depende también de cómo los diferentes SIGEs comunican y colaboran entre sí con el fin de compartir información. En este caso, hay que tener en cuenta que cada sistema podría utilizar una terminología diferente. Para evitar cualquier incompatibilidad semántica, se necesita un lenguaje común con el objetivo de mejorar la comunicación no sólo entre los SIGEs, sino también hacia los usuarios. De esta forma, se evitarían posibles malentendidos en la interpretación de la información recibida por parte de los ciudadanos y compartida entre los operadores de emergencia. Una posible solución a esta necesidad consiste en modelar el conocimiento sobre las alertas de emergencias y los procesos de evacuación desarrollando un sistema basado en la inteligencia artificial, como por ejemplo sistemas expertos, redes neuronales u ontologías. En particular, se considera que el conocimiento a modelar necesario para definir el mecanismo de personalización debería cubrir por lo menos lo siguientes cuatros dominios: accesibilidad , tecnología, emergencia y evacuación. Cada uno de estos dominios representa un factor especifico de la personalización. La accesibilidad se refiere a las características definidas en el perfil del usuario. La tecnología contiene los tipos de dispositivos y el canal utilizados para recibir información. La emergencia representa todo lo que se conoce sobre la situación critica mientras la evacuación incluye los procedimientos y las medidas a tomar para evacuar. En esta tesis, se propone el diseño de una ontología llamada SEMA4A (Simple Emergency Alerts 4 [for] All, Alertas de Emergencias Simples para Todos). La ontología es una representación de una área de conocimiento basada en la definición de reglas semánticas. A través de estas reglas, es posible definir modelos complejos que relacionen conceptos provenientes de diferentes dominios. Además, el uso de ontologías nos permite aplicar una serie de herramientas basadas en la lógica del primer orden para verificar la validez y la integridad de la representación resultante. El diseño de la ontología tiene que cumplir con los objetivos que han motivado este trabajo: la coherencia, la integridad, la comprensión y la interoperabilidad con los sistemas y los protocolos existentes. Cada una de estas propiedades ha sido evaluada utilizando técnicas especificas. Para la coherencia, se ha utilizado un razonador llamado Pellet. El resultado obtenido confirma que la definición de los conceptos y de las relaciones incluidas en SEMA4A ses semanticamente coherente. En cuanto a la integridad y la comprensión, hemos realizado dos tipos de evaluación: una cuantitativa y otra cualitativa. El objetivo de la evaluación cuantitativa es calcular tres funciones ya conocidas en el campo de la ingeniería ontológica: cover, accuracy y precision. Estas funciones nos permiten medir cuanto la ontología es representativa para los dominios de interés. En el ámbito de la evaluación cualitativa, hemos involucrado a expertos internacionales en materia de accesibilidad, evacuación y emergencia para qué opinen sobre SEMA4A y su valor respecto a la experiencia propia de cada uno. Por último, se ha cumplido con la interoperabilidad implementando SEMA4A con un lenguaje estándar llamado OWL (Ontology Web Language, Lenguaje Web para Ontologías) y siguiendo las lineas guías publicadas como iniciativa de la W3C (World Wide Web Consortium). Teniendo en cuenta los resultados obtenidos al finalizar las evaluaciones, finalmente podemos afirmar que la ontología propuesta en esta tesis puede ser utilizada por otros SIGEs para personalizar y compartir la información disponible sobre situaciones de emergencia y procedimientos de evacuación. Como prueba de ello, hemos desarrollado tres casos de uso en colaboración con el Grupo de DEI de la Universidad Carlos III de Madrid. SEMA4A se ha aplicado como parte del mecanismo de adaptación de la información disponible teniendo en cuenta el perfil del usuario, el tipo de emergencia, el canal de comunicación y otras circunstancias excepcionales. El primer caso de uso, llamado CAPONES, envía alertas de emergencia personalizando el contenido y la visualización del mensaje (texto, imágenes o realidad aumentada) para mejor cumplir con las necesidades de los usuarios involucrados. El segundo sistema es NERES cuyo objetivo es adaptar y notificar las rutas de evacuación respecto al plano de emergencia oficial. El último caso es la plataforma EmergenSYS que ofrece tres aplicaciones móviles diferentes. La primera permite a los ciudadanos de notificar incidentes al centro de operaciones en calidad de testigos o victimas. La segunda es un botón de pánico que el ciudadano puede presionar para que automáticamente llegue una notificación al centro de operaciones. La tercera permite a los ciudadanos recibir información útil acerca de una emergencia cercana, incluyendo también la ruta de evacuación personalizada

SEMA4A: An ontology for emergency notification systems accessibility

This is the post-print version of the final paper published in Expert Systems with Applications. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2009 Elsevier B.V.Providing alert communication in emergency situations is vital to reduce the number of victims. Reaching this goal is challenging due to users’ diversity: people with disabilities, elderly and children, and other vulnerable groups. Notifications are critical when an emergency scenario is going to happen (e.g. a typhoon approaching) so the ability to transmit notifications to different kind of users is a crucial feature for such systems. In this work an ontology was developed by investigating different sources: accessibility guidelines, emergency response systems, communication devices and technologies, taking into account the different abilities of people to react to different alarms (e.g. mobile phone vibration as an alarm for deafblind people). We think that the proposed ontology addresses the information needs for sharing and integrating emergency notification messages over distinct emergency response information systems providing accessibility under different conditions and for different kind of users.Ministerio de Educación y Cienci

From social networks to emergency operation centers: A semantic visualization approach

Social networks are commonly used by citizens as a communication channel for sharing their messages about a crisis situation and by emergency operation centers as a source of information for improving their situation awareness. However, to utilize this source of information, emergency operators and decision makers have to deal with large and unstructured data, the content, reliability, quality, and relevance of which may vary greatly. In this paper, to address this challenge, we propose a visual analytics solution that filters and visualizes relevant information extracted from Twitter. The tool offers multiple visualizations to provide emergency operators with different points of view for exploring the data in order to gain a better understanding of the situation and take informed courses of action. We analyzed the scope of the problem through an exploratory study in which 20 practitioners answered questions about the integration of social networks in the emergency management process. This study inspired the design of a visualization tool, which was evaluated in a controlled experiment to assess its effectiveness for exploring spatial and temporal data. During the experiment, we asked 12 participants to perform 5 tasks related to data exploration and fill a questionnaire about their experience using the tool. One of the most interesting results obtained from the evaluation concerns the effectiveness of combining several visualization techniques to support different strategies for solving a problem and making decisions.This work was supported by the project PACE grant funded by the Spanish Ministry of Economy and Competitivity [TIN2016-77690-R]

Molecular and cellular logic of cerebral cortex development, evolution, and disease

Editorial on the Research Topic Molecular and cellular logic of cerebral cortex development, evolution, and diseas

Designing Mobile Applications for Emergency Response: Citizens Acting as Human Sensors

When an emergency occurs, citizens can be a helpful support for the operation centers involved in the response activities. As witnesses to a crisis, they initially can share updated and detailed information about what is going on. Moreover, thanks to the current technological evolution people are able to quickly and easily gather rich information and transmit it through different communication channels. Indeed, modern mobile devices embed several sensors such as GPS receivers, Wi-Fi, accelerometers or cameras that can transform users into well-equipped human sensors. For these reasons, emergency organizations and small and medium enterprises have demonstrated a growing interest in developing smart applications for reporting any exceptional circumstances. In this paper, we present a practical study about this kind of applications for identifying both limitations and common features.This work is supported by the project emerCien grant funded by the Spanish Ministry of Economy and Competitivity (TIN2012-09687)

Visually-Enabled Active Deep Learning for (Geo) Text and Image Classification: A Review

This paper investigates recent research on active learning for (geo) text and image classification, with an emphasis on methods that combine visual analytics and/or deep learning. Deep learning has attracted substantial attention across many domains of science and practice, because it can find intricate patterns in big data; but successful application of the methods requires a big set of labeled data. Active learning, which has the potential to address the data labeling challenge, has already had success in geospatial applications such as trajectory classification from movement data and (geo) text and image classification. This review is intended to be particularly relevant for extension of these methods to GISience, to support work in domains such as geographic information retrieval from text and image repositories, interpretation of spatial language, and related geo-semantics challenges. Specifically, to provide a structure for leveraging recent advances, we group the relevant work into five categories: active learning, visual analytics, active learning with visual analytics, active deep learning, plus GIScience and Remote Sensing (RS) using active learning and active deep learning. Each category is exemplified by recent influential work. Based on this framing and our systematic review of key research, we then discuss some of the main challenges of integrating active learning with visual analytics and deep learning, and point out research opportunities from technical and application perspectives-for application-based opportunities, with emphasis on those that address big data with geospatial components

Personalized Alert Notifications and Evacuation Routes in Indoor Environments

The preparedness phase is crucial in the emergency management process for reaching an adequate level of readiness to react to potential threats and hazards. During this phase, emergency plans are developed to establish, among other procedures, evacuation and emergency escape routes. Information and Communication Technologies (ICT) can support and improve these procedures providing appropriate, updated and accessible information to all people in the affected zone. Current emergency management and evacuation systems do not adapt information to the context and the profile of each person, so messages received in the emergency might be useless. In this paper, we propose a set of criteria that ICT-based systems could achieve in order to avoid this problem adapting emergency alerts and evacuation routes to different situations and people. Moreover, in order to prove the applicability of such criteria, we define a mechanism that can be used as a complement of traditional evacuation systems to provide personalized alerts and evacuation routes to all kinds of people during emergency situations in working places. This mechanism is composed by three main components: CAP-ONES for notifying emergency alerts, NERES for defining emergency plans and generating personalized evacuation routes, and iNeres as the interface to receive and visualize these routes on smartphones. The usability and understandability of proposed interface has been assessed through a user study performed in a fire simulation in an indoor environment. This evaluation demonstrated that users considered iNeres easy to understand, to learn and to use, and they also found very innovative the idea to use smartphones as a support for escaping instead of static signals on walls and doors

Interactive Accessible Notifications for Emergency Notification Systems

5th International Conference, UAHCI 2009, Held as Part of HCI International 2009, San Diego, CA, USA, July 19-24, 2009Notifications are critical when an emergency scenario is going to happen (e.g. a hurricane approaching); so the ability to transmit notifications to different kind of users is a crucial feature for Emergency Management Systems. In this work an ontology was developed by investigating different sources: accessibility guidelines, emergency response systems, communication devices and technologies, taking into account the different abilities of people to react to different alarms (e.g. mobile phone vibration as an alarm for deaf blind people). The knowledge codified in the proposed ontology could be used to enhance and promote the use of non-conventional interfaces for notifying emergency messages thus providing accessibility under different conditions and for different kind of users.This work is funded by the project UIA4SIGE (TSI2007-03394) supported by the [Spanish] Ministry of Education and by an agreement with the DGPCE of the [Spanish] Ministry of Interior.Publicad

Human Neural Stem Cell Systems to Explore Pathogen-Related Neurodevelopmental and Neurodegenerative Disorders

Building and functioning of the human brain requires the precise orchestration and execution of myriad molecular and cellular processes, across a multitude of cell types and over an extended period of time. Dysregulation of these processes affects structure and function of the brain and can lead to neurodevelopmental, neurological, or psychiatric disorders. Multiple environmental stimuli affect neural stem cells (NSCs) at several levels, thus impairing the normal human neurodevelopmental program. In this review article, we will delineate the main mechanisms of infection adopted by several neurotropic pathogens, and the selective NSC vulnerability. In particular, TORCH agents, i.e., Toxoplasma gondii, others (including Zika virus and Coxsackie virus), Rubella virus, Cytomegalovirus, and Herpes simplex virus, will be considered for their devastating effects on NSC self-renewal with the consequent neural progenitor depletion, the cellular substrate of microcephaly. Moreover, new evidence suggests that some of these agents may also affect the NSC progeny, producing long-term effects in the neuronal lineage. This is evident in the paradigmatic example of the neurodegeneration occurring in Alzheimer's disease