Visualizing the semantic content of large text databases using text maps

A methodology for generating text map representations of the semantic content of text databases is presented. Text maps provide a graphical metaphor for conceptualizing and visualizing the contents and data interrelationships of large text databases. Described are a set of experiments conducted against the TIPSTER corpora of Wall Street Journal articles. These experiments provide an introduction to current work in the representation and visualization of documents by way of their semantic content

Knowledge Organization Systems (KOS) in the Semantic Web: A Multi-Dimensional Review

Since the Simple Knowledge Organization System (SKOS) specification and its SKOS eXtension for Labels (SKOS-XL) became formal W3C recommendations in 2009 a significant number of conventional knowledge organization systems (KOS) (including thesauri, classification schemes, name authorities, and lists of codes and terms, produced before the arrival of the ontology-wave) have made their journeys to join the Semantic Web mainstream. This paper uses "LOD KOS" as an umbrella term to refer to all of the value vocabularies and lightweight ontologies within the Semantic Web framework. The paper provides an overview of what the LOD KOS movement has brought to various communities and users. These are not limited to the colonies of the value vocabulary constructors and providers, nor the catalogers and indexers who have a long history of applying the vocabularies to their products. The LOD dataset producers and LOD service providers, the information architects and interface designers, and researchers in sciences and humanities, are also direct beneficiaries of LOD KOS. The paper examines a set of the collected cases (experimental or in real applications) and aims to find the usages of LOD KOS in order to share the practices and ideas among communities and users. Through the viewpoints of a number of different user groups, the functions of LOD KOS are examined from multiple dimensions. This paper focuses on the LOD dataset producers, vocabulary producers, and researchers (as end-users of KOS).Comment: 31 pages, 12 figures, accepted paper in International Journal on Digital Librarie

The Potency Of Metacognitive Learning To Foster Mathematical Logical Thinking

The ability of thinking logically needs to be developed due to the fact that it is an essential basic skill. Logical thinking affects that giving reason must be true, and that a sequence of assumptions is based on the high truth value. Mathematics is a subject that functions to train students to think logically. The understanding of logic will help students to arrange the proof that support through process to finally arrive at a conclusion. Currently, metacognition is viewed as an essential element of learning. It refers to someone knowledge of processes and the result itself or of that connected to the process. Metacognition is needed when student solves the task that needs argumentation and logical understanding. In order to help student to skillful think logically, mathematics learning must be designed as such so that the condition will raise the skill of metacognitive acts. Key words: metacognitive learning, mathematical logical thinkin

Expert and Lay Mental Models of Ecosystems: Inferences for Risk Communication

The authors evaluate a mental modeling approach to studying differences between lay and expert comprehension of ecosystems

The KINDRA project. Sharing and evaluating groundwater research and knowledge in Europe

Groundwater knowledge and research in the European Union is often scattered and non-standardised, because of different subjects involved and different approaches from Member States. The Horizon2020 project KINDRA has conducted an EU-wide assessment of existing groundwater-related practical and scientific knowledge based on a new Hydrogeological Research Classification System, identifying more than 280 keywords related to three main categories (namely Operational Actions, Research topics and Societal Challenges) to be intersected in a 3D-diagram approach. The classification is supported by a web-service, the European Inventory of Groundwater Research, which acts not only as knowledge repository but also as a tool to help identify relevant researchm topics, existing research trends and critical research challenges. The records have been uploaded during the project by 20 national experts from National Associations of Geologists, under the umbrella of the European Federation of Geologists. The total number of metadata included in the inventory at the end of the project are about 2300, and the analysis of the results is considered useful for producing synergies, implementing policies and optimising water management in Europe. By the use of additional indicators, the database content has been analysed by occurrence of keywords, type of document, level of innovation. Using the three-axes classification, more easily understandable by 2D diagrams as bubble plots, occurrence and relationship of different topics (main categories) in groundwater research have been highlighted. This article summarizes the activities realized in relation to the common classification system and to the metadata included in the EIGR, showing the distribution of thecollected information in different categories and attributes identified by the classification

RED: Deep Recurrent Neural Networks for Sleep EEG Event Detection

The brain electrical activity presents several short events during sleep that can be observed as distinctive micro-structures in the electroencephalogram (EEG), such as sleep spindles and K-complexes. These events have been associated with biological processes and neurological disorders, making them a research topic in sleep medicine. However, manual detection limits their study because it is time-consuming and affected by significant inter-expert variability, motivating automatic approaches. We propose a deep learning approach based on convolutional and recurrent neural networks for sleep EEG event detection called Recurrent Event Detector (RED). RED uses one of two input representations: a) the time-domain EEG signal, or b) a complex spectrogram of the signal obtained with the Continuous Wavelet Transform (CWT). Unlike previous approaches, a fixed time window is avoided and temporal context is integrated to better emulate the visual criteria of experts. When evaluated on the MASS dataset, our detectors outperform the state of the art in both sleep spindle and K-complex detection with a mean F1-score of at least 80.9% and 82.6%, respectively. Although the CWT-domain model obtained a similar performance than its time-domain counterpart, the former allows in principle a more interpretable input representation due to the use of a spectrogram. The proposed approach is event-agnostic and can be used directly to detect other types of sleep events.Comment: 8 pages, 5 figures. In proceedings of the 2020 International Joint Conference on Neural Networks (IJCNN 2020

FIVES: An integrated strategy for comprehension and vocabulary learning

This article describes a strategy that emphasizes the integration of all language and literacy skills for learning across content areas as well as the importance CCSS place on learners’ ability to ask questions about information, phenomena, or ideas encountered (Ciardiello, 2012/2013). FIVES is a strategy that meaningfully integrates research-based methodologies associated with reading, writing, speaking, listening, viewing, and visually representing for differentiated disciplinary literacy instruction related to authentic texts and issues. The strategy described can be universally applied across disciplines to develop high levels of competence with literacy processes and content

Development and Evaluation of "Where Are We?" Map-Skills Software and Curriculum

The "Where are We?" software and lessons are designed to help children in grades two through four learn to "translate" between the visually-perceived world that they sense around them, and the schematic representation of that landscape on a map. Field-based tests were developed to examine students' ability to absorb information in the real world and to transfer it onto a map and, conversely, the ability to absorb information from a map and transfer it into an action in the real world. Formative evaluation of a prototype version of "Where are We?" resulted in the following improvements in the instructional materials: more and prompter feedback for students, additional assessment tools for teachers, development of lessons to model successful map-using strategies, development of lessons to overcome common misconceptions, and replacement of text-based instructions with a voiceover demo. Educational levels: Graduate or professional