3,316 research outputs found
Educational Technology as Seen Through the Eyes of the Readers
In this paper, I present the evaluation of a novel knowledge domain
visualization of educational technology. The interactive visualization is based
on readership patterns in the online reference management system Mendeley. It
comprises of 13 topic areas, spanning psychological, pedagogical, and
methodological foundations, learning methods and technologies, and social and
technological developments. The visualization was evaluated with (1) a
qualitative comparison to knowledge domain visualizations based on citations,
and (2) expert interviews. The results show that the co-readership
visualization is a recent representation of pedagogical and psychological
research in educational technology. Furthermore, the co-readership analysis
covers more areas than comparable visualizations based on co-citation patterns.
Areas related to computer science, however, are missing from the co-readership
visualization and more research is needed to explore the interpretations of
size and placement of research areas on the map.Comment: Forthcoming article in the International Journal of Technology
Enhanced Learnin
Networks of reader and country status: An analysis of Mendeley reader statistics
The number of papers published in journals indexed by the Web of Science core
collection is steadily increasing. In recent years, nearly two million new
papers were published each year; somewhat more than one million papers when
primary research papers are considered only (articles and reviews are the
document types where primary research is usually reported or reviewed).
However, who reads these papers? More precisely, which groups of researchers
from which (self-assigned) scientific disciplines and countries are reading
these papers? Is it possible to visualize readership patterns for certain
countries, scientific disciplines, or academic status groups? One popular
method to answer these questions is a network analysis. In this study, we
analyze Mendeley readership data of a set of 1,133,224 articles and 64,960
reviews with publication year 2012 to generate three different kinds of
networks: (1) The network based on disciplinary affiliations of Mendeley
readers contains four groups: (i) biology, (ii) social science and humanities
(including relevant computer science), (iii) bio-medical sciences, and (iv)
natural science and engineering. In all four groups, the category with the
addition "miscellaneous" prevails. (2) The network of co-readers in terms of
professional status shows that a common interest in papers is mainly shared
among PhD students, Master's students, and postdocs. (3) The country network
focusses on global readership patterns: a group of 53 nations is identified as
core to the scientific enterprise, including Russia and China as well as two
thirds of the OECD (Organisation for Economic Co-operation and Development)
countries.Comment: 26 pages, 6 figures (also web-based startable), and 2 table
Usage Bibliometrics
Scholarly usage data provides unique opportunities to address the known
shortcomings of citation analysis. However, the collection, processing and
analysis of usage data remains an area of active research. This article
provides a review of the state-of-the-art in usage-based informetric, i.e. the
use of usage data to study the scholarly process.Comment: Publisher's PDF (by permission). Publisher web site:
books.infotoday.com/asist/arist44.shtm
Open Knowledge Maps: Creating a Visual Interface to the World’s Scientific Knowledge Based on Natural Language Processing
The goal of Open Knowledge Maps is to create a visual interface to the world’s scientific knowledge. The base for this visual interface consists of so-called knowledge maps, which enable the exploration of existing knowledge and the discovery of new knowledge. Our open source knowledge mapping software applies a mixture of summarization techniques and similarity measures on article metadata, which are iteratively chained together. After processing, the representation is saved in a database for use in a web visualization. In the future, we want to create a space for collective knowledge mapping that brings together individuals and communities involved in exploration and discovery. We want to enable people to guide each other in their discovery by collaboratively annotating and modifying the automatically created maps.Das Ziel von Open Knowledge Map ist es, ein visuelles Interface zum wissenschaftlichen Wissen der Welt bereitzustellen. Die Basis für die dieses Interface sind sogenannte “knowledge maps”, zu deutsch Wissenslandkarten. Wissenslandkarten ermöglichen die Exploration bestehenden Wissens und die Entdeckung neuen Wissens. Unsere Open Source Software wendet für die Erstellung der Wissenslandkarten eine Reihe von Text Mining Verfahren iterativ auf die Metadaten wissenschaftlicher Artikel an. Die daraus resultierende Repräsentation wird in einer Datenbank für die Anzeige in einer Web-Visualisierung abgespeichert. In Zukunft wollen wir einen Raum für das kollektive Erstellen von Wissenslandkarten schaffen, der die Personen und Communities, welche sich mit der Exploration und Entdeckung wissenschaftlichen Wissens beschäftigen, zusammenbringt. Wir wollen es den NutzerInnen ermöglichen, einander in der Literatursuche durch kollaboratives Annotieren und Modifizieren von automatisch erstellten Wissenslandkarten zu unterstützen
APREGOAR: Development of a geospatial database applied to local news in Lisbon
Project Work presented as the partial requirement for obtaining a Master's degree in Geographic Information Systems and ScienceHá informações valiosas em formato de texto não estruturado sobre a localização, calendarização
e a essências dos eventos disponíveis no conteúdo de notícias digitais. Vários
trabalhos em curso já tentam extrair detalhes de eventos de fontes de notícias digitais,
mas muitas vezes não com a nuance necssária para representar com precisão onde as
coisas realmente acontecem. Alternativamente, os jornalistas poderiam associar manualmente
atributos a eventos descritos nos seus artigos enquanto publicam, melhorando a
exatidão e a confiança nestes atributos espaciais e temporais. Estes atributos poderiam
então estar imediatamente disponíveis para avaliar a cobertura temática, temporal e
espacial do conteúdo de uma agência, bem como melhorar a experiência do utilizador
na exploração do conteúdo, fornecendo dimensões adicionais que podem ser filtradas.
Embora a tecnologia de atribuição de dimensões geoespaciais e temporais para o
emprego de aplicaçãoes voltadas para o consumidor não seja novidade, tem ainda de
ser aplicada à escala das notícias. Além disso, a maioria dos sistemas existentes suporta
apenas uma definição pontual da localização dos artigos, que pode não representar bem
o(s) local(is) real(ais) dos eventos descritos.
Este trabalho define uma aplicação web de código aberto e uma base de dados
espacial subjacente que suporta i) a associação de múltiplos polígonos a representar
o local onde cada evento ocorre, os prazos associados aos eventos, em linha com os
atributos temáticos tradicionais associados aos artigos de notícias; ii) a contextualização
de cada artigo através da adição de mapas de eventos em linha para esclarecer aos
leitores onde os eventos do artigo ocorrem; e iii) a exploração dos corpora adicionados
através de filtros temáticos, espaciais e temporais que exibem os resultados em mapas
de cobertura interactivos e listas de artigos e eventos.
O projeto foi aplicado na área da grande Lisboa de Portugal. Para além da funcionalidade
acima referida, este projeto constroi gazetteers progressivos que podem ser
reutilizados como associações de lugares, ou para uma meta-análise mais aprofundada
do lugar, tal como é percebido coloquialmente. Demonstra a facilidade com que estas
dimensões adicionais podem ser incorporadas com grade confiança na precisão da definição, geridas, e alavancadas para melhorar a gestão de conteúdo das agências noticiosas,
a compreensão dos leitores, a exploração dos investigadores, ou extraídas para
combinação com outros conjuntos dos dados para fornecer conhecimentos adicionais.There is valuable information in unstructured text format about the location, timing,
and nature of events available in digital news content. Several ongoing efforts already
attempt to extract event details from digital news sources, but often not with the
nuance needed to accurately represent the where things actually happen. Alternatively,
journalists could manually associate attributes to events described in their articles while
publishing, improving accuracy and confidence in these spatial and temporal attributes.
These attributes could then be immediately available for evaluating thematic, temporal,
and spatial coverage of an agency’s content, as well as improve the user experience of
content exploration by providing additional dimensions that can be filtered.
Though the technology of assigning geospatial and temporal dimensions for the
employ of consumer-facing applications is not novel, it has yet to be applied at scale to
the news. Additionally, most existing systems only support a single point definition of
article locations, which may not well represent the actual place(s) of events described
within.
This work defines an open source web application and underlying spatial database
that supports i) the association of multiple polygons representing where each event
occurs, time frames associated with the events, inline with the traditional thematic
attributes associated with news articles; ii) the contextualization of each article via the
addition of inline event maps to clarify to readers where the events of the article occur;
and iii) the exploration of the added corpora via thematic, spatial, and temporal filters
that display results in interactive coverage maps and lists of articles and events.
The project was applied to the greater Lisbon area of Portugal. In addition to the
above functionality, this project builds progressive gazetteers that can be reused as place
associations, or for further meta analysis of place as it is colloquially understood. It
demonstrates the ease of which these additional dimensions may be incorporated with a
high confidence in definition accuracy, managed, and leveraged to improve news agency
content management, reader understanding, researcher exploration, or extracted for
combination with other datasets to provide additional insights
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