Search results

The purpose of this paper is to visualize the collaboration network among regions in library science (LS) in China. Using various methods and tools of social network analysis and geographical visualization, results were obtained, showing the structure and patterns of research collaborations in topological and geographical views, as well as the geographical distributions of contribution.

The sample includes all studies published in the top journal in library science in China from 2006 to 2015. First, co-occurrence data representing collaborations among regions was extracted from author affiliations. Second, the topological network of collaboration was generated by applying social network analysis tools and descriptive statistics, network indicators of the collaboration network and research communities were calculated. Third, the topological network was projected into a geographical map with corresponding coordinates and distances using geographical tools. Finally, the topological network maps and the geographical maps were produced for visualization.

The levels of contribution are very unbalanced between regions, and overall research collaboration is low. Beijing, Hubei and several other areas are central and significant regions in China; other regions are mostly connected with central ones through direct collaborations. Research collaborations in LS research in China are mostly distributed in the east and south of China, being centralized in the “Beijing–Hubei–Shanghai” triangle zone, as well as within the triangle’s extending zones. Finally, there are three distinct research communities that connect closely within themselves and loosely between them. The Beijing community is relatively centralized in geography, while other communities are scattered.

This study applied various methods and tools of social network analysis and geographical mapping analysis to reveal the collaboration structure and patterns among regions in LS research in China. Visualized maps in topological and geographical views help shed new light on research efforts.

Big Data introduces high amounts and new forms of structured, unstructured and semi-structured data into the field of accounting and this requires alternative data management and reporting methods. Generating insights from these new data sources highlight the need for different and interactive forms of visualization in the field of visual analytics. Nonetheless, a considerable gap between the recommendations in research and the current usage in practice is evident. In order to understand and overcome this gap, a detailed analysis of the status quo as well as the identification of potential barriers for adoption is vital. The paper aims to discuss this issue.

A survey with 145 business accountants from Austrian companies from a wide array of business sectors and all hierarchy levels has been conducted. The survey is targeted toward the purpose of this study: identifying barriers, clustered as human-related and technological-related, as well as investigating current practice with respect to interactive visualization use for Big Data.

The lack of knowledge and experience regarding new visualization types and interaction techniques and the sole focus on Microsoft Excel as a visualization tool can be identified as the main barriers, while the use of multiple data sources and the gradual implementation of further software tools determine the first drivers of adoption.

Due to the data collection with a standardized survey, there was no possibility of dealing with participants individually, which could lead to a misinterpretation of the given answers. Further, the sample population is Austrian, which might cause issues in terms of generalizing results to other geographical or cultural heritages.

The study shows that those knowledgeable and familiar with interactive Big Data visualizations indicate high perceived ease of use. It is, therefore, necessary to offer sufficient training as well as user-centered visualizations and technological support to further increase usage within the accounting profession.

A lot of research has been dedicated to the introduction of novel forms of interactive visualizations. However, little focus has been laid on the impact of these new tools for Big Data from a practitioner’s perspective and their needs.

The purpose of this paper is to reveal the structure and patterns of cross-national collaborations in Big Data research through application of various social network analysis and geographical visualization methods.

The sample includes articles containing Big Data research, covering all years, in the Web of Science Core Collection as of December 2015. First, co-occurrence data representing collaborations among nations were extracted from author affiliations. Second, the descriptive statistics, network indicators of collaborations, and research communities were calculated. Third, topological network maps, geographical maps integrated with topological network projections, and proportional maps were produced for visualization.

The results show that the scope of international collaborations in Big Data research is broad, but the distribution among nations is unbalanced and fragmented. The USA, China, and the UK were identified as the major contributors to this research area. Five research communities are identified, led by the USA, China, Italy, South Korea, and Brazil. Collaborations within each community vary, reflecting different levels of research development. The visualizations show that nations advance in Big Data research are centralized in North America, Europe, and Asia-Pacific.

This study applied various informetric methods and tools to reveal the collaboration structure and patterns among nations in Big Data research. Visualized maps help shed new light on global research efforts.

Observes, while most school site management personnel are familiar with the multitude of visual representations of statistical data, via graphs and charts, the value of visual representations of geographical information remains largely unknown in educational management. Explains that geographical information systems (GIS), in addition to determining the exact geographical street address location of a client, can also overlay important SES, thematic information such as demographic characteristics (per capita household income, percentage, minority, etc.), and man‐made, and when natural geographical barriers are combined a powerful visual representation or picture of a client service area emerges. Describes how these visual representations of educational service areas can then be used to support educational policy analysis and school site management. Presents several illustrations of how GIS mapping procedures can be applied to school site management, planning and policy analysis. Draws three illustrations of GIS mapping from the school management areas of co‐ordination of school site outreach services to educational policy areas of ensuring “equity” in access to instructional services. Explores extensions of GIS mapping procedures to other areas in educational policy analysis and school site management.

The continuous development of information technology leads to intelligent education research. In the context of internationalisation, the study aims to understand the relevant research status worldwide, research similarities and differences that need to be discovered, and research frontiers that need to be explored.

Web of Science (WoS) core collection was used as the data source, descriptive statistical analysis, geographic data visualisation and coupling analysis are used to reveal coupling relationships, present a cooperative situation and discover research frontiers.

Intelligent education research has been widely carried out in countries around the world, and there is extensive scientific research cooperation. According to coupling analysis results, the coupling strength of bibliographic between countries has been continuously improved, while the coupling strength of keywords has remained balanced, and there is standardisation and diversity of research.

The weakness of the research lies in the limitations of the data sources. Important research achievements on a certain topic in many non-English speaking countries are usually published in native journals. In the future research direction, more coupling analysis objects can be carried out, such as focussing on authors and institutions.

Through the coupling analysis of country bibliographic and keywords, it reveals the consistency and divergence of intelligent education research between different countries at different time spans.

Design and implement country bibliographic coupling (CBC) and country keyword coupling (CKC) strength indicators to calculate the strength of coupling between countries.

The purpose of this paper is to examine whether and how a methodological coupling of visualisations of trace data and interview methods can be utilised for information practices studies.

Trace data visualisation enquiry is suggested as the coupling of visualising exported data from an information system and using these visualisations as basis for interview guides and elicitation in information practices research. The methodology is illustrated and applied through a small-scale empirical study of a citizen science project.

The study found that trace data visualisation enquiry enabled fine-grained investigations of temporal aspects of information practices and to compare and explore temporal and geographical aspects of practices. Moreover, the methodology made possible inquiries for understanding information practices through trace data that were discussed through elicitation with participants. The study also found that it can aid a researcher of gaining a simultaneous overarching and close picture of information practices, which can lead to theoretical and methodological implications for information practices research.

Trace data visualisation enquiry extends current methods for investigating information practices as it enables focus to be placed on the traces of practices as recorded through interactions with information systems and study participants' accounts of activities.

The purpose of this paper is to explore the data connection, spatial distribution characteristics and trends in genealogical information. First, it implements a spatial-temporal visualization of the Hakka genealogical information system that makes these individual family pedigree charts appear as one seamless genealogy to family and researchers seeking connections and family history all over the world. Second, this study applies migration analysis by applying big data technologies to Hakka genealogies to investigate the migration patterns of the Hakka ethnic group in Taiwan between 1954 and 2014. This innovative library service enhances the Hakka genealogical migration analysis using big data.

The platform is designed for the exchange of genealogical data to be used in big data analysis. This study integrates big data and geographic information systems (GIS) to map the population distribution themes. The general procedure included collecting genealogical big data, geographic encoding, gathering the map information, GIS layer integration and migration map production.

The analytical results demonstrate that big data technology is highly appropriate for family migration history analysis, given the increasing volume, velocity and variety of genealogical data. The spatial-temporal visualization of the genealogical research platform can follow family history and migration paths, and dynamically generate roadmaps to simplify the cartographic steps.

Technology that combines big data and GIS is suitable for performing migration analysis based on genealogy. A web-based application for spatial-temporal genealogical information also demonstrates the contribution of innovative library services.

Big data play a dominant role in library services, and in turn, provide an active library service. These findings indicate that big data technology can provide a suitable tool for improving library services.

Online genealogy and family trees are linked with large-volume, growing data sets that are complex and have multiple, autonomous sources. The migration analysis using big data has the potential to help genealogy researchers to construct minority ethnic history.

Starting from a critical analysis of the main criteria currently used to identify marginal areas, this paper aims to propose a new classification model of such territories by leveraging knowledge discovery approaches and knowledge visualization techniques, which represent a fundamental pillar in the knowledge-based urban development process.

The methodology adopted in this study relies on the design science research, which includes five steps: problem identification, objective definition, solution design and development, demonstration and evaluation.

Results demonstrate how to exploit knowledge discovery and visualization to obtain multiple mappings of inner areas, in the aim to identify good practices and optimize resources to set up more effective territorial development strategies and plans. The proposed approach overcomes the traditional way adopted to map inner areas that uses a single indicator (i.e. the distance between a municipality and the nearest pole where it is possible to access to education, health and transportation services) and leverages seven groups of indicators that represent the distinguishing features of territories (territorial capital, social costs, citizenship, geo-demography, economy, innovation and sustainable development).

The proposed model could be enriched by new variables, whose value can be collected by official sources and stakeholders engaged to provide both structured and unstructured data. Also, another enhancement could be the development of a cross-algorithms comparison that may reveal useful to suggest which algorithm can better suit the needs of policy makers or practitioners.

This study sets the ground for proposing a decision support tool that policy makers can use to classify in a new way the inner areas, thus overcoming the current approach and leveraging the distinguishing features of territories.

This study shows how the availability of distributed knowledge sources, the modern knowledge management techniques and the emerging digital technologies can provide new opportunities for the governance of a city or territory, thus revitalizing the domain of knowledge-based urban development.

Construction activities, particularly related to transportation, have a considerable impact on the environment and air quality. This paper aims to present a geographic information systems (GIS) and computer‐aided design (CAD)‐based approach for visualizing, communicating and analysing greenhouse gas (GHG) emissions resulting from construction activities.

A methodology using GIS is developed to graphically represent spatial aspects of construction. The approach adopted involves use of a 3D model developed in CAD environment, which was synchronized with a construction schedule stored in Excel spreadsheets. GIS environment is used to link spatial and scheduling information relevant to GHG emissions from construction activities. A baseline was created to enable effective monitoring of construction emissions.

The presented GIS model has the potential to enhance visualisation of distribution and dynamic variations of GHG emissions and could help stakeholders better analyse and understand how construction activities impact the environment.

This paper presents a novel method of graphically presenting GHG and other hazardous air emissions from construction activities using a GIS‐based approach. The paper presents the result of comparing the 3D surface representation of simulated estimated and actual construction emissions to show the impact of construction activities on the environment to support the engineering analysis and decision‐making process.

Globalization, the ever-increasing worldwide flow of ideas, practices, and material objects resulting in increasing interdependency between people and nations across the globe, has numerous interrelated economic, political, cultural, ideological, environmental, and technological facets.

In an effort to make the elusive and multifaceted concept of globalization more tangible and measurable, different instruments have been developed, usually in the form of “indexes” based on quantitative data. These indexes mainly result in rankings of individual cities as well as whole countries with respect to their supposed level of globalization. Some items of the existing indexes to measure the level of globalization of nation states or cities refer to phenomena that are to some extent visually observable, but many aspects and manifestations of globalization escape these rather crude operationalizations.

Visual approaches to globalization help to enrich and complement the more abstract and mainly quantitatively supported discourses around this multifaceted phenomenon. They may provide valid and unobtrusive ways to assess and understand the impact of culture and cultural exchange in the daily lives of inhabitants of cities around the world and add a unique “localized,” cross-cultural empirical perspective to the many divergent views and discussions about the presumed beneficial or detrimental nature of these processes. An ‘in situ’ visual approach to globalization may help to uncover the “real life” impact and the specific contexts of these processes at different locations. This chapter discusses different options for researching globalization and cultural change in cities.