From Searching to Using: Making Sense of Digital Cultural Heritage Collections

The rise of digital cultural heritage has seen the creation of a vast number of collections, which provide access to large amounts of data. While initially access to this data was provided only via keyword-based search interfaces, there has been increased interest in exploratory interfaces to support open-ended search tasks. However, finding information that interests the user is only the first step and the next step must be to provide interfaces that allow the user to actually make use of the information they have found. Towards this goal a novel sense-making workbench is presented in this paper, which enables the user to aggregate information from multiple collections, arrange them into a sense-making structure, and export them for their final use

GPS-MIV: The General Purpose System for Multi-display Interactive Visualization

The new age of information has created opportunities for inventions like the internet. These inventions allow us access to tremendous quantities of data. But, with the increase in information there is need to make sense of such vast quantities of information by manipulating that information to reveal hidden patterns to aid in making sense of it. Data visualization systems provide the tools to reveal patterns and filter information, aiding the processes of insight and decision making. The purpose of this thesis is to develop and test a data visualization system, The General Purpose System for Multi-display Interactive Visualization (GPS-MIV). GPS-MIV is a software system allowing the user to visualize data graphically and interact with it. At the core of the system is a graphics system that displays different computer generated scenes from multiple perspectives and with multiple views. Additionally, GSP-MIV provides interaction for the user to explore the scene

STUDENT’S ATTITUDE TOWARDS DICTIONARY AND ITS USAGE : A Case of Study for English Department Students Diponegoro University

In learning a foreign language, dictionary is one of learning aids to assist students in making decision about making sense of words in usage –in the target language. This research is conducted to discover how English Department students in Universitas Diponegoro perceive dictionary and use it to assist meaning discovery. The data in this paper is obtained from returned questionnaires previously distributed across four academic years in. The results show that dictionary is not the primary source of English vocabulary intake. Most dictionaries are bilingual (English-Indonesian or Indonesian-English), and may take the form of printed or electronic dictionary. We also discovered that the respondents tend to choose a dictionary based on the number of words listed. Further clarifications of the respondents’ answers indicate the preference of vocabulary intake, where dictionary is not a priority. Bilingual dictionaries are preferred as compared to monolingual ones with the assumption that they are easier to understand. Although the definition of word is still very loose, students seem to be more attracted to dictionaries, which claim to have vast number of entries. For practical purposes, portable dictionary or application dictionary is more preferred as they support mobility. From the results, we may conclude that dictionaries are used by the respondents with restriction in meaning discovery. We suggest that they take it to the next level, where existing linguistic features from dictionaries might also be used to assist writing

Visualizing and animating large-scale spatiotemporal data with ELBAR explorer

Visual exploration of data enables users and analysts observe interesting patterns that can trigger new research for further investigation. With the increasing availability of Linked Data, facilitating support for making sense of the data via visual exploration tools for hypothesis generation is critical. Time and space play important roles in this because of their ability to illustrate dynamicity, from a spatial context. Yet, Linked Data visualization approaches typically have not made efficient use of time and space together, apart from typical rather static multivisualization approaches and mashups. In this paper we demonstrate ELBAR explorer that visualizes a vast amount of scientific observational data about the Brazilian Amazon Rainforest. Our core contribution is a novel mechanism for animating between the di↵erent observed values, thus illustrating the observed changes themselves

On the value of data mining tools

Improvements in ICTs lead to increasingly high bandwidth becoming widely available, allowing large volumes of data to be moved easily over vast distances. CEOs, CIOs, CFOs and managers in organisations can access increasingly large volumes of data to provide a knowledge basis for making important decisions. As the volume of data grows, making sense it becomes increasingly difficult. Data mining is used to extract useful knowledge from large, fuzzy datasets. There are many different data mining models, such as decision trees, neural networks, clustering, prediction, K-nearest neighbour, and association analysis.Many software vendors have developed data mining tools, based on sophisticated algorithms. To understand how these algorithms work requires considerable technical knowledge that is beyond many IT practitioners. This paper poses the question of how much value such tools are to practitioners who do not have the technical background to fully understand the software and interpret the results.This issue is investigated by comparing two tools based on the decision tree model. Preliminary results suggest that current data mining tools are of limited value to users without considerable knowledge of statistics and data mining

Business Intelligence, Analytics And Data Visualization: A Heat Map Project Tutorial

Business intelligence and analytics (BI&A) initiatives are helping countless organizations harness and interpret the vast amount of information available in the world today. The explosion of BI&A in industry has fueled the high demand for knowledge workers with advanced analytical skills. The purpose of this paper is to introduce a data visualization project tutorial for Information Systems (IS) education. The applied BI&A tutorial was designed to help students learn how to create and analyze a heat map using SQL Server Data Tools (SSDT) and SQL Server Reporting Services (SSRS). Students learn how to make decisions based on large amounts of data by presenting it in visual form. This tutorial exposes students to the decision-making power derived from data visualization. Utilizing the 5E Instructional Model, the tutorial assists in the development of BI&A professionals who can quickly make sense of mass amounts of data, identify trends buried within data sets, and are skilled in making sound decisions that add value to organizations

Visualizing data: why an (interactive) picture is worth 1000 numbers

lectureOne of the most striking and unique aspects about this moment in human history is the amount of data we are generating. This data holds the promise of unlocking the mysteries of the universe, untangling complex natural and man-made systems, and allowing us to live longer, healthier, and more productive lives. But generating data is only the first step - developing methods to make sense of vast collections of information is now widely considered the major challenge. A key component of addressing this challenge is visualization, which supports sense making by representing data as pictures and supporting exploration through human-computer interactions. Through the design of intuitive representations of data, visualization designers arc able to harness our perceptual system for quickly finding interesting patterns and trends in a sea of data, instead of relying on our more limited memory and cognition. Creating effective visualizations, however, relies on a combination of knowledge about computer science, design, application domains, and how people internalize the meaning of data. This talk discusses what we know about how to design effective, interactive visualizations, as well as some of the open challenges left to solve. It will also provide examples of how scientists use these tools to glean insight from complex data

Artificial Intelligence and Big Data Analytics in Support of Cyber Defense

Cybersecurity analysts rely on vast volumes of security event data to predict, identify, characterize, and deal with security threats. These analysts must understand and make sense of these huge datasets in order to discover patterns which lead to intelligent decision making and advance warnings of possible threats, and this ability requires automation. Big data analytics and artificial intelligence can improve cyber defense. Big data analytics methods are applied to large data sets that contain different data types. The purpose is to detect patterns, correlations, trends, and other useful information. Artificial intelligence provides algorithms that can reason or learn and improve their behavior, and includes semantic technologies. A large number of automated systems are currently based on syntactic rules which are generally not sophisticated enough to deal with the level of complexity in this domain. An overview of artificial intelligence and big data technologies in cyber defense is provided, and important areas for future research are identified and discussed

SYSTEMATIC LITERATURE REVIEW: DATA STANDARDIZATION IN HEALTH INFORMATION SYSTEMS

Digitalization within the healthcare sector has resulted in the accumulation of vast amounts of data that can be utilized towards the improvement of health outcomes. Meaningful use of such data, however, requires that it is standardized. Standardization plays a key role in providing a universal language for data that is exchanged through different health systems. Through a systematic literature review, this paper identifies practices that are vital for an effective standardization process. Ontological development, governance and organizational practices are identified as pertinent to the process of standardization and are analyzed and explained through the lens of a multi-thread social activity model by Fomin et al. (2003). This model provides a comprehensive view of related aspects of design, sense-making, and negotiation. The analysis shows that all these aspects take place in all stages of the standardization process, and they are highly dependent on each other and can occur simultaneously

Investigating the Use of Creative Mask-Making as a Means to Explore Professional Identity of Doctoral Psychology Students

The goal of this qualitative study is two-fold: to explore doctoral psychology students\u27 current sense of self-identity as clinicians (nearing graduation) and their future sense of who they hope to become as practicing clinical psychologists using a creative arts methodology and to illustrate how the use of creative arts processes have clinical relevance for not only mental health clinicians and psychologists but also educators. Seven doctoral psychology students nearing graduation participated (individually) in a guided imagery and mask-making experience and in a phenomenological, semi-structured, in-depth interview following the art making. Through the use of Interpretative Phenomenological Analysis (IPA), an integrative, hermeneutically and phenomenologically-based interpretive research method used to analyze the narrative data, this study explored how the participants\u27 experiences as doctoral students and who they hope to become as future clinical psychologists (Domain 1—Doctoral student as future psychologist) and their experiences about art-making and what they learned about themselves during the process (Domain 2—Guided visualization and art-making as catalysts). Results from the domain “Doctoral Student as future psychologist” suggest that the doctoral psychology students nearing graduation often feel overwhelmed with the multitude of remaining tasks and obligations influencing their ability to make future career plans and that their primary focus for the future is hope that they will have a sense of greater self-agency and a more balanced life. Results from the second domain, “Guided visualization and art-making as catalysts” indicated that the vast majority of participants appreciated the creative arts/mask-making process and also were surprised about how much they learned about themselves, how the process helped them gain insight into their own identities as future psychologists and their understanding of their own struggles while in graduate school, and provided the participants with an increased understanding about how creative arts processes can be incorporated in the field of psychology for a means of exploration of ideas and problems, not only in a mental health setting with a client but also in an educational setting for use with future doctoral students. The electronic version of this dissertation is at AURA: Antioch University Repository and Archive, http://aura.antioch.edu/ and OhioLINK ETD Center, https://etd.ohiolink.ed