Volume 34, Number 3, September 2014 OLAC Newsletter

Digitized September 2014 issue of the OLAC Newsletter

ID5.2 Roadmap for KRSM RTD

Roadmap for KRSM RTD activities.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

Big Data Computing for Geospatial Applications

The convergence of big data and geospatial computing has brought forth challenges and opportunities to Geographic Information Science with regard to geospatial data management, processing, analysis, modeling, and visualization. This book highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates opportunities for using big data for geospatial applications. Crucial to the advancements highlighted in this book is the integration of computational thinking and spatial thinking and the transformation of abstract ideas and models to concrete data structures and algorithms

Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019

One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingly see the creation of knowledge graphs that capture information about the entirety of a class of entities. [...] This grand challenge extends this further by asking if we can create a knowledge graph of "everything" ranging from common sense concepts to location based entities. This knowledge graph should be "open to the public" in a FAIR manner democratizing this mass amount of knowledge." Although linked open data (LOD) is one knowledge graph, it is the closest realisation (and probably the only one) to a public FAIR Knowledge Graph (KG) of everything. Surely, LOD provides a unique testbed for experimenting and evaluating research hypotheses on open and FAIR KG. One of the most neglected FAIR issues about KGs is their ongoing evolution and long term preservation. We want to investigate this problem, that is to understand what preserving and supporting the evolution of KGs means and how these problems can be addressed. Clearly, the problem can be approached from different perspectives and may require the development of different approaches, including new theories, ontologies, metrics, strategies, procedures, etc. This document reports a collaborative effort performed by 9 teams of students, each guided by a senior researcher as their mentor, attending the International Semantic Web Research School (ISWS 2019). Each team provides a different perspective to the problem of knowledge graph evolution substantiated by a set of research questions as the main subject of their investigation. In addition, they provide their working definition for KG preservation and evolution

A new integrated model for multitasking during web searching

Investigating multitasking information behaviour, particularly while using the web, has become an increasingly important research area. People s reliance on the web to seek and find information has encouraged a number of researchers to investigate the characteristics of information seeking behaviour and the web seeking strategies used. The current research set out to explore multitasking information behaviour while using the web in relation to people s personal characteristics, working memory, and flow (a state where people feel in control and immersed in the task). Also investigated were the effects of pre-determined knowledge about search tasks and the artefact characteristics. In addition, the study also investigated cognitive states (interactions between the user and the system) and cognitive coordination shifts (the way people change their actions to search effectively) while multitasking on the web. The research was exploratory using a mixed method approach. Thirty University students participated; 10 psychologists, 10 accountants and 10 mechanical engineers. The data collection tools used were: pre and post questionnaires, pre-interviews, a working memory test, a flow state scale test, audio-visual data, web search logs, think aloud data, observation, and the critical decision method. Based on the working memory test, the participants were divided into two groups, those with high scores and those with lower scores. Similarly, participants were divided into two groups based on their flow state scale tests. All participants searched information on the web for four topics: two for which they had prior knowledge and two more without prior knowledge. The results revealed that working memory capacity affects multitasking information behaviour during web searching. For example, the participants in the high working memory group and high flow group had a significantly greater number of cognitive coordination and state shifts than the low working memory group and low flow group. Further, the perception of task complexity was related to working memory capacity; those with low memory capacity thought task complexity increased towards the end of tasks for which they had no prior knowledge compared to tasks for which they had prior knowledge. The results also showed that all participants, regardless of their working memory capacity and flow level, had the same the first frequent cognitive coordination and cognitive state sequences: from strategy to topic. In respect of disciplinary differences, accountants rated task complexity at the end of the web seeking procedure to be statistically less significant for information tasks with prior knowledge compared to the participants from the other disciplines. Moreover, multitasking information behaviour characteristics such as the number of queries, web search sessions and opened tabs/windows during searches has been affected by the disciplines. The findings of the research enabled an exploratory integrated model to be created, which illustrates the nature of multitasking information behaviour when using the web. One other contribution of this research was to develop new more specific and closely grounded definitions of task complexity and artefact characteristics). This new research may influence the creation of more effective web search systems by placing more emphasis on our understanding of the complex cognitive mechanisms of multitasking information behaviour when using the web

Understanding Children’s Help-Seeking Behaviors: Effects of Domain Knowledge

This dissertation explores children’s help-seeking behaviors and use of help features when they formulate search queries and evaluate search results in IR systems. This study was conducted with 30 children who were 8 to 10 years old. The study was designed to answer three research questions with two parts in each: 1(a) What are the types of help-seeking situations experienced by children (8-10 years old) when they formulate search queries in a search engine and a kid-friendly web portal?, 1(b) What are the types of help-seeking situations experienced by children (8-10 years old) when they evaluate search results in a search engine and a kid-friendly web portal?, 2(a) What types of help features do children (8-10 years old) use and desire when they formulate search queries in a search engine and a kid-friendly web portal?, 2(b) What types of help features do children (8-10 years old) use and desire when they evaluate search results in a search engine and a kid-friendly web portal?, 3(a) How does children’s (8-10 years old) domain knowledge affect their help seeking and use of help features when they formulate search queries in a search engine and a kid-friendly web portal?, 3(b) How does children’s (8-10 years old) domain knowledge affect their help seeking and use of help features when they evaluate search results in a search engine and a kid-friendly web portal? This study used multiple data collection methods including performance-based domain knowledge quizzes as direct measurement, domain knowledge self-assessments as indirect measurement, pre-questionnaires, transaction logs, think-aloud protocols, observations, and post-interviews. Open coding analysis was used to examine children’s help-seeking situations. Children’s cognitive, physical, and emotional types of help-seeking situations when using Google and Kids.gov were identified. To explore help features children use and desire when they formulate search queries and evaluate results in Google and Kids.gov, open coding analysis was conducted. Additional descriptive statistics summarized the frequency of help features children used when they formulated search queries and evaluated results in Google and Kids.gov. Finally, this study investigated the effect of children’s domain knowledge on their help seeking and use of help features in using Google and Kids.gov based on linear regression. The level of children’s self-assessed domain knowledge affects occurrences of their help-seeking situations when they formulated search queries in Google. Similarly, children’s domain knowledge quiz scores showed a statistically significant effect on occurrences of their help-seeking situations when they formulated keywords in Google. In the stage of result evaluations, the level of children’s self-assessed domain knowledge influenced their use of help features in Kids.gov. Furthermore, scores of children’s domain knowledge quiz affected their use of help features when they evaluated search results in Kids.gov. Theoretical and practical implications for reducing children’s cognitive, physical, and emotional help-seeking situations when they formulate search queries and evaluate search results in IR systems were discussed based on the results

E-CRM and CMS systems: potential for more dynamic businesses

Any change in customer’s behaviour affects the customer’s value. In addition, profitability and economic viability also change. Most companies still do not know entirely their customer base characteristics. They find difficult to define criteria that segment their customer base to find high-value customers. They need to focus on target selections to carry on with marketing campaigns which involve high investments. Given the potential of e-CRM and CMS as powerful tools to guide customer-oriented understanding and analysis, greater attention is required. Several companies, operating within the same business and having access to the same information and technology, differ in e-CRM performance. Without sufficient evidence, managers are prone to making investment decisions that are neither efficient nor effective. So it is imperative to base the decision of e-CRM and CMS adoption, on not only their analytical power, but also on economic viability criteria for sustainable business dynamic