Xiaoyue Ma

From action icon to knowledge icon: Objective-oriented icon taxonomy in computer science

Abstract Icon plays a critical role in computer interface design. Studies on icon taxonomy explain the way in which various types of icon represent the objects and provide designers creation rules by which icons are more in line with users’ cognitive psychology. However, along with larger and larger use of icons, the previous classification criterion causes the boundary between categories blur. What’s more, Single classification standard is not able to well illustrate the icons applied in today’s computer applications. The purpose of this paper is to present an objective-oriented icon taxonomy which proposes to categorize icons into action icon and knowledge icon. To assess this proposition, we analyzed a sample of icons that applied in computer interface and suggest precise application domains to both action icon and knowledge icon categories. The results of this practice manifested that action icon and knowledge icon implied a high relation with applied environment and explicated the development trace of computer icons. This work is one of the first to point out the notion of knowledge icon and to highlight the importance of objective of icon application. Findings in this paper could enrich icon use in computer interface design, especially provides possible way to improve online knowledge sharing by visual tool like icon.

Semantically structured VDL-Based iconic tags system

Iconic tags system based on Visual Distinctive Language has been developed and assessed improving tagging effectiveness by considering tagging quality and tagging speed. This amelioration benefits from semiotic interpretation of tag meaning and graphical code of tag structure. To make in-depth research about this special iconic tags system, we study tags arrangement in this paper and hypothesized that semantically arranged iconic tags would imply better tagging results. A supplementary experiment was taken place by comparison between randomly and semantically arrangement method, which has validated our hypothesis.

Visual Distinctive Language: Using a Hypertopic-Based Iconic Tagging System for Knowledge Sharing

Tagging systems for social semantic web centralize and provide the tags that can be employed in classifying, sharing and seeking knowledge on the web for personal or organizational use. However, an increased variety of vocabularies and languages cause connections between tags and documents marked by these textual tags to become less and less distinctive, making the use and reuse of tagging systems even harder. In this paper, we present an approach of Visual Distinctive Language to improve the representation of tags and their structure. This approach was also evaluated by a control experiment with an observation of tagging process, the results of which have validated our hypothesis.

Graphically structured icons for knowledge tagging

Knowledge organization systems need tags to centralize and provide the keywords that can be employed in classifying, sharing and seeking knowledge for personal or organizational use. However, the increased variety of vocabularies and languages causes the connections between textual tags and the documents marked by them to become less and less distinctive. The purpose of this paper is to present an exploratory study on new type of knowledge tags: structured iconic tags. This kind of tag is created based on the special graphical rule – Visual Distinctive Language (VDL) – and has particular focus on the representation of tag structure. A ‘tagging on paper’ experiment was conducted to compare tagging results among three types of tags: textual tags, iconic tags without explicit structure and VDL-based iconic tags. Experimental results demonstrated that the new type of iconic tags improves the representation of tag structure as well as the interpretation of tag meaning. This work is one of the first to investigate how icons would be applied for tagging and what kind of graphical code would better represent knowledge organization. Findings in this paper could enrich the tagging method, which in turn provides a possible way to develop a visual knowledge organization system and iconic tag clouds for digital library.

Iconic categorization with knowledge-based “icon systems” can improve collaborative KM

Icon system could represent an efficient solution for collective iconic categorization of knowledge by providing graphical interpretation. Their pictorial characters assist visualizing the structure of text to become more understandable beyond vocabulary obstacle. In this paper we are proposing a Knowledge Engineering (KM) based iconic representation approach. We assume that these systematic icons improve collective knowledge management. Meanwhile, text (constructed under our knowledge management model - Hypertopic) helps to reduce the diversity of graphical understanding belonging to different users. This “position paper” also prepares to demonstrate our hypothesis by an “iconic social tagging” experiment which is to be accomplished in 2011 with UTT students. We describe the “socio semantic web” information portal involved in this project, and a part of the icons already designed for this experiment in Sustainability field. We have reviewed existing theoretical works on icons from various origins, which can be used to lay the foundation of robust “icons systems”.

VDL-based iconic co-annotation in crisis management

Crisis management is typical collaborative work which requires multi types of actors to cooperate in decision making. Crisis Clever System (CCS) is a decision making environment based on emergency experience feedback and provides situation base for later cases. Co-annotation may be needed to remark resources in the situation base or cooperate in decision making when crisis occurs. Iconic co-annotation is meaningful to this map-based cooperative work and is supposed to improve the interpretation of situations described in CCS. In this paper, a VDL-based iconic co-annotation method is presented for crisis management. It is assumed to better express multi-understanding of situations in CCS and to improve the communication quality when cooperating in real CCS-based crisis management.

Collaboratively constructing a VDL-Based icon system for knowledge tagging

Tag system for a knowledge organization system centralizes and provides the tags that can be employed in classifying, sharing and seeking knowledge for personal or organizational use within a social community. Considering current constraints of textual tag system and developing iconic tag system, VDL-based iconic tag system has been built and validated to improve knowledge tagging with symbolic interpretation and graphical organization of tag structure. In this paper, we are proposing cooperative creation of such special icon system where VDL-based icons will be applied for social knowledge tagging and sharing. This VDL-based icon system could also serve as a visual knowledge organization system to facilitate icon searching in a given context.