Social Machines

The term ‘social machine’ has recently been coined to refer to Web-based systems that support a variety of socially-relevant processes. Such systems (e.g., Wikipedia, Galaxy Zoo, Facebook, and reCAPTCHA) are progressively altering the way a broad array of social activities are performed, ranging from the way we communicate and transmit knowledge, establish romantic partnerships, generate ideas, produce goods and maintain friendships. They are also poised to deliver new kinds of intelligent processing capability by virtue of their ability to integrate the complementary contributions of both the human social environment and a global nexus of distributed computational resources. This chapter provides an overview of recent research into social machines. It examines what social machines are and discusses the kinds of social machines that currently exist. It also presents a range of issues that are the focus of current research attention within the Web Science community

Using Windmill Expansion for Document Retrieval

SEMIOTIKS aims to utilise online information to support the crucial decision–making of those military and civilian agencies involved in the humanitarian removal of landmines in areas of conflict throughout the world. An analysis of the type of information required for such a task has given rise to four main areas of research: information retrieval, document annotation, summarisation and visualisation. The first stage of the research has focused on information retrieval, and a new algorithm, “Windmill Expansion” (WE) has been proposed to do this. The algorithm uses retrieval feedback techniques for automated query expansion in order to improve the effectiveness of information retrieval. WE is based on the extraction of human–generated written phases for automated query expansion. Top and Second Level expansion terms have been generated and their usefulness evaluated. The evaluation has concentrated on measuring the degree of overlap between the retrieved URLs. The less the overlap, the more useful the information provided. The Top Level expansion terms were found to provide 90% of useful URLs, and the Second Level 83% of useful URLs. Although there was a decline of useful URLs from the Top Level to the Second Level, the quantity of relevant information retrieved has increased. The originality of SEMIOTIKS lies in its use of the WE algorithm to help non–domain specific experts automatically explore domain words for relevant and precise information retrieval

NITELIGHT: A Graphical Tool for Semantic Query Construction

Query formulation is a key aspect of information retrieval, contributing to both the efficiency and usability of many semantic applications. A number of query languages, such as SPARQL, have been developed for the Semantic Web; however, there are, as yet, few tools to support end users with respect to the creation and editing of semantic queries. In this paper we introduce a graphical tool for semantic query construction (NITELIGHT) that is based on the SPARQL query language specification. The tool supports end users by providing a set of graphical notations that represent semantic query language constructs. This language provides a visual query language counterpart to SPARQL that we call vSPARQL. NITELIGHT also provides an interactive graphical editing environment that combines ontology navigation capabilities with graphical query visualization techniques. This paper describes the functionality and user interaction features of the NITELIGHT tool based on our work to date. We also present details of the vSPARQL constructs used to support the graphical representation of SPARQL queries

Context-Aware Information Retrieval for Enhanced Situation Awareness

In the coalition forces, users are increasingly challenged with the issues of information overload and correlation of information from heterogeneous sources. Users might need different pieces of information, ranging from information about a single building, to the resolution strategy of a global conflict. Sometimes, the time, location and past history of information access can also shape the information needs of users. Information systems need to help users pull together data from disparate sources according to their expressed needs (as represented by system queries), as well as less specific criteria. Information consumers have varying roles, tasks/missions, goals and agendas, knowledge and background, and personal preferences. These factors can be used to shape both the execution of user queries and the form in which retrieved information is packaged. However, full automation of this daunting information aggregation and customization task is not possible with existing approaches. In this paper we present an infrastructure for context-aware information retrieval to enhance situation awareness. The infrastructure provides each user with a customized, mission-oriented system that gives access to the right information from heterogeneous sources in the context of a particular task, plan and/or mission. The approach lays on five intertwined fundamental concepts, namely Workflow, Context, Ontology, Profile and Information Aggregation. The exploitation of this knowledge, using appropriate domain ontologies, will make it feasible to provide contextual assistance in various ways to the work performed according to a user’s taskrelevant information requirements. This paper formalizes these concepts and their interrelationships

Web-Based Knowledge Extraction and the Cognitive Characterization of Cultural Groups

The advent of Web 2.0 has provided new opportunities for cultural analysts to understand more about the cognitive characteristics of cultural groups. In particular, user-contributed content provides important indications as to the beliefs, attitudes and values of cultural groups, and this is an important focus of attention for those concerned with the development of cognitively-relevant models. In order to support the exploitation of the Web in the context of cultural modeling activities, it is important to deal with both the large-scale nature of the Web and the current dominance of natural language formats. In this paper, we outline an approach to support the exploitation of the Web in the context of cultural modeling activities. The approach begins with the development of qualitative cultural models (which describe the beliefs, concepts and values of cultural groups), and these models are subsequently used to develop an ontology-based information extraction capability (which harvests model-relevant information from online textual resources). We are currently developing a system to support the approach, and the continued development of this system should enable cultural analysts to more fully exploit the Web for the purpose of developing more accurate, detailed and predictively-relevant cognitive models

A Controlled Natural Language Interface for Semantic Media Wiki

Despite their potential value as collaborative knowledge editing systems, semantic wikis present a number of usability challenges for human end users. In particular, there are several mismatches between the simple user interaction mechanisms of wikis (which are the key to the success of wikis) and the need for users to create, edit and understand structured knowledge content (e.g., in the form of RDF or OWL ontologies). In this paper, we present a Controlled Natural Language (CNL) approach to collaborative ontology development using Semantic MediaWiki (SMW). In order to support the expressivity required for OWL ontology development, we extended the representational substructure of the SMW system with an OWL meta model using a template-based mechanism. To improve usability, we provided a form-based guided input interface and implemented several CNL verbalizers (CNL text generation components). In particular, we developed verbalizers for the English and Chinese variants of the Rabbit CNL, as well as the Attempto Controlled English (ACE) CNL. The combination of semantic wiki systems and CNL editing interfaces may provide an effective mechanism for promoting the large-scale collaborative creation of semantically-enriched online content

The Extended Mind and Network-Enabled Cognition

In thinking about the transformative potential of network technologies with respect to human cognition, it is common to see network resources as playing a largely assistive or augmentative role. In this paper we propose a somewhat more radical vision. We suggest that the informational and technological elements of a network system can, at times, constitute part of the material supervenience base for a human agent’s mental states and processes. This thesis (called the thesis of network-enabled cognition) draws its inspiration from the notion of the extended mind that has been propounded in the philosophical and cognitive science literature. Our basic claim is that network systems can do more than just augment cognition; they can also constitute part of the physical machinery that makes mind and cognition mechanistically possible. In evaluating this hypothesis, we identify a number of issues that seem to undermine the extent to which contemporary network systems, most notably the World Wide Web, can legitimately feature as part of an environmentally-extended cognitive system. Specific problems include the reliability and resilience of network-enabled devices, the accessibility of online information content, and the extent to which network-derived information is treated in the same way as information retrieved from biological memory. We argue that these apparent shortfalls do not necessarily merit the wholesale rejection of the network-enabled cognition thesis; rather, they point to the limits of the current state-of-the-art and identify the targets of many ongoing research initiatives in the network and information sciences. In addition to highlighting the importance of current research and technology development efforts, the thesis of network-enabled cognition also suggests a number of areas for future research. These include the formation and maintenance of online trust relationships, the subjective assessment of information credibility and the long-term impact of network access on human psychological and cognitive functioning. The nascent discipline of web science is, we suggest, suitably placed to begin an exploration of these issues

The Cognitive Virtues of Dynamic Networks

For the most part, studies in the network science literature tend to focus on networks whose functional connectivity is largely invariant with respect to some episode of collective information processing. In the real world, however, networks with highly dynamic functional topologies tend to be the norm. In order to improve our understanding of the effect of dynamic networks on collective cognitive processing, we explored the problem-solving abilities of synthetic agents in dynamic networks, where the links between agents were progressively added throughout the problem-solving process. The results support the conclusion that (at least in some task contexts) dynamic networks contribute to a better profile of problem-solving performance compared to static networks (whose topologies are fixed throughout the course of information processing). Furthermore, the results suggest that constructive networks (like those used in the present study) strike a productive balance between autonomy and social influence. When agents are allowed to operate independently at the beginning of a problem-solving process, and then later allowed to communicate, the result is often a better profile of collective performance than if extensive communication had been permitted from the very outset of the problem-solving process. These results are relevant, we suggest, to a range of phenomena, such as groupthink, the common knowledge effect and production blocking, all of which have been observed in group problem-solving contexts

A Data-Intensive Lightweight Semantic Wrapper Approach to Aid Information Integration

We argue for the flexible use of lightweight ontologies to aid information integration. Our proposed approach is grounded on the availability and exploitation of existing data sources in a networked environment such as the world wide web (instance data as it is commonly known in the description logic and ontology community). We have devised a mechanism using Semantic Web technologies that wraps each existing data source with semantic information, and we refer to this technique as SWEDER (Semantic Wrapping of Existing Data Sources with Embedded Rules). This technique provides representational homogeneity and a firm basis for information integration amongst these semantically enabled data sources. This technique also directly supports information integration though the use of context ontologies to align two or more semantically wrapped data sources and capture the rules that define these integrations. We have tested this proposed approach using a simple implementation in the domain of organisational and communication data and we speculate on the future directions for this lightweight approach to semantic enablement and contextual alignment of existing network-available data sources

Semantic Web Techniques to Support Interoperability in Distributed Networked Environments

We explore two Semantic Web techniques arising from ITA research into semantic alignment and interoperability in distributed networks. The first is POAF (Portable Ontology Aligned Fragments) which addresses issues relating to the portability and usage of ontology alignments. POAF uses an ontology fragmentation strategy to achieve portability, and enables subsequent usage through a form of automated ontology modularization. The second technique, SWEDER (Semantic Wrapping of Existing Data sources with Embedded Rules), is grounded in the creation of lightweight ontologies to semantically wrap existing data sources, to facilitate rapid semantic integration through representational homogeneity. The semantic integration is achieved through the creation of context ontologies which define the integrations and provide a portable definition of the integration rules in the form of embedded SPARQL construct clauses. These two Semantic Web techniques address important practical issues relevant to the potential future adoption of ontologies in distributed network environments