Collaborative Exploration and Sensemaking of Big Environmental Sound Data

Many ecologists are using acoustic monitoring to study animals and the health of ecosystems. Technological advances mean acoustic recording of nature can now be done at a relatively low cost, with minimal disturbance, and over long periods of time. Vast amounts of data are gathered yielding environmental soundscapes which requires new forms of visualization and interpretation of the data. Recently a novel visualization technique has been designed that represents soundscapes using dense visual summaries of acoustic patterns. However, little is known about how this visualization tool can be employed to make sense of soundscapes. Understanding how the technique can be best used and developed requires collaboration between interface, algorithm designers and ecologists. We empirically investigated the practices and needs of ecologists using acoustic monitoring technologies. In particular, we investigated the use of the soundscape visualization tool by teams of ecologists researching endangered species detection, species behaviour, and monitoring of ecological areas using long duration audio recordings. Our findings highlight the opportunities and challenges that ecologists face in making sense of large acoustic datasets through patterns of acoustic events. We reveal the characteristic processes for collaboratively generating situated accounts of natural places from soundscapes using visualization. We also discuss the biases inherent in the approach. Big data from nature has different characteristics from social and informational data sources that comprise much of the World Wide Web. We conclude with design implications for visual interfaces to facilitate collaborative exploration and discovery through soundscapes.     

Semantic tagging and linking of software engineering social content

Social online communities and platforms play a significant role in the activities of software developers either as an integral part of the main activities or through complimentary knowledge and information sharing. As such techniques become more prevalent resulting in a wealth of shared information, the need to effectively organize and sift through the information becomes more important. Top-down approaches such as formal hierarchical directories have shown to lack scalability to be applicable to these circumstanes. Light-weight bottom-up techniques such as community tagging have shown promise for better organizing the available content. However, in more focused communities of practice, such as software engineering and development, community tagging can face some challenges such as tag explosion, locality of tags and interpretation differences, to name a few. To address these challenges, we propose a semantic tagging approach that benefits from the information available in Wikipedia to semantically ground the tagging process and provide a methodical approach for tagging social software engineering content. We have shown that our approach is able to provide high quality tags for social software engineering content that can be used not only for organizing such content but also for making meaningful and relevant content recommendation to the users both within a local community and also across multiple social online communities. We have empirically validated our approach through four main research questions. The results of our observations show that the proposed approach is quite effective in organizing social software engineering content and making relevant, helpful and novel content recommendations to software developers and users of social software engineering communities.     

Building community information systems: the Connected Kids case

New technologies make it feasible and, in many cases, practical for individuals, groups, and organizations to collaborate in the development of joint information systems. Users find collaborative information systems attractive because they make it possible to find information from diverse sources easily and efficiently. Such systems also make good sense for information providers because they can attract and serve a larger audience than a solitary effort might otherwise command, making it possible to pool resources to achieve certain economies of scale and technology expense. Conceived as both a digital government project and a community information system, Connected Kids helped bridge one city's digital divide by providing new information technologies to youth organizations.     

Nomadic Work: Romance and Reality. A Response to Barbara Czarniawska’s ‘Nomadic Work as Life-Story Plot’

This article takes departure in Barbara Czarniawska’s discussion of ‘Nomadic Work as Life-Story Plot’. It contextualises her analysis of actors’ interpretations of nomadic work with a bi-focal review of the ambiguous realities of these phenomena. Firstly, an examination of key aspects of the socio-economic and political context of nomadic work in global neoliberal economies reveals precarious conditions that cloud romantic interpretations of nomadicity. Secondly, a review of studies of everyday practices of nomadic work shows how neoliberal, but also alternative futures are enacted through creative appropriation of collaborative technologies. One example is the work of digital ‘disaster deck’ volunteers and its potential for the mobilization of ‘rapid, highly localized assistance’ through closer collaboration between a distributed crowd, local communities, and official emergency responders (Starbird and Palen 2013). This and other examples suggest emergent new practices and politics of dwelling in mobility that are focused on sociality and collaboration, straddling virtual and physical commons. The twin critique developed in this response can augment narrative analysis to inform more integrated CSCW innovation that challenges the ‘brave new world of work’.     

Rendering controversial socioscientific issues legible through digital mapping tools

Giving students opportunities to work collaboratively with complex online information is important for the development of democratic citizenship, but providing and structuring these opportunities poses pedagogical challenges. In this study, we investigate how digital mapping tools developed within Science and Technology Studies (STS) are used by upper secondary science students for the collaborative exploration and ordering of controversial socio-scientific issues (SSIs) found online. Our sociocultural approach to detailed analysis of video data reveals how students synchronously construct shared interactive visualizations and respond collaboratively to mediating features of the network visualization tool for handling multiple perspectives and information encountered online. The analysis shows how the tool-mediated activity provided means for students to work out what is relevant and useful in a corpus of online data. We unpack the details of the complex dynamics of this process of evaluating and categorizing websites, uncovering ways that interaction with emerging knowledge artefacts is co-constitutive of participation in the local setting. In particular, this analysis reveals how the tool-mediating activity slows down the process of judging and categorizing online material in terms of criteria such as institutional status, trustworthiness, and position of a controversy. Furthermore, it reveals that alignments and misalignments between the digital tool used and students’ own logics prompted students to engage in productive collaborative negotiation of how to make sense of a controversy.     

What makes a maker: the motivation for the maker movement in ICT

ABSTRACT

The maker movement is a cultural trend that focuses on an individual’s ability to be a creator of things using technology. This study provides an exploratory analysis of the motivations of making and community participation in the maker movement. This study conducted a field study based on motivation theory using a survey methodology that involved 93 individual makers from seven online maker communities. The analysis results show that different motives have a positive effect on makers in different ways: extrinsic, status opportunity motivation affects making itself while use-value motivation affects community participation. Intrinsic motivation does not have a significant relationship with either participation or making. Furthermore, community participation is an important factor in making as it influences both learning and performance, while making only influences performance. These results can help to enlarge the understanding of makers and contribute to the growth of the maker movement.     

Designing in between Local Government and the Public – Using Institutional Analysis in Interventions on Civic Infrastructures

Adapting and changing the systems and technologies involved in civic engagement with local government is among the key challenges of collaborative technologies for political participation. In such contexts, both existing sets of technologies and ingrained, often formalised practices, the ‘rules of the game’, constrain any opportunity for intervention. Additionally, ‘civic’ and expert groups with conflicting agendas and divergent demands on public choices assert their influence in these transformation programmes. The article argues that established methods in collaborative systems design have thus far overlooked the role of recurring actions involved in public participation as well as the formal rules and ingrained practices that construct them. Yet, such patterns present a valuable resource for design interventions. Thus, based on an institutional approach, the article outlines a methodology for requirement gathering by mapping the relations of actors, software and their use along identifiable action situations. The method called for a dialogue between socio-technical-spatial contexts of public service and specific actions taking place within it. Drawing on a case of organising civic engagement in urban planning, the article discusses how to find and trace existing practices across social settings, information technologies and material contexts where engagements take place. The approach underscores the existing institutional contexts in inspiring, opening and constraining the opportunities to support ‘civics’.     

The State of the Art of Spatial Interfaces for 3D Visualization

We survey the state of the art of spatial interfaces for 3D visualization. Interaction techniques are crucial to data visualization processes and the visualization research community has been calling for more research on interaction for years. Yet, research papers focusing on interaction techniques, in particular for 3D visualization purposes, are not always published in visualization venues, sometimes making it challenging to synthesize the latest interaction and visualization results. We therefore introduce a taxonomy of interaction technique for 3D visualization. The taxonomy is organized along two axes: the primary source of input on the one hand and the visualization task they support on the other hand. Surveying the state of the art allows us to highlight specific challenges and missed opportunities for research in 3D visualization. In particular, we call for additional research in: (1) controlling 3D visualization widgets to help scientists better understand their data, (2) 3D interaction techniques for dissemination, which are under‐explored yet show great promise for helping museum and science centers in their mission to share recent knowledge, and (3) developing new measures that move beyond traditional time and errors metrics for evaluating visualizations that include spatial interaction.     

Sense of virtual community: A follow up on its measurement

Understanding the dynamics of virtual communities has become an important issue for research. One concept that explains the participation in online communities is a sense of virtual community (SOVC), which is based on the offline equivalent sense of community (SOC) and describes a “spirit of belonging together”. Although these two concepts are similar, their measurement is problematic. Inspired by earlier studies, which investigated whether traditional SOC measures are appropriate for measuring SOVC, we adopted the SOC index 2 (SCI2) recently developed by Chavis et al. in a virtual setting. Our aim was to determine whether the refined SOC measurement is more suitable for virtual communities than their forerunners. We tested the SCI2 in a popular German community on 312 respondents. Our results showed that a thorough measure of SOVC still needs further refinement. We also discuss possibilities for improvement.     

The next frontier for bio- and cheminformatics visualization

Life science research is increasingly reliant on computation, as affirmed by the recent mapping of the human genome and the analysis questions it poses. Our task is to make sense of these genetic blueprints to develop treatments and therapies for disease. This market is huge, as is the commitment by pharmaceutical companies, biotech firms, and the investment community. The stage is set for scientific discovery and technology advances, the stakes are high, and researchers have many analysis alternatives. The question is whether visualization can be a player in this market and whether it's up to the challenges. This is the question we attempted to answer as panelists at the Visualization 2001 conference. As a group of researchers and practitioners in this burgeoning field, we have noticed three broad problem-solving themes: the visual integration of analyses; high-dimensional analytic visualization; and the emergence of new visualization designs to solve problems. It is clear that advances in information visualization will be integral to bio- and cheminformatics     

In Search of New Product Ideas: Identifying Ideas in Online Communities by Machine Learning and Text Mining

Online communities are attractive sources of ideas relevant for new product development and innovation. However, making sense of the ‘big data’ in these communities is a complex analytical task. A systematic way of dealing with these data is needed to exploit their potential for boosting companies' innovation performance. We propose a method for analysing online community data with a special focus on identifying ideas. We employ a research design where two human raters classified 3,000 texts extracted from an online community, according to whether the text contained an idea. Among the 3,000, 137 idea texts and 2,666 non‐idea texts were identified. The human raters could not agree on the remaining 197 texts. These texts were omitted from the analysis. The remaining 2,803 texts were processed by using text mining techniques and used to train a classification model. We describe how to tune the model and which text mining steps to perform. We conclude that machine learning and text mining can be useful for detecting ideas in online communities. The method can help researchers and firms identify ideas hidden in large amounts of texts. Also, it is interesting in its own right that machine learning can be used to detect ideas.     

Instructional design and emerging teaching models in higher education

Knowledge acquisition and participation are the two prominent metaphors that guide our thinking about learning and relevant instruction. The first of them represents an individual and the latter a social basis of learning. Problem-based learning, case-based teaching, learning by design and cognitive apprenticeship powerfully emphasise anticipation and participation as main goals and perspectives into learning. Those perspectives seem to be typical of all the approaches that can be related with the family of collaborative teaching models. However, the increasing popularity of the collaborative aspect in university education challenges us to develop new approaches into instructional design. In the article the four mentioned, emerging collaborative teaching models are studied and discussed from the perspective of instructional design. The challenges of integration of new technologies in learning are also shortly presented.     

Identifying Seekers and Suppliers in Social Media Communities to Support Crisis Coordination

Effective crisis management has long relied on both the formal and informal response communities. Social media platforms such as Twitter increase the participation of the informal response community in crisis response. Yet, challenges remain in realizing the formal and informal response communities as a cooperative work system. We demonstrate a supportive technology that recognizes the existing capabilities of the informal response community to identify needs (seeker behavior) and provide resources (supplier behavior), using their own terminology. To facilitate awareness and the articulation of work in the formal response community, we present a technology that can bridge the differences in terminology and understanding of the task between the formal and informal response communities. This technology includes our previous work using domain-independent features of conversation to identify indications of coordination within the informal response community. In addition, it includes a domain-dependent analysis of message content (drawing from the ontology of the formal response community and patterns of language usage concerning the transfer of property) to annotate social media messages. The resulting repository of annotated messages is accessible through our social media analysis tool, Twitris. It allows recipients in the formal response community to sort on resource needs and availability along various dimensions including geography and time. Thus, computation indexes the original social media content and enables complex querying to identify contents, players, and locations. Evaluation of the computed annotations for seeker-supplier behavior with human judgment shows fair to moderate agreement. In addition to the potential benefits to the formal emergency response community regarding awareness of the observations and activities of the informal response community, the analysis serves as a point of reference for evaluating more computationally intensive efforts and characterizing the patterns of language behavior during a crisis.     

Building a community among teachers, researchers and university students. A blended approach to training

In this paper we present a case study about a community of practice’s foundation and development among Italian teachers, researchers and university students who participated in a European project aimed at developing and testing innovative pedagogical models and technologies for collaborative knowledge building. Forty-five people (34 teachers, five researchers and six university students) participated in the community of adults that interacted for a school year both face to face and online. We analyzed interactions in order to study the roles, forms and distribution of participation in that community, and the content of teachers’ reflections about the activity. The analysis focuses particularly on different modalities of participation between expert teachers (involved in the project from the beginning) and novices, novice and expert being treated as relevant dimensions according to Wenger’s model. Conversations were transcribed and a qualitative analysis of face-to-face and online discussion performed. The diversity of roles and different modalities of participation between social factors involved in the community, in particular between novice and expert teachers, emerged from the analysis. In final focus groups, teachers underlined innovative potentialities as well as difficulties related to computer-supported collaborative learning, both in classroom activities and in teacher training. In these final focus groups, novice teachers participated in the community, becoming more competent and conscious partners in shared planning with the expert teachers.     

Collaborative Online Examinations: Impacts on Interaction, Learning, and Student Satisfaction

This paper presents the results of a field experiment on online examinations facilitated by collaboration support systems. In particular, it examines collaborative learning and virtual teams through online examinations as an assessment procedure, compared to traditional examinations. Assessment is increasingly regarded as an important part of the learning process. Applying constructivism and collaborative-learning theories, the collaborative examination process features students' active participation in various phases of the exam process through small group activities online. A 1 times 3 field experiment evaluated the collaborative online exam compared with the traditional in-class exam, and the participatory exam, where students participated in the online exam processes without groups. Data analysis using results from 485 students indicates that collaborative examinations significantly enhance interactions and the sense of an online learning community and result in significantly higher levels of perceived learning     

The State of the Art in Integrating Machine Learning into Visual Analytics

Visual analytics systems combine machine learning or other analytic techniques with interactive data visualization to promote sensemaking and analytical reasoning. It is through such techniques that people can make sense of large, complex data. While progress has been made, the tactful combination of machine learning and data visualization is still under‐explored. This state‐of‐the‐art report presents a summary of the progress that has been made by highlighting and synthesizing select research advances. Further, it presents opportunities and challenges to enhance the synergy between machine learning and visual analytics for impactful future research directions.     

Design and evaluation of an adaptive incentive mechanism for sustained educational online communities

Most online communities, such as discussion forums, file-sharing communities, e-learning communities, and others, suffer from insufficient user participation in their initial phase of development. Therefore, it is important to provide incentives to encourage participation, until the community reaches a critical mass and “takes off”. However, too much participation, especially of low-quality can also be detrimental for the community, since it leads to information overload, which makes users leave the community. Therefore, to regulate the quality and the quantity of user contributions and ensure a sustainable level of user participation in the online community, it is important to adapt the rewards for particular forms of participation for individual users depending on their reputation and the current needs of the community. An incentive mechanism with these properties is proposed. The main idea is to measure and reward the desirable user activities and compute a user participation measure, then cluster the users based on their participation measure into different classes, which have different status in the community and enjoy special privileges. For each user, the reward for each type of activity is computed dynamically based on a model of community needs and an individual user model. The model of the community needs predicts what types of contributions (e.g. more new papers or more ratings) are most valuable at the current moment for the community. The individual model predicts the style of contributions of the user based on her past performance (whether the user tends to make high-quality contributions or not, whether she fairly rates the contributions of others). The adaptive rewards are displayed to the user at the beginning of each session and the user can decide what form of contribution to make considering the rewards that she will earn. The mechanism was evaluated in an online class resource-sharing system, Comtella. The results indicate that the mechanism successfully encourages stable and active user participation; it lowers the level of information overload and therefore enhances the sustainability of the community.     

Social Network Clustering and Visualization using Hierarchical Edge Bundles

The hierarchical edge bundle (HEB) method generates useful visualizations of dense graphs, such as social networks, but requires a predefined clustering hierarchy, and does not easily benefit from existing straight‐line visualization improvements. This paper proposes a new clustering approach that extracts the community structure of a network and organizes it into a hierarchy that is flatter than existing community‐based clustering approaches and maps better to HEB visualization. Our method not only discovers communities and generates clusters with better modularization qualities, but also creates a balanced hierarchy that allows HEB visualization of unstructured social networks without predefined hierarchies. Results on several data sets demonstrate that this approach clarifies real‐world communication, collaboration and competition network structure and reveals information missed in previous visualizations. We further implemented our techniques into a social network visualization application on facebook.com and let users explore the visualization and community clustering of their own social networks.     

Augmented reality visualization: A review of civil infrastructure system applications

In Civil Infrastructure System (CIS) applications, the requirement of blending synthetic and physical objects distinguishes Augmented Reality (AR) from other visualization technologies in three aspects: (1) it reinforces the connections between people and objects, and promotes engineers’ appreciation about their working context; (2) it allows engineers to perform field tasks with the awareness of both the physical and synthetic environment; and (3) it offsets the significant cost of 3D Model Engineering by including the real world background. This paper reviews critical problems in AR and investigates technical approaches to address the fundamental challenges that prevent the technology from being usefully deployed in CIS applications, such as the alignment of virtual objects with the real environment continuously across time and space; blending of virtual entities with their real background faithfully to create a sustained illusion of co-existence; and the integration of these methods to a scalable and extensible computing AR framework that is openly accessible to the teaching and research community. The research findings have been evaluated in several challenging CIS applications where the potential of having a significant economic and social impact is high. Examples of validation test beds implemented include an AR visual excavator-utility collision avoidance system that enables workers to “see” buried utilities hidden under the ground surface, thus helping prevent accidental utility strikes; an AR post-disaster reconnaissance framework that enables building inspectors to rapidly evaluate and quantify structural damage sustained by buildings in seismic events such as earthquakes or blasts; and a tabletop collaborative AR visualization framework that allows multiple users to observe and interact with visual simulations of engineering processes.