Collaborative Information Seeking

Working in collaboration is one of the fundamental behaviors of human kind. We do so for various reasons – solving complex problems, learning a skill, and even for simply propagating social connections. It is this behavior that has not only made many of the human achievements possible, but the very survival of the human race feasible. Given that many problems in today’s world require dealing with information, it is no surprise that we find the need to collaborate on complex problems that involve seeking, using, and evaluating information. What are these complex problems? They range from travel planning and health-related information seeking to patent search and preparing legal cases. This chapter describes an interview study done on a small sample to elicit why would anyone collaborate for information seeking, what support they will need, and what does one can gain through collaborative information seeking (CIS). It then attempts to explain this CIS behavior using Shah’s C5 model of collaboration. Finally, the chapter asks and at least partially addresses so what and now what questions. In doing so, the current chapter lays out the groundwork, helping the reader put other chapters in this book in perspective.

Collaborative information seeking (CIS) has lately produced interesting empirical studies, describing CIS in real-life settings. While these studies explore how and why CIS manifests itself in different domains, discussions about how to study CIS have been scarce. The research area of CIS may, however, benefit from a discussion of methodological issues. This chapter describes the application of three methods for collecting and analyzing data in three CIS studies. The three methods are Multidimensional Exploration, used in a CIS study of students’ information behavior during a group assignment; Task-structured Observation, used in a CIS study of patent engineers; and Condensed Observation, used in a CIS study of information-systems development. The three methods are presented in the context of the studies for which they were devised, and the experiences gained using the methods are discussed. The chapter shows that different methods can be used for collecting and analyzing data about CIS incidents. Two of the methods focused on tasks and events in work settings, while the third was applied in an educational setting. Commonalities and differences among the methods are discussed to inform decisions about their applicability in future CIS studies and, more generally, to foster methodological discussions in CIS research.

Collaborative Information Seeking (CIS) is common in many professional contexts. This chapter discusses CIS from four different perspectives – education, healthcare, science research and patent research. We first introduce the CIS context, focusing on Evans and Chi’s proposed model of social search. We highlight the ways contextual factors relate to the search process, in particular noting the role of communication in CIS processes. The four example professional contexts are discussed with reference to the ‘medium’ of collaboration, the ways CIS is conducted, the tools used and physical setting of CIS, and the ‘context’ of CIS, the purposes for which an instance of CIS occurs in that discipline. We suggest that these contextual factors can be aligned with, but are additional to, the existing Evans and Chi model of social search, and that their addition in a ‘pre- and post-model’ extension could provide a shared framework for researching contextual features of CIS. In highlighting commonalities and contrasts across the disciplinary contexts we suggest that a developed model, and further research, is needed to understand the relationship between motivations in these different disciplines and the evaluation of CIS episodes, and the role of processes, particularly communication, in those episodes. In order to evaluate CIS in different disciplines future research should focus on the between, and within discipline differences in the purposes of CIS. Characteristics of success in different disciplinary contexts may relate both to the consideration of the collaborative context, and the information need; developing deeper understanding of this point.

Information seeking is a central and inherently collaborative activity in the emergency department (ED), which is the common entry point to hospitals for nearly all acute patients. In this paper, we investigate how ED clinicians’ collaborative information seeking (CIS) is shaped by the procedures that they follow in the ED. Based on observations in two Danish EDs, we identify four procedures prominent to how CIS is accomplished: the triage procedure, the timeouts, the coordinating nurse, and the recurrent opportunities for information seeking at the whiteboard. We then discuss how CIS activities are impacted by these procedures and the challenges to effective CIS in these settings. We conclude with some thoughts about future studies of CIS in healthcare settings.

The following chapter presents and compares three empirical studies on Collaborative Information Seeking (CIS) within the context of leisure time and of work tasks. The focus lies on the methods, the results and a comparison between the studies. The first study was conducted in Malaysia and concentrates on the way Malaysian students execute their mobile search in a social setting. The following two studies focus on CIS in the context of work tasks. The first study deals with ad hoc CIS in a work task scenario and was conducted with German Information Science students. The second study refers to long-term CIS in relation with work tasks and was conducted in the same context. Apart from describing the test designs in the different scenarios, we discuss similarities and differences between leisure-based and work-based CIS, adapted from the results of the three empirical studies. In addition, we point out limitations given by the design and the different scopes of the surveys. With the help of the studies we hope to provide a deeper understanding of the way students execute their collaborative search in leisure-based and work-based scenarios. Furthermore, the description of the different test designs and the given limitations can help to conduct additional studies in the respective contexts.

This chapter discusses Collaborative Information Seeking (CIS) from an educational perspective. Our core claim is that CIS has the potential to bring together rich collaborative, and multimodal, contexts in which important learning processes may take place. We thus see CIS as more than just an activity with potential to ‘speed up’ information seeking, or contribute to effective division of labour. This claim is independent of the particular classroom subject, or the form of technological mediation; rather, the chapter provides a focus on some key considerations in collaborative learning that should be of interest to both educators and those interested in the ‘benefits’ of CIS. This chapter first outlines our broad educational interest in elements of CIS, connecting that to the focal points of CIS research. We go on to highlight the importance of dialogue as a tool for learning, before discussing the complexities of understanding ‘success’ in CIS tasks, and then specifically the role that dialogue has played so far in CIS research. We conclude with a call to researchers in both CIS and education to explore the nature of learning in CIS contexts, making use of a rich understanding of the importance of dialogue to create meaning together.

For many decades, technical support centers have been seen as information providers that assist customers with technical problems, provide varied solutions, and guide them to valuable information resources. These centers have diverse technical proficiencies that are required to handle a wide range of technical issues, varying from simple to complex. However, current online and live-chat support interfaces support one-to-one interactions, and collaboration among novice agents (gatekeepers), experts, and customers or clients is not supported. Novice agents receive clients’ problems, and if they cannot solve them, they consult experts. Also, they work as gatekeepers between clients and technical experts, and they allow only selected clients with complex problems to pass the gates and interact with experts. Literature confirms the importance of gatekeeping in many contexts, such as medical, engineering, and technical fields. This chapter ties the gatekeeping concept together with current models in customer service and technical support systems that have implemented this function. Current live-chat applications are discussed in this chapter to show how collaborative information seeking (CIS) tools, such as chatting, searching, and sharing can help to establish a successful live technical support platform. The chapter discusses innovative enhancements that could guide system developers to improve today’s live support platforms and advance them with CIS features. Optimistically, future improvements would allow clients and technical agents to seek, select, share, evaluate, and use information collaboratively to leverage the level of technical awareness on diverse products, enhance problem-solving skills for customers, and relieve technical centers from excessive help requests.

Despite a rise in collaborative research, resulting in complex collaborative information seeking (CIS), few studies have explored the CIS experiences of academics in the humanities. This research explores the CIS activities of digital humanities scholars within the broader context of their collaborative research practices. Data from qualitative semi-structured interviews and guided interactions with digital tools are analysed using the conceptual lens of “parallel work” to best understand scholars’ engagement with CIS. The results demonstrate the complexities of research contexts and how CIS is shaped by individuals’ research needs, technology use and general information behaviours. The findings demonstrate how digital tools enable and constrain collaborative information work, and show how availability, ease of use, and other peoples’ activities often determine which tools and seeking practices are used in collaboration. Additionally, while scholars in the digital humanities work collaboratively, they continue to work as solo scholars, at times working quite independently within a collaborative project. Of particular note are results that show a lack of group-based information seeking practices within collaborative research practices. The model of Parallel Research Practice is proposed as a way to understand how digital humanities scholars engage in collaborative information activities.

In various work domains, the collaborative performance of a work task by a team can lead to a shared information need required to fulfill this task. Many empirical studies identified collaborative information seeking and retrieval as everyday work patterns in order to solve a shared information need and to benefit from the diverse expertise and experience of the team members. In everyday work practices, collaboration is realized by utilizing a broad range of software tools that build a heterogeneous collaboration environment. In such environments, collaboration is performed in a loosely coupled manner and using tools designed for individual usage. In this chapter, we present a general probabilistic framework for ranking documents in such collaborative settings that accounts for differences in skills and expertise within the team and ranks documents accordingly. Our approach is justified by decision theory. We present a proof of optimality of our ranking principle and show that it can serve as a justification for previous research approaches in the area of collaborative search.

This chapter aims to reflect about the importance and challenges of research on the affective dimension in collaborative information seeking (CIS). This is achieved through three major parts. First, an overview of the relevance of the affective dimension is provided. Second, research on the affective dimension in individual information seeking in general, and CIS in particular is discussed. Finally, research approaches, challenges, and ethical aspects in this type of studies are discussed. This chapter hopes to encourage researchers to formulate new questions, hypotheses, and more importantly further investigate this interesting topic.

Big data analytics poses many socio-computational problems with respect to collaborative information seeking. While collaboration presents a way to alleviate the data deluge, research into this area is only relatively recent. The diverse range of skills and knowledge among a data analytics team presents an array of problems, including a wide spectrum of domain expertise, lack of shared understanding between roles, and challenges with the physical and computational aspects of multiple people seeking information within the multiple systems required for big data analytics. This chapter discusses recent research on collaborative big data analytics to discuss present progress, lessons learned, and gaps to be filled with future research. It proposes that the framework of the transactive memory system is a viable way to view people working around big data, as it supports collaborative sensemaking and the production of common ground among heterogeneous teams.