G U E S T EDITO RS’ IN T RODU C T ION
Collaborative Information Seeking Chirag Shah, Rutgers University Robert Capra, University of North Carolina at Chapel Hill
Preben Hansen, Stockholm University
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Published by the IEEE Computer Society
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In today’s era of ever-increasing user-generated content and online sharing, computer and information scientists have a renewed interest in collaborative information seeking as an exciting area of research and development, with applications that range from education to e-commerce, with implications for areas that range from libraries to legal informatics.
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nformation seeking is a cognitive, psychological, and physical activity. It is more than just searching for and retrieving information, and it can be performed with or without computing assistance. Information seeking typically takes place in the context of a broader task and involves looking for, collecting, and analyzing information, as well as sensemaking and sharing.1 Researchers in the fields of computer science, human– computer interaction, information science, and library science study how people engage in information seeking in hopes of building more efficient and effective systems to support these activities. To date, much of this research has focused on how individuals undertake these activities: how they search, collect, and make sense of information; and how they use that information in the broader context of a task. Algorithms and systems traditionally assume that one person is searching and reviewing the results; thus, user interfaces support the needs of individual searchers. As a research area, collaborative information seeking (CIS) focuses on how groups of people perform these activities based on the idea that information seeking is not always a solitary activity, that people collaborating on information-seeking tasks work in distinct ways and so should be studied and supported separately. Collaboration is a useful and often necessary component of complex projects,2 and the settings for CIS are diverse: a team of engineers working together to create an infrastructure design, a family planning a two-week vacation, researchers coauthoring a scholarly article, a couple organizing their wedding, or a group of medical professionals diagnosing a patient. All of these examples involve people coming together with intention, looking for and sharing information, and making sense out of shared findings to attain their goals. CIS resembles individual information seeking, but with added dimensions such as the roles the collaborators assume, how they work together across time and space, their awareness of one another’s actions, and the negotiation and sharing that must occur. Collaborators might search in a highly coordinated fashion, or be only loosely coupled. They could be peers or take on asymmetrical roles (such as searcher/reader or mentor/student). CIS activities can occur synchronously or asynchronously, be co-located or remote, and involve specialized search
systems. Other research areas—computer-supported cooperative work (CSCW) and the related fields of computer-mediated communication (CMC), system-focused groupware, and computer-supported collaborative learning (CSCL)—contribute much to our understanding of CIS, but without its specific focus on the information-seeking aspect of collaborative work.
CIS PREVALENCE As Internet-connected computing devices have become more portable and ubiquitous and as online collaboration has grown more common, researchers have recognized the potential benefits of supporting the collaborative and social aspects of information seeking. For example, recent research projects have examined how people use existing tools for CIS;3 a taxonomy of dimensions of CIS;4 application of CIS in various domains such as healthcare,5 crisis management,6 reviewing patent applications,7 and library use;8 and software tools to support CIS.9–11 This research has yielded a number of prototype systems and insightful results about CIS, many of which have been presented in recent workshops, conferences, and journals. Since 2010, a series of workshops has been organized with various conferences and communities on the topic of CIS, including the CIS 2010 Workshop in conjunction with the ACM GROUP Conference, the CIS 2011 Workshop with the ASIST Conference, and the CIS 2013 Workshop with the ACM CSCW Conference.
CIS is not only an information-seeking activity involving collaboration, but also a collaborative activity with the goal of information seeking. Although this is not the first time scholars have acknowledged the social aspect of information seeking,8 current work coincides with a combination of new technologies, such as Web 2.0 and social media/networking tools, and changes in human behavior, including people’s increasing tendency to quickly and ubiquitously share and connect with others through new interfaces and devices. This confluence has sparked recent research under many names:
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G U E S T EDITO RS’ IN T RODU C T ION and Retrieval in a Heterogeneous Environment,” describe a three-layer model for collaboration in work settings that includes individuals, search Collaboration Information systems, and information objects that seeking can be used to describe loosely coupled, centralized, and heterogeneous collaboration systems. They present Collaborative an overview of their experimental information Information ezDL (Easy Access to Digital Libraries) seeking (CIS) retrieval system, which is designed to support information seeking across multiple sessions for both individuals and collaborative groups. ezDL allows users to create personal and shared repositories of information, and the system will make recommendations and provide collaborative filtering based on Figure 1. Collaborative information seeking (CIS)'s relationship to the information seeking, collaboration, and information retrieval fields, in context. these libraries. Sensemaking describes an individual or group attempting to make sense of, synthesize, and understand collected information. CIS, collaborative information retrieval (CIR), collaborative Collaborative sensemaking is an important component of information behavior (CIB), collaborative search, co-search, CIS. In “Investigating Collaborative Sensemaking Behavco-browsing, and collaborative exploratory search. Imior in Collaborative Information Seeking,” Yihan Tao and portant contributions have been made from research in Anastasios Tombros report results from a study of the colall these areas as reflected in the articles included in this laborative sensemaking behaviors and needs of online special issue. Figure 1, based on the work one of us pubsearchers performing a research task. These results show lished previously,12 illustrates the relationship between CIS that users need support in building structure, awareness of and the related fields of information seeking, collaboration, collaborators’ current foci, and keeping track of the overall and information retrieval. task progression. Their findings imply that CIS tool design CIS is not only an information-seeking activity involvshould take into account issues such as support for strucing collaboration, but also a collaborative activity with the ture construction and visualization and group awareness goal of information seeking. Its study requires taking into of the sensemaking process. account people seeking information in collaboration for One way that CIS systems can enhance awareness of a common goal, where the information seeking is intencollaborators’ actions is to display lists of recent docutional, the collaboration explicitly defined, and the goal ments that collaborators have found and queries that they mutually beneficial. have issued. Awareness of collaborators’ actions then assists or influences the actions of each team member as IN THIS ISSUE he or she is searching individually. One specific way this For organizations, CIS is an essential part of problem may occur is during query formulation and reformulasolving. Work tasks often involve direct and indirect collabtion. When teammates are aware of each other’s queries, oration with others to find, identify, and apply information. they may write queries to overlap or avoid areas already Two articles in this special issue address these work conexplored, depending on the team’s goals. In the article texts. In “Identifying Knowledge Brokers and Their Role “Influences on Query Reformulation in Collaborative in Enterprise Research through Social Media,” Zhe Xu, Jay Web Search,” authors Zhen Yue, Shuguang Han, Daqing Ramanathan, and Rajiv Ramnath analyze message threads He, and Jiepu Jiang describe how both search actions and from a Fortune 500 company’s social media to explore how collaborative actions can influence users’ query reformu“knowledge brokers” connect requestors to sources of inlations, and show that task type can also play a role—for formation. The authors show that knowledge brokers play example, explicit communication affected their subjects’ an important problem-solving role within the enterprise, query reformulation in decision-making tasks more than although these brokers are not always identifiable through in information-gathering tasks. existing expert-finding systems. Increasing use of mobile devices creates new opportuThilo Böhm, Claus-Peter Klas, and Matthias Hemmje, nities for synchronous, co-located collaborative searches in their article, “ezDL: Collaborative Information Seeking
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to occur among groups of people. In “Supporting Interpersonal Interaction during Collaborative Mobile Search,” authors Jaime Teevan, Meredith Ringel Morris, and Shiri Azenkot describe O-SNAP, a collaborative search system specifically designed for mobile devices. O-SNAP allows users to move between individual and group search modes by physically rotating their device from portrait to landscape orientation, and includes features to encourage interaction. Finally, Marti Hearst asks “What’s Missing from Collaborative Search?” In this article, she reflects on current CIS challenges and proposes promising areas for future work.
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y studying and developing systems to support CIS, we hope to help users discover, create, and make sense out of information in ways that have not been possible with existing individualized systems and tools. This special issue provides an introduction to the topic of CIS, highlights concrete examples of current CIS systems, discusses CIS in the context of work-tasks, and illustrates future possibilities.
References 1. K. Byström, and P. Hansen, “Conceptual Framework for Task in Information Studies,” J. Am. Soc. Information Science and Technology, vol. 56, no. 10, 2005, pp. 1050–1061. 2. P.J. Denning, “Mastering the Mess,” Comm. ACM, vol. 50, no. 4, 2007, pp. 21–25. 3. R. Capra et al., “Tools-at-Hand and Learning in MultiSession, Collaborative Search,” Proc. 28th Int’l Conf. Human Factors in Computing Systems (CHI 2010), 2010, pp. 951–960. 4. G. Golovchinsky, J. Pickens, and M. Back, “A Taxonomy of Collaboration in Online Information Seeking,” Proc. Int’l Workshop Collaborative Information Retrieval at ACM/IEEE Joint Conf. on Digital Libraries (JCDL), 2008; http://www.fxpal.com/?p=abstract&abstractID=454. 5. M.C. Reddy and B.J. Jansen, “A Model for Understanding Collaborative Information Behavior in Context: A Study of Two Healthcare Teams,” Information Processing and Management, vol. 44, no. 1, 2008, pp. 256–273. 6. B. Bjurling and P. Hansen, “Contracts for Information Sharing in Collaborative Networks,” Proc. 7th Int’l Conf. Information Systems Crisis Response and Management, 2010; w w w.iscra m.org/ISCR AM2010/Papers/2 43 -Bjurling_etal.pdf. 7. P. Hansen and P. Järvelin, “Collaborative Information Retrieval in an Information-Intensive Domain,” Information Processing and Management, vol. 41, no. 5, 2005, pp. 1101–1119.
8. M.B.T. Twidale, D.M.N. Nichols, and C.D. Paice, “Browsing Is a Collaborative Process,” Information Processing and Management, vol. 33, no. 6, 1997, pp. 761–783. 9. M.R. Morris and E. Horvitz, “SearchTogether: An Interface for Collaborative Web Search,” ACM Symp. User Interface Software and Technology (UIST 05), 2005, pp. 3–12. 10. C. Shah, “Coagmento: A Collaborative Information Seeking, Synthesis and Sense-Making Framework,” Proc. Computer Supported Cooperative Work (CSCW 2010), 2010, pp. 527–528. 11. R. Capra et al., “Searcher Actions and Strategies in Asynchronous Collaborative Search,” Proc. Am. Soc. Information Science and Technology, vol. 50, no. 1, 2013, pp. 1–10. 12. C. Shah, Collaborative Information Seeking: The Art and Science of Making the Whole Greater than the Sum of All, Springer, 2012, p. 185; www.springer.com/ computer/database+management+&+information +retrieval/book/978-3-642-28812-8.
Chirag Shah is an assistant professor in both the School of Communication & Information (SC&I) and the Department of Computer Science at Rutgers University. His research interests include information seeking/retrieval in social and collaborative contexts. Shah received a PhD in information science from the University of North Carolina at Chapel Hill. He is a lifetime member of ACM and a member of the Association of Information Science & Technology (ASIST). Contact him at
[email protected]. Robert Capra is an assistant professor in the School of Information and Library Science at the University of North Carolina at Chapel Hill. His research interests include human–computer interaction, personal information management, and search user interfaces. Capra received a PhD in computer science from Virginia Tech. He is a member of IEEE, ACM, and ASIST. Contact him at
[email protected]. Preben Hansen is an associate professor in the Department of Computer and Systems Sciences at Stockholm University, Sweden. His research interests include interactive information seeking and retrieval, human–computer interaction, and work-task–based research in collaborative contexts. He is working with the EU projects Promise, MUMIA, and KNOWeSCAPE. Hansen received a PhD in information science from University of Tampere, Finland. Contact him at
[email protected].
Selected CS articles and columns are available for free at http://ComputingNow.computer.org.
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