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PurposeAn ensemble is an intermediate unit of work between action and activity in the hierarchical framework proposed by classical activity theory. Ensembles are the mid‐level of activity, offering more flexibility than objects, but more purposeful structure than actions. The paper aims to introduce the notion of ensembles to understand the way object‐related activities are instantiated in practice.Design/methodology/approachThe paper presents an analysis of the practices of professional information workers in two different companies using direct and systematic observation of human behavior. It also provides an analysis and discussion of the activity theory literature and how it has been applied in areas such as human‐computer interaction and computer‐supported collaborative work.FindingsThe authors illustrate the relevance of the notion of ensembles for activity theory and suggest some benefits of this conceptualization for analyzing human work in areas such as human‐computer interaction and computer‐supported collaborative work.Research limitations/implicationsThe notion of ensembles can be useful for the development of a computing infrastructure oriented to more effectively supporting work activities.Originality/valueThe paper shows that the value of the notion of ensembles is to close a conceptual gulf not adequately addressed in activity theory, and to understand the practical aspects of the instantiation of objects over time.

Intro -- Preface -- Organization -- Contents -- Scientific Work and Data Practices -- A Comparative Study of Biological Scientists' Data Sharing Between Genome Sequence Data and Lab Experiment Data -- Abstract -- 1 Introduction -- 2 Literature Review -- 3 Theoretical Framework -- 4 Research Model and Hypothesis Development -- 5 Research Methods -- 6 Data Analysis and Results -- 6.1 Assessment of Measures -- 6.2 Hierarchical Regression Analysis -- 6.3 Independent Sample t-test -- 7 Discussion -- 8 Conclusion -- References -- Surfacing Data Change in Scientific Work -- 1 Introduction -- 2 Literature Review -- 3 Research Sites and Methods -- 4 Findings -- 4.1 Why Scientists Are Concerned About Data Change -- 4.2 Two Broad Types of Data Change -- 4.3 Trusting Collaborators and Processes to Make Datasets `Better' -- 4.4 Rhythms and Organizational Structures of Projects -- 5 Discussion and Conclusion -- References -- Understanding Hackathons for Science: Collaboration, Affordances, and Outcomes -- Abstract -- 1 Introduction -- 2 Background -- 3 Methods -- 3.1 The Setting: Two Hackathons at STScI -- 3.2 Data Collection and Analysis -- 4 Results -- 5 Discussion and Conclusion -- References -- Methodological Concerns in (Big) Data Research -- Modeling the Process of Information Encountering Based on the Analysis of Secondary Data -- Abstract -- 1 Introduction -- 2 Literature Review -- 2.1 Existing IE Process Models -- 2.2 CIT-Based IE Research -- 3 Data Collection -- 4 Data Analysis and Results -- 5 Discussion and Conclusions -- 5.1 The Value of the General IE Process Model -- 5.2 Limitations -- Acknowledgement -- Appendix -- References -- Methodological Transparency and Big Data: A Critical Comparative Analysis of Institutionalization -- Abstract -- 1 Introduction -- 2 Background -- 3 Methods -- 4 Discussion of Results.

Cover -- Contents -- Acknowledgments -- Foreword -- CHAPTER 1. WHY THIS HANDBOOK? -- 1.1 Beginnings -- 1.2 Why ethnographic methods and why virtual worlds? -- 1.3 Why a handbook? -- 1.4 An orientation to the virtual worlds we studied -- CHAPTER 2. THREE BRIEF HISTORIES -- 2.1 A brief history of ethnographic methods -- 2.2 A brief history of virtual worlds -- 2.3 A brief history of research on virtual world cultures -- 2.4 The uses of history -- CHAPTER 3. TEN MYTHS ABOUT ETHNOGRAPHY -- 3.1 Ethnography is unscientific -- 3.2 Ethnography is less valid than quantitative research -- 3.3 Ethnography is simply anecdotal -- 3.4 Ethnography is undermined by subjectivity -- 3.5 Ethnography is merely intuitive -- 3.6 Ethnography is writing about your personal experience -- 3.7 Ethnographers contaminate fieldsites by their very presence -- 3.8 Ethnography is the same as grounded theory -- 3.9 Ethnography is the same as ethnomethodology -- 3.10 Ethnography will become obsolete -- CHAPTER 4. RESEARCH DESIGN AND PREPARATION -- 4.1 Research questions: emergence, relevance, and personal interest -- 4.2 Selecting a group or activity to study -- 4.3 Scope of the fieldsite -- 4.4 Attending to offline contexts -- CHAPTER 5. PARTICIPANT OBSERVATION IN VIRTUAL WORLDS -- 5.1 Participant observation in context -- 5.2 Participant observation in practice -- 5.3 Preparing the researching self -- 5.4 Taking care in initiating relationships with informants -- 5.5 Making mistakes -- 5.6 Taking extensive fieldnotes -- 5.7 Keeping data organized -- 5.8 Participant observation and ethnographic knowledge -- 5.9 The timing and duration of participant observation -- 5.10 The experimenting attitude -- CHAPTER 6. INTERVIEWS AND VIRTUAL WORLDS RESEARCH -- 6.1 The value of interviews in ethnographic research -- 6.2 Effective interviewing