Information Technology system administrators (sysadmins) perform the crucial and never-ending work of maintaining the technical infrastructure on which our society depends. Computer systems grow more complex every year, however, and the cost of administration is an ever increasing fraction of total system cost -IT systems are growing harder to manage. To better understand this problem, we undertook a series of field studies of system administration work over the past four years, visiting a variety of enterprise and large university sites. One of our most compelling observations was how often the tools used by system administrators were not well aligned with their work practices. We believe that this misalignment was the result of administration tools designed without a complete understanding of the full context of administration work. To promote the design of better tools, this paper describes system administration work in more detail based on examples from our field studies, outlines the dimensions along which enterprise sysadmins differ significantly from other computer users, and provides a set of guidelines for tools to better support how administrators actually work.
With greater availability of data, businesses are increasingly becoming data-driven enterprises, establishing standards for data acquisition, processing, infrastructure, and decision making. Enterprises now have people dedicated to performing analytic work to support decision makers. To better understand analytic work, particularly the role of enterprise business analysts, researchers interviewed 34 analysts at a large corporation. Analytical work occurred in an ecosystem of data, tools, and people; the ecosystem's overall quality and efficiency depended on the amount of coordination and collaboration. Analysts were the bridge between business and IT, closing the semantic gap between datasets, tools, and people. This article provides an overview of the analytic work in the enterprise, describing challenges in data, tools, and practices and identifying opportunities for new tools for collaborative analytics.
Modern enterprises are replete with numerous online processes. Many must be performed frequently and are tedious, while others are done less frequently yet are complex or hard to remember. We present interviews with knowledge workers that reveal a need for mechanisms to automate the execution of and to share knowledge about these processes. In response, we have developed the CoScripter system (formerly Koala [ 11]), a collaborative scripting environment for recording, automating, and sharing web-based processes. We have deployed CoScripter within a large corporation for more than 10 months. Through usage log analysis and interviews with users, we show that CoScripter has addressed many user automation and sharing needs, to the extent that more than 50 employees have voluntarily incorporated it into their work practice. We also present ways people have used CoScripter and general issues for tools that support automation and sharing of how-to knowledge. . First, we present results from an interview study that explores how people practice, learn, and share their procedural knowledge in the enterprise. Second, we present results from an extended deployment of an end-user programming system in a large organization. Finally, we discuss a number of general issues that arose in the deployment that must
Citizen science projects can collect a wealth of scientific data, but that data is only helpful if it is actually used. While previous citizen science research has mostly focused on designing effective capture interfaces and incentive mechanisms, in this paper we explore the application of HCI methods to ensure that the data itself is useful. To provide a focus for this exploration we designed and implemented Creek Watch, an iPhone application and website that allow volunteers to report information about waterways in order to aid water management programs. Working with state and local officials and private groups involved in water monitoring, we conducted a series of contextual inquiries to uncover what data they wanted, what data they could immediately use, and how to most effectively deliver that data to them. We iteratively developed the Creek Watch application and website based on our findings and conducted evaluations of it with both contributors and consumers of water data, including scientists at the city water resources department. Our study reveals that the data collected is indeed useful for their existing practices and is already in use in water and trash management programs. Our results suggest the application of HCI methods to design the data for the end users is just as important as their use in designing the user interface.
Troubleshooting large computer systems is often highly collaborative. Because these systems consist of complex infrastructures with many interdependent components, expertise is spread across people and organizations. Those who administer such systems are faced with cognitive and social challenges, including the establishment of common ground and coordination of attention, as they troubleshoot in collaboration with peers, technical support, and software application developers. We take a distributed cognition approach to interpreting a specific instance of problem-solving in administering a web-based system, examining the movement of representational state across media in a single system administrator's environment. We also apply the idea of language use as joint activity to understand how discourse attributes affect what is accomplished collaboratively. Our analysis focuses on information flow among participants and other sources, and how these affect what information is attended to, transmitted, and used.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.