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Quotes recent (1994) literature suggesting that workers receive more training and support in their local work area than from a centralized management information systems (MIS) group. Suggests that there is therefore little knowledge about how users learn the computing skills necessary for them to achieve their tasks. Explores the issues. Presents four case studies, two having a central MIS training and support functions and two having none. Observes that in four work groups members depended on locally emerging arrangements for training and support.

Examines how important social and technical choices become part of the history of a computer‐based information system (CBIS). Argues that CBIS should be developed in terms of their social, as well as their information‐processing characteristics. Demonstrates that developing CBIS as an institutional system is important because: the useability is more critical than the technology; a well‐used CBIS with a stable structure is more difficult to replace than an unstable, ill‐used one; and CBIS vary from one social setting to another. Illustrates with a case study of a failed attempt at conversion.

The first‐ever conference on “computer‐supported cooperative work” (CSCW) defined a new perspective and perhaps even a new speciality in the field of computer science. The fundamental insight is that, with very few exceptions, our work does not take place in isolation but, rather, is embedded in a multiplicity of social contexts. And this, obviously, has enormous implications for how information technology is conceived and designed.

As a terminal hooked to a mainframe utility, the typical PC is an excellent example of a Trojan Horse. Although extremely versatile, these machines are perfectly capable of acting as dumb as the terminals they replaced. Many of them do. Nevertheless, they sit and wait for you to do something innovative. Through your own expertise or daring spirit, you may have placed a hard disk on the terminal, perhaps tried a few other programs such as word processors or maybe even a spreadsheet. Over time the terminal became a little smarter, capable of more and greater activities.

This paper aims to analyse a set of converging trends underpinning a larger phenomenon called science 2.0 and to assess what are the most important implications for scientific method and research institutions.

It is based on a triangulation of exploratory methods which include a wide-ranging literature review, Web-based mapping and in-depth interviews with stakeholders.

The main implications of science 2.0 are enhanced efficiency, transparency and reliability; raise of data-driven science; microcontributions on a macroscale; multidimensional, immediate and multiform evaluation of science; disaggregation of the value chain of service providers for scientists; influx of multiple actors and the democratisation of science.

The paper rejects the notion of science 2.0 as the mere adoption of Web 2.0 technologies in science and puts forward an original integrated definition covering three trends that have not yet been analysed together: open science, citizens science and data-intensive science. It argues that these trends are mutually reinforcing and puts forward their main implications. It concludes with the identification of three enablers of science 2.0 – policy measures, individual practice of scientists and new infrastructure and services and sees the main bottleneck in lack of incentives on the individual level.