<XML><RECORDS><RECORD><REFERENCE_TYPE>3</REFERENCE_TYPE><REFNUM>6161</REFNUM><AUTHORS><AUTHOR>Renaud,K.V.</AUTHOR><AUTHOR>Cooper,R.L.</AUTHOR></AUTHORS><YEAR>2001</YEAR><TITLE>Considering Possible Outcomes and the User's Environment in Designing User Interfaces to Data Intensive Systems</TITLE><PLACE_PUBLISHED>User Interfaces to Data Intensive Systems. UIDIS'01. ETH, Zurich. 31 May - 1 June 2001. </PLACE_PUBLISHED><PUBLISHER>IEEE</PUBLISHER><LABEL>Renaud:2001:6161</LABEL><ABSTRACT>Application programmers are often unrealistic about the end-user's working environment and seldom cater for the effects of events which will interfere with the use of the application. Such events can disrupt the straightforward execution of a task and interfere with a user's concentration. These events, which will be referred to in this paper as quirks, could be system breakdowns, various types of interruptions to application use, or human errors. Applications often make no concession to the inevitability of quirks and seldom give assistance in rebuilding mental context afterwards or facilitate understanding of the cause in the case of an error. In addition to the normal quirks caused merely by sharing office space or in working as part of a group of people, most data-intensive systems are distributed and this tends to precipitate a whole range of errors, hitherto unsuspected, which will probably be reported to the user in all their technical verbosity, reducing the user's understanding of, and confidence in, the system and perhaps necessitating intervention by specialists. The inherent distributed nature of data-intensive systems also increases the likelihood of breakdowns, since so many more computers are involved in the application than the computer being used by the end-user. Few applications consider the effects of quirks while developing their systems, and the user is therefore unsupported in recovering from them. This paper discusses how applications may be designed to better support users in dealing with the effects of quirks in data-intensive systems. </ABSTRACT></RECORD></RECORDS></XML>