Online library catalogs, Library catalogs & users, Library catalog use studies, Mobile apps, Application software, Data analysis, Academic libraries, Rapid prototyping, College students, Formative evaluation, Wayfinding, and Performance evaluation
This research presents the results of a project that investigated how students use a library developed mobile app to locate books in the library. The study employed a methodology of formative evaluation so that the development of the mobile app would be informed by user preferences for next generation wayfinding systems. A key finding is the importance of gathering ongoing user feedback for designing useful and used mobile academic library applications. Elements and data points to include in future mobile interfaces are discussed. [ABSTRACT FROM AUTHOR]
Schulz, Axel, Loza Mencía, Eneldo, and Schmidt, Benedikt
Information Systems. Apr2016, Vol. 57, p88-110. 23p.
Information theory, Microblogs, Information resources, Rapid prototyping, Traffic accidents, and Emergency management
Small scale-incidents such as car crashes or fires occur with high frequency and in sum involve more people and consume more money than large and infrequent incidents. Therefore, the support of small-scale incident management is of high importance. Microblogs are an important source of information to support incident management as important situational information is shared, both by citizens and official sources. While microblogs are already used to address large-scale incidents detecting small-scale incident-related information was not satisfyingly possible so far. In this paper we investigate small-scale incident reporting behavior with microblogs. Based on our findings, we present an easily extensible rapid prototyping framework for information extraction of incident-related tweets. The framework enables the precise identification and extraction of information relevant for emergency management. We evaluate the rapid prototyping capabilities and usefulness of the framework by implementing the multi-label classification of tweets related to small-scale incidents. An evaluation shows that our approach is applicable for detecting multiple labels with an match rate of 84.35%. [ABSTRACT FROM AUTHOR]