The Interplay of Big Data, WorldCat, and Dewey

As the premier example of big data in the bibliographic world, WorldCat has the potential to support knowledge discovery in many arenas. After giving evidence for a big data characterization of WorldCat, the paper explores this knowledge discovery potential from two perspectives related to the Dewey Decimal Classification (DDC) system: (1) how WorldCat data can inform development of the DDC (classification analytics) and (2) how DDC-classified content in WorldCat can shed light on the bibliographic world itself (collection analytics). In the realm of classification analytics, WorldCat data support decisions to modify the DDC by expanding or reducing the number of classes, adding topical coverage, or adding subject access points; data analysis can support recognition of (1) trending topics and (2) the faceted structure of subject domains. In the realm of collection analytics, the paper considers as possible applications the use of the DDC in the topical "fingerprinting" of categorized content in WorldCat or in performing a bibliographic gap analysis

The conditions of peak empiricism in big data and interaction design

An influx of mechanisms for the collection of large sets of data has prompted widespread consideration of the impact that data analytic methods can have on a number of disciplines. Having an established record of the use of a unique mixture of empirical methods, the work of understanding and designing for user behavior is well situated to take advantage of the advances claimed by “big data” methods. Beyond any straightforward benefit of the use of large sets of data, such an increase in the scale of empirical evidence has far-reaching implications for the work of empirically guided design. We develop the concept of “peak empiricism” to explain the new role that large-scale data comes to play in design, one in which data become more than a simple empirical tool. In providing such an expansive empirical setting for design, big data weakens the subjective conditions necessary for empirical insight, pointing to a more performative approach to the relationship between a designer and his or her work. In this, the work of design is characterized as “thinking with” the data in a partnership that weakens not only any sense of empiricism but also the agentive foundations of a classical view of design work

2nd Workshop on Research in the Large : Using App Stores, Wide Distribution Channels and Big Data in UbiComp Research

With the proliferation of app stores and the advancement of mobile devices, research that might have only been tested with a dozen participants in the past can now be released to millions. This offers huge opportunities, but also requires adaptations of existing methods in dealing with large deployments and making sense of large data sets. This workshop provides a forum for researchers to exchange experiences and strategies for wide distribution of applications as well as gathering and analyzing the large- scale data sets the result from these deployments

2nd Workshop on Research in the Large : Using App Stores, Wide Distribution Channels and Big Data in UbiComp Research

With the proliferation of app stores and the advancement of mobile devices, research that might have only been tested with a dozen participants in the past can now be released to millions. This offers huge opportunities, but also requires adaptations of existing methods in dealing with large deployments and making sense of large data sets. This workshop provides a forum for researchers to exchange experiences and strategies for wide distribution of applications as well as gathering and analyzing the large- scale data sets the result from these deployments