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The importance of involving humans in the data science process has been widely discussed in the literature. However, studies lack details on how to involve humans in the process. Using a design science approach, this paper proposes and evaluates a human‐supervised data science framework in the context of local governments. Our findings suggest that the involvement of a stakeholder group, public managers in this case, in the process of data science project enhanced quality of data science outcomes. Public managers' detailed knowledge on both the data and context was beneficial for improving future data science infrastructure. In addition, the study suggests that local governments can harness the value of data‐driven approaches to policy and decision making through focalized investments in improving data and data science infrastructure, which includes culture and processes necessary to incorporate data science and analytics into the decision‐making process. [ABSTRACT FROM AUTHOR]

The amount of scientific papers is growing together with the development of science itself; but, although there is an unprecedented availability of large citation indexes, some daily activities of researchers remain time‐consuming and poorly supported. In this paper, we present Visual Bibliographies (VisualBib), a real‐time visual platform, designed using a zz‐structure‐based model for linking metadata and a narrative, visual approach for showing bibliographies. VisualBib represents a usable, advanced, and visual tool, which simplifies the management of bibliographies, supports a core set of bibliographic tasks, and helps researchers during complex analyses on scientific bibliographies. We present the variety of metadata formats and visualization methods, proposing two use case scenarios. The maturity of the system implementation allowed us two studies, for evaluating both the effectiveness of VisualBib in providing answers to specific data analysis tasks and to support experienced users during real‐life uses. The results of the evaluation are positive and describe an effective and usable platform. [ABSTRACT FROM AUTHOR]

Recommender systems are changing the way that people find information, products, and even other people. This paper studies the problem of leveraging the context of the items presented to the user in a user/system interaction session to improve the recommender system's ranking prediction. We propose a novel model that incorporates the opportunity cost of giving up the other items in the session and computes session‐specific relevance values for items for context‐aware recommendation. The model can work on a variety of different problems settings with emphasis on implicit user feedback as it supports varying levels of ordinal relevance. Experimental evaluation demonstrates the advantages of our new model with respect to the ranking quality. [ABSTRACT FROM AUTHOR]

The music information retrieval ( MIR) community has long understood the role of evaluation as a critical component for successful information retrieval systems. Over the past several years, it has also become evident that user-centered evaluation based on realistic tasks is essential for creating systems that are commercially marketable. Although user-oriented research has been increasing, the MIR field is still lacking in holistic, user-centered approaches to evaluating music services beyond measuring the performance of search or classification algorithms. In light of this need, we conducted a user study exploring how users evaluate their overall experience with existing popular commercial music services, asking about their interactions with the system as well as situational and personal characteristics. In this paper, we present a qualitative heuristic evaluation of commercial music services based on Jakob Nielsen's 10 usability heuristics for user interface design, and also discuss 8 additional criteria that may be used for the holistic evaluation of user experience in MIR systems. Finally, we recommend areas of future user research raised by trends and patterns that surfaced from this user study. [ABSTRACT FROM AUTHOR]

This paper presents a novel user interface that provides global visualizations of large document sets in order to help users to formulate the query that corresponds to their information needs and to access the corresponding documents. An important element of the approach we introduce is the use of concept hierarchies (CHs) in order to structure the document collection. Each CH corresponds to a facet of the documents users can be interested in. Users browse these CHs in order to specify and refine their information needs. Additionally the interface is based on OLAP principles and multi-dimensional analysis operators are provided to users in order to allow them to explore a document collection. [ABSTRACT FROM AUTHOR]