Unpacking the “black box”: a preliminary study of visualizing humanists and social science scholars’ data and research processes

Due to the significant variations in their needs, attitudes, and practices toward their research, different scholars could have different research processes and interact with different kinds of data. We report the preliminary results of a qualitative study that examines how humanities and social science (H&SS) scholars interact with their data throughout the course of their research process. By conducting two focus group sessions with eight H&SS scholars, our results show that scholars indeed took different research patterns and thus interacted with distinctive data. The sketches produced in this study provide insights on future larger-scale focus group design, and also identify opportunities for an academic library or data service provider to support H&SS scholars’ research activities

DataCite as a novel bibliometric source: Coverage, strengths and limitations

This paper explores the characteristics of DataCite to determine its possibilities and potential as a new bibliometric data source to analyze the scholarly production of open data. Open science and the increasing data sharing requirements from governments, funding bodies, institutions and scientific journals has led to a pressing demand for the development of data metrics. As a very first step towards reliable data metrics, we need to better comprehend the limitations and caveats of the information provided by sources of open data. In this paper, we critically examine records downloaded from the DataCite's OAI API and elaborate a series of recommendations regarding the use of this source for bibliometric analyses of open data. We highlight issues related to metadata incompleteness, lack of standardization, and ambiguous definitions of several fields. Despite these limitations, we emphasize DataCite's value and potential to become one of the main sources for data metrics development.Comment: Paper accepted for publication in Journal of Informetric

Assessment of density functional methods with correct asymptotic behavior

Long-range corrected (LC) hybrid functionals and asymptotically corrected (AC) model potentials are two distinct density functional methods with correct asymptotic behavior. They are known to be accurate for properties that are sensitive to the asymptote of the exchange-correlation potential, such as the highest occupied molecular orbital energies and Rydberg excitation energies of molecules. To provide a comprehensive comparison, we investigate the performance of the two schemes and others on a very wide range of applications, including the asymptote problems, self-interaction-error problems, energy-gap problems, charge-transfer problems, and many others. The LC hybrid scheme is shown to consistently outperform the AC model potential scheme. In addition, to be consistent with the molecules collected in the IP131 database [Y.-S. Lin, C.-W. Tsai, G.-D. Li, and J.-D. Chai, J. Chem. Phys., 2012, 136, 154109], we expand the EA115 and FG115 databases to include, respectively, the vertical electron affinities and fundamental gaps of the additional 16 molecules, and develop a new database AE113 (113 atomization energies), consisting of accurate reference values for the atomization energies of the 113 molecules in IP131. These databases will be useful for assessing the accuracy of density functional methods.Comment: accepted for publication in Phys. Chem. Chem. Phys., 46 pages, 4 figures, supplementary material include

Users’ Perceived Difficulties and Corresponding Reformulation Strategies in Voice Search

We report on users’ perceptions on query input errors and query reformulation strategies in voice search. The perceptions were collected through a controlled experiment. Our results reveal that: 1) users’ faced obstacles during a voice search that can be related to system recognition errors and topic complexity; 2) users naturally develop different strategies while dealing with varying types of words that are problematic for systems to recognize

Blastic Natural Killer-Cell Lymphoma Presenting in the Skin

AbstractBlastic natural killer (NK)-cell lymphoma is a clinically aggressive hemato-logic neoplasm with a high incidence of cutaneous involvement. We report a 19-year-old man who presented with asymptomatic, erythematous, infiltrated bean plaques and nodules of various sizes, scattered over the face, trunk and extremities. A skin biopsy specimen revealed diffuse dermal infiltration of medium-sized pleomorphic cells with a blastic appearance. Immunohistochemical studies showed that the tumor cells were positive for CD56, CD43, CD123, and terminal deoxynucleotidyl trans-ferase (TdT). The neoplastic cells were negative for B-cell, T-cell, and myeloid cell markers. In situ hybridization for Epstein-Barr virus encoded RNA (EBER) gave a negative result. Flow cytometric analysis of bone marrow aspirate demonstrated a CD56 positive population of blastic cells. A diagnosis of blastic NK-cell lymphoma was made and the skin lesions regressed after treatment with L-asparaginase-based chemotherapy (L-asparaginase, cyclophosphamide, etoposide). The skin lesions regressed after two sessions of chemotherapy

Discussing IS Alignment Results: A Classification Framework

Information system (IS) alignment has been one of the most important topics recognized by management since the last decade. However, it is a complex concept. Although some classification frameworks and guidelines have been suggested, they are only useful to understand the nature of alignment constructs and the types of relationships between them. None of them classifies the ways of discussing alignment results which are the final outcomes of an alignment assessment that describe the extent and appropriateness of various constructs to one another. This paper suggests a framework to help understand how alignment results can be discussed, which includes four perspectives. It is expected that the framework can help not only readers understand IS alignment research, but also IS researchers initiate appropriate alignment research projects. Several future research projects based on this framework are also revealed

The Effect of Mobile Gamification on Brand Loyalty

The purpose of this study is mainly to use the gamification concept to design a mobile gaming app (application) for contextual marketing, and we will integrate digital game design technologies, such as augmented reality (AR) and global positioning system (GPS). The study will then look at associated consumer value and brand loyalty created by the users after experiencing the mobile game. Accordingly, we define the eight elements of a mobile gamification design, including coping-escape, fantasy, recreation, social, omnipotence, competition, skill development, and location-based. This research model treats “location-based” as a formative second-order construct driven by ubiquitous connectivity and contextual offer. Consumer value and brand loyalty are also a second-order construct. The study will conduct a quasi-experimental research to verify our model. It is hoped that service managers can benefit from the insights discovered from this study and implement more effective management strategies for effective performance

Toward a conceptual framework for data sharing practices in social sciences: A profile approach. In the proceedings of the ASIS&T 2016 Annual Meeting

This paper investigates the landscape of data-sharing practices in social sciences via the data sharing profile approach. Guided by two pre-existing conceptual frameworks, Knowledge Infrastructure (KI) and the Theory of Remote Scientific Collaboration (TORSC), we design and test a profile tool that consists of four overarching dimensions for capturing social scientists’ data practices, namely: 1) data characteristics, 2) perceived technical infrastructure, 3) perceived organizational context, and 4) individual characteristics. To ensure that the instrument can be applied in real and practical terms, we conduct a case study by collecting responses from 93 early-career social scientists at two research universities in the Pittsburgh Area, U.S. The results suggest that there is no significant difference, in general, among scholars who prefer quantitative, mixed method, or qualitative research methods in terms of research activities and data-sharing practices. We also confirm that there is a gap between participants’ attitudes about research openness and their actual sharing behaviors, highlighting the need to study the “barrier” in addition to the “incentive” of research data sharing