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Safe Open Science for Restricted Data

Abstract

Open science is prompting wide efforts to make data from research available for broader use. However, sharing data is complicated by important protections on the data (e.g., protections of privacy and intellectual property). The spectrum of options existing between data needing to be fully open access and data that simply cannot be shared at all is quite limited. This paper puts forth a generalized remote secure enclave as a socio-technical framework consisting of policies, human processes, and technologies that work hand in hand to enable controlled access and use of restricted data. Based on experience in implementing the enclave for computational, analytical access to a massive collection of in-copyright texts, we discuss the synergies and trade-offs that exist between software components and policy and process components in striking the right balance between safety for the data, ease of use, and efficiency.

Open access
Special Issue on Cyberinfrastructure, Machine Learning, and Digital Library
Open access
Big Data in Health Care: Applications and Challenges

Abstract

The concept of Big Data is popular in a variety of domains. The purpose of this review was to summarize the features, applications, analysis approaches, and challenges of Big Data in health care. Big Data in health care has its own features, such as heterogeneity, incompleteness, timeliness and longevity, privacy, and ownership. These features bring a series of challenges for data storage, mining, and sharing to promote health-related research. To deal with these challenges, analysis approaches focusing on Big Data in health care need to be developed and laws and regulations for making use of Big Data in health care need to be enacted. From a patient perspective, application of Big Data analysis could bring about improved treatment and lower costs. In addition to patients, government, hospitals, and research institutions could also benefit from the Big Data in health care.

Open access
Business Values/Implications of AI and Machine Learning
Open access
A Clickstream Data Analysis of the Differences between Visiting Behaviors of Desktop and Mobile Users

Abstract

Mobile devices are gaining popularity among online shoppers whose behavior has been reshaped by the changes in screen size, interface, functionality, and context of use. This study, based on a log file from a cross-border E-commerce platform, conducted a clickstream data analysis to compare desktop and mobile users’ visiting behavior. The original 2,827,449 clickstream records generated over a 4-day period were cleaned and analyzed according to an established analysis framework at the footprint level. Differences are found between desktop and mobile users in the distribution of footprints, core footprints, and footprint depth. As the results show, online shoppers preferred to explore various products on mobile devices and read product details on desktops. The E-commerce mobile application (app) presented higher interactivity than the desktop and mobile websites, thus increasing both user involvement and product visibility. It enabled users to engage in the intended activities more effectively on the corresponding pages. Mobile users were further divided into iOS and Android users whose visiting behaviors were basically similar to each other, though the latter might experience slower response speed.

Open access
Smart and Connected Health: What Can We Learn from Funded Projects?

Abstract

Following an integrated data analytics framework that includes descriptive analysis and multiple automatic content analysis, we examined 265 projects that have been funded by the National Science Foundation (NSF) under the Smart and Connected Health (SCH) program. Our analysis discovered certain characteristics of these projects, including the distribution of the funds over years, the leading organizations in SCH, and the multidisciplinary nature of these projects. We also conducted content analysis on project titles and automatic analysis on the abstracts of the projects, including term frequency/word cloud analysis, clustering analysis, and topic modeling using Biterm method. Our analysis found that five main research areas were explored in these projects: system or platform development, modeling or algorithmic development for various purposes, designing smart health devices, clinical data collection and application, and education and academic activities of SCH. Together we obtained a comparatively fair understanding of these projects and demonstrated how different analytic approaches could complement each other. Future research will focus on the impact of these projects through an analysis of their publications and citations.

Open access
Structural Analysis of Medical-Terminology Hashtag versus Lay-Language Hashtag Tweet Collections: An Information Theoretical Method with Entropy Matrix

Abstract

Healthcare communication on Twitter is challenging because the space for a tweet is limited, but the topic is too sophisticated to be concise. Comparing medical-terminology hashtags versus lay-language hashtags, this paper explores the characteristics of healthcare hashtags using an entropy matrix which derived from information theory. In this paper, the entropy matrix comprises of six different components used for constructing a tweet and serves as a framework for the structural analysis with the granularity of tweet composition. These granular components include image(s), text with semantic meanings, hashtag(s), @ username(s), hyperlink, and unused space. The entropy matrix proposed in this paper contributes to a new approach to visualizing the complexity level of hashtag collections. In addition, the calculated entropy could be an indicator of the diversity of a user’s choice across those tweet components. Furthermore, the visualizations (radar graph and scatterplot) illustrate statistical structures and the dynamics of the hashtag collections measured by entropy. The results from this study demonstrate a manifest relationship between tweet composition and the number of being retweeted.

Open access
Aspects of Innovation and Technology Transfer in Romania

Abstract

Technological information, knowledge transfer, research and innovation are factors of success in the contemporary economy. Romania is on the last place in Europe in terms of innovation, and the Romanian regions occupy the last positions the picture of the European innovation at the regional level. The paper presents a presentation of the situation of the innovation in Romania, with aspects concerning the need for innovation of SMEs. Domestic companies need innovation to cope with the European and international competition. The collaboration with the university/research institutes and the patent/license acquisition have a low share, showing the lack of technology transfer and of certain partnerships between the business environment and the research area.

The establishment of networks specialized in technological transfer, with government support, can be a solution for the sustainable growth of the national economy.

Open access
Competitiveness for Knowledge Society: from Nature to New Developments and Challenges

Abstract

This article tracks the emergence of the concept of competitiveness. A historical review of the achievements of foreign and Bulgarian authors is presented, as well as a grounded critical assessment of the different aspects of the category under consideration. An aggregate assessment of the achievements at the present stage is provided. Few directions for new developments and challenges of competitiveness research are outlined.

Open access
The Corelation between Labour Market and Education – Results of a Comparative Study Conducted in the Hungarian, Romanian and British Educational Systems

Abstract

The present study aims at highlighting some of the impacts that labour market an education mutually have on each other both in the context of economies in transition (even if they used to have long historic traditions related to pioneering in instruction and education at mass and elite level) and that of a steady and consequent capitalist state undisturbed by the storms of radical political changes and periods of totally negating the values and results created by former historic eras and communities.

The main idea is that the relationship between the labour market and education is that of a mutual demand and supply based corelation, permanently influencing each other, so no political or economic authority and power should miss taking this into consideration unless they want to fail.

Open access