Supermassive Black Holes in Galactic Nuclei: Past, Present and Future Research

This review discusses the current status of supermassive black hole research, as seen from a purely observational standpoint. Since the early '90s, rapid technological advances, most notably the launch of the Hubble Space Telescope, the commissioning of the VLBA and improvements in near-infrared speckle imaging techniques, have not only given us incontrovertible proof of the existence of supermassive black holes, but have unveiled fundamental connections between the mass of the central singularity and the global properties of the host galaxy. It is thanks to these observations that we are now, for the first time, in a position to understand the origin, evolution and cosmic relevance of these fascinating objects.Comment: Invited Review, 114 pages. Because of space requirements, this version contains low resolution figures. The full resolution version can be downloaded from http://www.physics.rutgers.edu/~lff/publications.htm

Linked data integration and consumption ::a case of open-interconnected application in swiss administration

Building government services with an interconnected administration approach is a worldwide trend aimed to solve the complexity of government-related processes. The connection between people and services relies on technical tools that could benefit from improvements at the data level, by more easily sharing and having a better interlinking of data from different sources. Linked data technologies have been developed to fulfill this universal need at the World Wide Web scale, and evolve it into a web of data. In this study, we move along the data lifecycle from linked data access onto its consumption and up to the design of end-users applications. As technologies for linked data publication are already at an advanced stage, we focus on the features needed for linked data consumption and present the framework we implemented in the “OverLOD Surfer” project. We apply the solution to our former work in eGovernment and semantic business process management to strengthen our assertion that the web of data approach is effective in supporting the realization of applications for an interconnected administration

Mining and visualizing social data to inform marketing decisions

Most of today's commercial companies heavily rely on social media and community management tools to interact with their clients and analyze their online behaviour. Nonetheless, these tools still lack evolved data mining and visualization features to tailor the analysis in order to support useful marketing decisions. We present an original methodology that aims at formalizing the marketing need of the company and develop a tool that can support it. The methodology is derived from the Cross-Industry Standard Process for Data Mining (CRISP-DM) and includes additional steps dedicated to the design and development of visualizations of mined data. We followed the methodology in two use cases with Swiss companies. First, we developed a prototype that aims at understanding the needs of tourists based on Flickr and Instagram data. In that use case, we extend the existing literature by enriching hashtags analysis methods with a semantic network based on Linked Data. Second, we analyzed internal customer data of an online discount retailer to help them define guerilla marketing measures. We report on the challenges of integrating Facebook data in the process. Informal feedback from domain experts confirms the strong potential of such advanced analytic features based on social data to inform marketing decisions

How to motivate participation and improve quality of crowdsourcing when building accessibility maps

Crowdsourcing, as one of the most promising tech-niques for distributed problem-solving, requires sustained human involvement. Therefore, it also brings new challenges to data management, fundamentally data input and its quality. In this paper, we looked at various forms of user motivations and quality control of crowdsourcing when building accessibility maps mobile applications. We discuss how motivations could be used to contribute to our accessibility maps scenarios, and how data can be improved for two types of participants: individual participants and organization participants. We identified three useful techniques for improving data quality: qualification-based, reputation-based, and aggregation-based. In addition, based on our own mobile application (named WEMAP), we evaluated our approaches through focus group discussions and in-depth interviews

Linked data based framework for tourism decision support system ::case study of chinese tourists in Switzerland

Switzerland is one of the most desirable European destinations for Chinese tourists; therefore, a better understanding of Chinese tourists is essential for successful business practices. In China, the largest and leading social media platform—Sina Weibo, a hybrid of Twitter and Facebook—has more than 600 million users. Weibo’s great market penetration suggests that tourism operators and markets need to understand how to build effective and sustainable communications on Chinese social media platforms. In order to offer a better decision support platform to tourism destination managers as well as Chinese tourists, we proposed a framework using linked data on Sina Weibo. Linked Data is a term referring to using the Internet to connect related data. We will show how it can be used and how ontology can be designed to include the users’ context (e.g., GPS locations). Our framework will provide a good theoretical foundation for further understand Chinese tourists’ expectation, experiences, behaviors and new trends in Switzerland