The contribution of data mining to information science

The information explosion is a serious challenge for current information institutions. On the other hand, data mining, which is the search for valuable information in large volumes of data, is one of the solutions to face this challenge. In the past several years, data mining has made a significant contribution to the field of information science. This paper examines the impact of data mining by reviewing existing applications, including personalized environments, electronic commerce, and search engines. For these three types of application, how data mining can enhance their functions is discussed. The reader of this paper is expected to get an overview of the state of the art research associated with these applications. Furthermore, we identify the limitations of current work and raise several directions for future research

Going Public When You Can in Biotechnology

Scientist-entrepreneurs prominent in biotech and other high-technology industries view going public not as a cost-effective source of capital but as a cross between selling a now-proven innovation and winning a lottery. Unlike most empirical IPO analyses confined to those firms that go public, we study substantially all the non-public biotech firms founded up through 1989. The probability that one of these firms goes public in any given year increases with the quality of the firm's science base (use of recombinant DNA technology, number of articles by star scientists as or with firm employees, number of biotech patents), the percentage of eligible firms going public the year the firm was founded as a strategy indicator, recent biotech returns as an indicator of a hot market, and whether or how many rounds of venture capital has been obtained. The same key factors increase the expected proceeds raised from IPOs, but the quality of the firm's science base plays a more dominant role. All firms going public try to look like the next Genentech, but only those with the strong science base necessary for success attract large investments.

Artificial intelligence in the cyber domain: Offense and defense

Artificial intelligence techniques have grown rapidly in recent years, and their applications in practice can be seen in many fields, ranging from facial recognition to image analysis. In the cybersecurity domain, AI-based techniques can provide better cyber defense tools and help adversaries improve methods of attack. However, malicious actors are aware of the new prospects too and will probably attempt to use them for nefarious purposes. This survey paper aims at providing an overview of how artificial intelligence can be used in the context of cybersecurity in both offense and defense.Web of Science123art. no. 41

Learning by volunteer computing, thinking and gaming: What and how are volunteers learning by participating in Virtual Citizen Science?

Citizen Science (CS) refers to a form of research collaboration that engages volunteers without formal scientific training in contributing to empirical scientific projects. Virtual Citizen Science (VCS) projects engage participants in online tasks. VCS has demonstrated its usefulness for research, however little is known about its learning potential for volunteers. This paper reports on research exploring the learning outcomes and processes in VCS. In order to identify different kinds of learning, 32 exploratory interviews of volunteers were conducted in three different VCS projects. We found six main learning outcomes related to different participants' activities in the project. Volunteers learn on four dimensions that are directly related to the scope of the VCS project: they learn at the task/game level, acquire pattern recognition skills, on-topic content knowledge, and improve their scientific literacy. Thanks to indirect opportunities of VCS projects, volunteers learn on two additional dimensions: off topic knowledge and skills, and personal development. Activities through which volunteers learn can be categorized in two levels: at a micro (task/game) level that is direct participation to the task, and at a macro level, i.e. use of project documentation, personal research on the Internet, and practicing specific roles in project communities. Both types are influenced by interactions with others in chat or forums. Most learning happens to be informal, unstructured and social. Volunteers do not only learn from others by interacting with scientists and their peers, but also by working for others: they gain knowledge, new status and skills by acting as active participants, moderators, editors, translators, community managers, etc. in a project community. This research highlights these informal and social aspects in adult learning and science education and also stresses the importance for learning through the indirect opportunities provided by the project: the main one being the opportunity to participate and progress in a project community, according to one's tastes and skills

How to Create an Innovation Accelerator

Too many policy failures are fundamentally failures of knowledge. This has become particularly apparent during the recent financial and economic crisis, which is questioning the validity of mainstream scholarly paradigms. We propose to pursue a multi-disciplinary approach and to establish new institutional settings which remove or reduce obstacles impeding efficient knowledge creation. We provided suggestions on (i) how to modernize and improve the academic publication system, and (ii) how to support scientific coordination, communication, and co-creation in large-scale multi-disciplinary projects. Both constitute important elements of what we envision to be a novel ICT infrastructure called "Innovation Accelerator" or "Knowledge Accelerator".Comment: 32 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

A review of the characteristics of 108 author-level bibliometric indicators

An increasing demand for bibliometric assessment of individuals has led to a growth of new bibliometric indicators as well as new variants or combinations of established ones. The aim of this review is to contribute with objective facts about the usefulness of bibliometric indicators of the effects of publication activity at the individual level. This paper reviews 108 indicators that can potentially be used to measure performance on the individual author level, and examines the complexity of their calculations in relation to what they are supposed to reflect and ease of end-user application.Comment: to be published in Scientometrics, 201

Where should governments invest their research funding?

Anyone observing the world in which they live can see how the outputs of research improve our life, work and environment. Some people believe that if governments invest specifically in research designed to produce immediately useful outcomes, it could ensure an even higher return on government investment. However, as the paper discusses, there are many problems with this approach, not least being that research directed at particular outcomes can fail while curiosity-led research can lead to many and varied applications which are as far reaching in their implications as they are unexpected