Faculty Seminar On Collaboration Syllabus

This is a collectively-built, in-progress syllabus for a faculty seminar on the topic of collaboration at Swarthmore College, Spring 2016. Topics include competing definitions of collaboration across disciplines, formal and informal collaboration, rich descriptions of collaboration, metrics and measures of collaborations, digital and analog tools for collaboration, literary and historical forms of collaboration, cost/benefit analyses of collaboration, crossinstitutional collaborations, institutional versus individual collaborations, collaboration narratives, failed or tragic collaborations, and teaching collaborations. Seminar members include statisticians, historians, psychologists, visual artists, literary critics, physicists, philosophers, engineers, education studies researchers, linguists, art historians, and computer scientists. Our format will accommodate both discussions of readings based on the syllabus as well as small experiments, and planning for possible future related projects

Privacy-Friendly Collaboration for Cyber Threat Mitigation

Sharing of security data across organizational boundaries has often been advocated as a promising way to enhance cyber threat mitigation. However, collaborative security faces a number of important challenges, including privacy, trust, and liability concerns with the potential disclosure of sensitive data. In this paper, we focus on data sharing for predictive blacklisting, i.e., forecasting attack sources based on past attack information. We propose a novel privacy-enhanced data sharing approach in which organizations estimate collaboration benefits without disclosing their datasets, organize into coalitions of allied organizations, and securely share data within these coalitions. We study how different partner selection strategies affect prediction accuracy by experimenting on a real-world dataset of 2 billion IP addresses and observe up to a 105% prediction improvement.Comment: This paper has been withdrawn as it has been superseded by arXiv:1502.0533

Measuring collaborative emergent behavior in multi-agent reinforcement learning

Multi-agent reinforcement learning (RL) has important implications for the future of human-agent teaming. We show that improved performance with multi-agent RL is not a guarantee of the collaborative behavior thought to be important for solving multi-agent tasks. To address this, we present a novel approach for quantitatively assessing collaboration in continuous spatial tasks with multi-agent RL. Such a metric is useful for measuring collaboration between computational agents and may serve as a training signal for collaboration in future RL paradigms involving humans.Comment: 1st International Conference on Human Systems Engineering and Design, 6 pages, 2 figures, 1 tabl

Searching Research Excellence: An in-depth bibliometric analysis of the international research contribution of the University of Granada

The main goal of this report is to offer a comprehensive portray of the research performance and impact of the University of Granada. It presents a bibliometric longitudinal analysis for the 1980-2013 time period, including bibliometric indicators for 195 subject categories. Hence showing a general analysis and specific analyses by subjects. These 195 analyses by subjects show the strengths and weaknesses of the research system. Thus, the reader may identify the disciplines in which the University of Granada currently or historically has been more productive or had a greater impact. These disciplines comprise four broad areas: Humanities & Social Sciences, Engineering & Technology, Exact & Natural Sciences, and Life & Health Sciences. The report is directed to the academic staff of the University of Granada. Its objective is to show the state of research at the university in an accurate and reliable fashion. There is a brief bibliometric report for each subject category which showcases research trends, bibliometric indicators and a list of the most productive researchers.Universidad de Granada. Vicerrectorado de Investigación y Política Científica

Opportunities and challenges in designing a blended international student project activity: Experiences from the EPIC project

In this paper we explain our experiences and observations on a blended international teaching/training student project activity designed for students of different academic levels and programs at different universities working together on a project given by an industrial partner. This project activity is designed based on the EPIC project, funded by the Erasmus+ programme of the European Commission, which aims to provide a framework for carrying out multi-cultural and multidisciplinary student projects for increasing employability in an international job market.Peer ReviewedPostprint (author's final draft

Providing behaviour awareness in collaborative project courses

Several studies show that awareness mechanisms can contribute to enhance the collaboration process among students and the learning experiences during collaborative project courses. However, it is not clear what awareness information should be provided to whom, when it should be provided, and how to obtain and represent such information in an accurate and understandable way. Regardless the research efforts done in this area, the problem remains open. By recognizing the diversity of work scenarios (contexts) where the collaboration may occur, this research proposes a behaviour awareness mechanism to support collaborative work in undergraduate project courses. Based on the authors previous experiences and the literature in the area, the proposed mechanism considers personal and social awareness components, which represent metrics in a visual way, helping students realize their performance, and lecturers intervene when needed. The trustworthiness of the mechanisms for determining the metrics was verified using empirical data, and the usability and usefulness of these metrics were evaluated with undergraduate students. Experimental results show that this awareness mechanism is useful, understandable and representative of the observed scenarios.Peer ReviewedPostprint (published version

Providing behaviour awareness in collaborative project courses

Several studies show that awareness mechanisms can contribute to enhance the collaboration process among students and the learning experiences during collaborative project courses. However, it is not clear what awareness information should be provided to whom, when it should be provided, and how to obtain and represent such information in an accurate and understandable way. Regardless the research efforts done in this area, the problem remains open. By recognizing the diversity of work scenarios (contexts) where the collaboration may occur, this research proposes a behaviour awareness mechanism to support collaborative work in undergraduate project courses. Based on the authors previous experiences and the literature in the area, the proposed mechanism considers personal and social awareness components, which represent metrics in a visual way, helping students realize their performance, and lecturers intervene when needed. The trustworthiness of the mechanisms for determining the metrics was verified using empirical data, and the usability and usefulness of these metrics were evaluated with undergraduate students. Experimental results show that this awareness mechanism is useful, understandable and representative of the observed scenarios.Peer ReviewedPostprint (published version

Constructing Temporal Networks of OSS Programming Language Ecosystems

One of the primary factors that encourage developers to contribute to open source software (OSS) projects is the collaborative nature of OSS development. However, the collaborative structure of these communities largely remains unclear, partly due to the enormous scale of data to be gathered, processed, and analyzed. In this work, we utilize the World Of Code dataset, which contains commit activity data for millions of OSS projects, to build collaboration networks for ten popular programming language ecosystems, containing in total over 290M commits across over 18M projects. We build a collaboration graph representation for each language ecosystem, having authors and projects as nodes, which enables various forms of social network analysis on the scale of language ecosystems. Moreover, we capture the information on the ecosystems' evolution by slicing each network into 30 historical snapshots. Additionally, we calculate multiple collaboration metrics that characterize the ecosystems' states. We make the resulting dataset publicly available, including the constructed graphs and the pipeline enabling the analysis of more ecosystems.Comment: Accepted to SANER 202

Controlled Data Sharing for Collaborative Predictive Blacklisting

Although sharing data across organizations is often advocated as a promising way to enhance cybersecurity, collaborative initiatives are rarely put into practice owing to confidentiality, trust, and liability challenges. In this paper, we investigate whether collaborative threat mitigation can be realized via a controlled data sharing approach, whereby organizations make informed decisions as to whether or not, and how much, to share. Using appropriate cryptographic tools, entities can estimate the benefits of collaboration and agree on what to share in a privacy-preserving way, without having to disclose their datasets. We focus on collaborative predictive blacklisting, i.e., forecasting attack sources based on one's logs and those contributed by other organizations. We study the impact of different sharing strategies by experimenting on a real-world dataset of two billion suspicious IP addresses collected from Dshield over two months. We find that controlled data sharing yields up to 105% accuracy improvement on average, while also reducing the false positive rate.Comment: A preliminary version of this paper appears in DIMVA 2015. This is the full version. arXiv admin note: substantial text overlap with arXiv:1403.212