Report of the 2014 NSF Cybersecurity Summit for Large Facilities and Cyberinfrastructure

This event was supported in part by the National Science Foundation under Grant Number 1234408. Any opinions, findings, and conclusions or recommendations expressed at the event or in this report are those of the authors and do not necessarily reflect the views of the National Science Foundation

Distributed real-time hybrid simulation: Modeling, development and experimental validation

Real-time hybrid simulation (RTHS) has become a recognized methodology for isolating and evaluating performance of critical structural components under potentially catastrophic events such as earthquakes. Although RTHS is efficient in its utilization of equipment and space compared to traditional testing methods such as shake table testing, laboratory resources may not always be available in one location to conduct appropriate large-scale experiments. Consequently, distributed systems, capable of connecting multiple RTHS setups located at numerous geographically distributed facilities through information exchange, become essential. This dissertation focuses on the development, evaluation and validation of a new distributed RTHS (dRTHS) platform enabling integration of physical and numerical components of RTHS in geographically distributed locations over the Internet.^ One significant challenge for conducting successful dRTHS over the Internet is sustaining real-time communication between test sites. The network is not consistent and variations in the Quality of Service (QoS) are expected. Since dRTHS is delay-sensitive by nature, a fixed transmission rate with minimum jitter and latency in the network traffic should be maintained during an experiment. A Smith predictor can compensate network delays, but requires use of a known dead time for optimal operation. The platform proposed herein is developed to mitigate the aforementioned challenge. An easily programmable environment is provided based on MATLAB/xPC. In this method, (i) a buffer is added to the simulation loop to minimize network jitter and stabilize the transmission rate, and (ii) a routine is implemented to estimate the network time delay on-the-fly for the optimal operation of the Smith predictor.^ The performance of the proposed platform is investigated through a series of numerical and experimental studies. An illustrative demonstration is conducted using a three story structure equipped with an MR damper. The structure is tested on the shake table and its global responses are compared to RTHS and dRTHS configurations where the physical MR damper and numerical structural model are tested in local and geographically distributed laboratories.^ The main contributions of this research are twofold: (1) dRTHS is validated as a feasible testing methodology, alternative to traditional and modern testing techniques such as shake table testing and RTHS, and (ii) the proposed platform serves as a viable environment for researchers to develop, evaluate and validate their own tools, investigate new methods to conduct dRTHS and advance the research in this area to the limits

When do Researchers Collaborate? Toward a Model of Collaboration Propensity in Science and Engineering Research

Geographically distributed and multidisciplinary collaborations have proven invaluable in answering a range of important scientific questions, such as understanding and controlling disease threats like SARS and AIDS or exploring the nature of matter in particle physics. Despite this, however, collaboration can often be problematic. There are institutional obstacles, collaboration tools may be poorly designed, and group coordination is difficult. To better design technologies to support research activities, we need an improved understanding of why scientists collaborate and how their collaborations work. To achieve this improved understanding, this study compares two theoretical approaches to collaboration propensity—that is, the extent to which collaboration is perceived as useful by individual researchers. On one hand, cultural comparisons of disciplines suggest that collaboration propensity will be higher in disciplinary cultures that have a more collectivist orientation, as indicated by low levels of competition for individual recognition and few concerns about secrecy related to commercialization and intellectual property. In contrast, an approach based on social and organizational psychology suggests that collaboration propensity will vary as a function of resource concentration, fieldwide focus on a well-defined set of problems, and the need for and availability of help when difficult problems are encountered in day-to-day work. To explore this question, a mail survey of 900 academic researchers in three fields was conducted, along with 100 interviews with practicing researchers at 17 sites in the field. Results support a focus on work attributes in interpreting collaboration propensity. That is, cultural factors such as competition for individual recognition and concerns about intellectual property were not perceived as significant impediments to collaboration. Instead, characteristics like resource concentration and the need for coordination were more important in determining collaboration propensity. Implications of these findings include a call for more careful examination of the day-to-day work of scientists and engineers, and a suggestion that concerns about scientific competition impeding collaboration may be unwarranted.Ph.D.InformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/39375/2/Birnholtz.dissertation_final.pd

1st year EFAST annual report

The present report provides information about the activities conducted during the 1st year of the EFAST project. The first chapter is dedicated to describe the inquiries conducted at the beginning of the project and to briefly summarise the main results. The second chapter is dedicated to the first EFAST workshop where some of the leading scientists in the field of earthquake engineering have met to discuss about the need and the technologies related to earthquake engineering. The third chapter contains a state of the art and future direction in seismic testing and simulation. The final chapter is dedicated to describe the preliminary design of the web portal of the future testing facility.JRC.DG.G.5-European laboratory for structural assessmen

WHY DO PROJECT PARTICIPANTS WORK TOGETHER? AN INVESTIGATION OF THE ANTECEDENTS OF COLLABORATION TIE STRENGTH IN CYBERINFRASTRUCTURE PROJECTS

A cyberinfrastructure (CI) project is a new form of large-scale distributed project that is different from other information systems projects, including open source software projects and distributed organizational information systems development projects. These projects may share some similarities but they also have many striking differences, including differences in goals, funding, participants, control types and coordination mechanisms. A CI project aims to build a complex digital infrastructure to enable innovative and transformative research. Such digital infrastructure offers scientists and researchers a set of connected resources including laboratories, databases, computer hardware, software and people, so that they can conduct research that addresses complex questions that are beyond the capability of any individual person or institution. CI Projects are grand in scope and challenging to execute. Successfully building cyberinfrastructure requires intense and sustained collaborative efforts of people from diverse backgrounds and disciplines and from different organizations and institutions. However, collaboration among key project participants is a complex phenomenon. In part, due to the different backgrounds and knowledge of the project participants, a number of factors may promote or hinder their collaboration. Furthermore, individuals associated with efforts to build cyberinfrastructure, unlike individuals involved in projects within traditional organizational settings, are free to choose with whom they want to collaborate. Therefore, collaboration in CI projects is not assigned as is typical in organizational projects but rather involves individual choices to collaborate. Understanding the factors that promote collaboration will not only help us better understand individual behaviors, but also provide insights for the project management team in crafting better strategies to promote collaboration. This study intends to examine the antecedents of collaboration tie strength among CI project participants. The research question I address is: what are the antecedents of collaboration tie strength in cyberinfrastructure projects? Since a CI project is both technologically intensive and socially complex, I examine the antecedents of collaboration tie strength from both the technological perspective and the social perspective. More importantly, this study also examines: how these social factors and technological factors interact with each other in predicting collaboration tie strength? The research site is a National Science Foundation (NSF) funded CI project, named The Global Environment for Network Innovations (GENI ). This project intends to build a digital infrastructure for networking scientists to explore the next generation Internet at scale. The major stakeholders involved in this project include computer scientists and researchers, government agencies, industrial professionals and students. By the time of this study, GENI had gone through two phases: pre-planning and planning. The construction phase was ongoing. Pre-planning phase consists of events before 2004, by which time NSF agreed to support GENI and hired key individuals to drive the initiative. The planning phase began in 2004 and lasted until 2008. In this phase, groups of researchers and sponsors worked together to shape the idea of the GENI project in terms of its vision, goals and organization. The construction phase commenced in 2008. This phase featured development activities to build the specific CI technologies in different GENI technical clusters and to roll out the GENI projects to a larger scale. The management team, GENI Project Office (GPO), adopted a spiral development approach (Boehm 1986), with each spiral involving steps of a complete project development lifecycle. A spiral began with the GPO setting out goals and allocating funds to different project teams. Each spiral lasted one year, so that each spiral ended after a year of complete project development cycle. At that point the performance of these projects was reviewed, and the evaluation results became, in part, the basis for funding decisions of the next spiral. In each spiral, the overall GENI project was divided into many smaller projects. A major form of collaboration among individuals involved in GENI, or interested in becoming involved in GENI, is through forming project teams. Each individual can choose to work with others on a specific project. An individual can also work on multiple projects with different people. At the time of this study, the GENI project completed four spirals (1 to 4), and the project was still ongoing. My study focuses on the most recent spiral at the time of this study, i.e., project spiral 4, which includes around 126 projects with an average of five people on each project. The unit of analysis is the dyad of collaborative individuals. The dependent variable is collaboration tie strength, i.e., the number of projects two individuals both worked on in the GENI project spiral 4 weighted by the project size. The study examines the antecedents of collaboration tie strength from both the technological and social perspectives. From the technological perspective, knowledge dependency, technical dependency and resource dependency are considered to positively predict collaboration tie strength. From the social perspective, power distance, social similarity and familiarity are considered to positively predict collaboration tie strength. Furthermore, the study examines the interactions between the three social factors and the three technological factors in predicting collaboration tie strength. Three main sets of analyses are carried out to test the hypotheses with collaboration tie strength as the dependent variable. In the first set of analyses, collaboration tie strength, is measured as a binary variable and the full dataset is used for the analysis with logistic regression as the regression method. This set of analyses helps show how the different social and technological factors predict whether two people collaborate. In the second set of analyses, collaboration tie strength, is measured as a numeric count variable and the full data is used for the analysis with Poisson regression as the regression method. This set of analyses helps show how the different social and technological factors predict how many times two people collaborate. In the third set of analyses, collaboration tie strength, is still measured as a numeric count variable but only the partial dataset where collaboration tie strength is non-zero is used for the analysis with Poisson regression as the regression method. This set of analyses helps show how the different social and technological factors predict how many times two people collaborate for those who actually collaborated. The results suggest that resource dependency, technical dependency and familiarity all significantly positively predict whether two people collaborate. Resource dependency and familiarity positively predict the number of times two people collaborate. Technical dependency and familiarity positively predict the number of times two people collaborate for those who actually collaborated. Overall, technological factors yield stronger positive prediction for collaboration tie strength than social factors. Interactions between certain technological factors and social factors are also found to be significant, with all interaction coefficients being negative. In particular, similarity and familiarity both suppress the prediction of resource dependency on whether two people collaborate. Power distance suppresses the prediction of technical dependency on how many times two people collaborate for those who actually collaborated. Despite all the interaction effects, the prediction of all social and technological factors remains positive. This study makes both theoretical and practical contributions. From the theoretical perspective, through the empirical study on the GENI project, the work not only contributes to the IS research on IT collaboration, but also answers the calls for more IS research on CI projects. From the practical perspective, the findings of this study suggest to CI project managers and fund providers that collaboration in CI projects is a very complicated phenomenon. It evolves, changes and depends on many factors. By providing a fine-grained view of how different social and technological factors interact and predict collaboration tie strength, this study may help project management in crafting better strategies to promote collaboration

Data Information Literacy: Librarians, Data, and the Education of a New Generation of Researchers

Given the increasing attention to managing, publishing, and preserving research datasets as scholarly assets, what competencies in working with research data will graduate students in STEM disciplines need to be successful in their fields? And what role can librarians play in helping students attain these competencies? In addressing these questions, this book articulates a new area of opportunity for librarians and other information professionals, developing educational programs that introduce graduate students to the knowledge and skills needed to work with research data. The term “data information literacy” has been adopted with the deliberate intent of tying two emerging roles for librarians together. By viewing information literacy and data services as complementary rather than separate activities, the contributors seek to leverage the progress made and the lessons learned in each service area. The intent of the publication is to help librarians cultivate strategies and approaches for developing data information literacy programs of their own using the work done in the multiyear, IMLS-supported Data Information Literacy (DIL) project as real-world case studies. The initial chapters introduce the concepts and ideas behind data information literacy, such as the twelve data competencies. The middle chapters describe five case studies in data information literacy conducted at different institutions (Cornell, Purdue, Minnesota, Oregon), each focused on a different disciplinary area in science and engineering. They detail the approaches taken, how the programs were implemented, and the assessment metrics used to evaluate their impact. The later chapters include the “DIL Toolkit,” a distillation of the lessons learned, which is presented as a handbook for librarians interested in developing their own DIL programs. The book concludes with recommendations for future directions and growth of data information literacy. More information about the DIL project can be found on the project’s website: datainfolit.org.https://docs.lib.purdue.edu/purduepress_ebooks/1042/thumbnail.jp

Information Technology Standards in eResearch: A Conceptual Model of the Primary Adoption Process in Higher Education Organizations

Current research on IT standards tends to focus on their lifecycle: from the development and selection, to their implementation and use. This work proposed an interdisciplinary perspective to analyze primary adoption process in the eResearch domain. As organizations are the core entities in the innovation process, the analysis of IT standards adoption was applied to eResearch infrastructures within higher education organizations. The core argument was built on the adopter s viewpoint as it provides the most explanatory process about adoption. Two international case studies probed the suitability of a model to identify the determinant role of factors like external and internal networks, top management support and organization structure. This dissertation delivers new insights that contribute to bring certainty about one relevant context of standards adoption

Innovations and advances in structural engineering: Honoring the career of Yozo Fujino

This special issue of Smart Structures and Systems (SSS) is dedicated to Dr. Yozo Fujino to celebrate his outstanding and innovative contributions to structural engineering during his career. The papers in this issue present a wide range of recent results on bridge dynamics, wind and earthquake effects on structures, health monitoring, and passive/active control technology. This collection of papers also provides a glimpse into the broad nature of Dr. Fujino’s interests. Prof. Fujino is an internationally recognized leader who has been an inspiration to industrial and academic scientists and engineers for over 30 years. During his brilliant academic career, Prof. Fujino has made and continues to make fundamental contributions to dynamics, control and monitoring of bridges considering both wind actions and earthquakes loading. In addition, he has consulted on over 30 signature bridge projects including Akashi Kaikyo Bridge in Japan, Millennium Bridge (vibration control) in UK and Stonecutters Bridge in Hong Kong, demonstrating his recognition not only for his research achievements, but also for his practical knowledge and experience in bridge engineering. In addition to his numerous contributions to science and engineering, Dr. Fujino is a dedicated and passionate teacher and professor, inspiring young scientists and engineers to advance their knowledge and experiences. Dr. Fujino is currently a Distinguished Professor of Advanced Sciences at Yokohama National University (YNU) in Japan. He is also jointly appointed as a Program Director (Policy Adviser) for the Council for Science, Technology and Innovation, Cabinet Office, Japanese Government. Prior to joining YNU, he served for more than 30 years as a Professor of Civil Engineering and the head of the Bridge and Structures Laboratory at The University of Tokyo. On behalf of all the contributors to this special issue, we would like to sincerely congratulate Dr. Yozo Fujino on a truly amazing career and wish him good health, happiness, and many more contributions to structural engineering in the years to come.Ope

Connecting Researchers to Repositories IMLS Project Report

Abstract: Despite a general consensus that making research data available is beneficial to many stakeholders, data sharing/curation is still not performed as an integrated step in most research lifecycles or common practice in the academic setting. Given many efforts over the last several years, why aren’t repositories used more by researchers? This question was explored in two workshops meant to consider the next steps in developing the Data Curation Profiles (DCP) Toolkit. It identifies a unique approach to help efforts to increase data deposits in research data repositories from an entrepreneurial perspective

A cyber-physical approach to the optimal design of civil structures using boundary layer wind tunnels and mechatronic models

The threat of wind-related hazards to vulnerable coastal locations necessitates the development of economical approaches to design and construct resilient buildings. This study investigates using a cyber-physical systems (CPS) approach as a replacement for traditional trial-and-error methods for civil infrastructure design for wind loads. The CPS approach combines the accuracy of boundary layer wind tunnel (BLWT) testing with the efficiency of numerical optimization algorithms. The approach is autonomous: experiments are executed in a BLWT, sensor feedback is monitored and analyzed, and optimization algorithms dictate physical changes to the model through actuators. The cyberinfrastructure for this project was developed with the collaboration of multiple researchers at the University of Florida Experimental Facility (UFEF) under the Natural Hazard Engineering Research Infrastructure (NHERI) program. A proof-of-concept was developed to optimally design the parapet wall of a low-rise building. Parapet walls nominally reduce suction loads on the roof but lead to an increase in positive roof pressure and base shear. A mechatronic low-rise building model was created with a parapet wall of adjustable height for BLWT testing. Various single-objective optimization algorithms were implemented to minimize the magnitude of roof wind pressures. Multi-objective optimization was used to simultaneously minimize both the magnitude of roof suction pressures and building base shear. A multi-objective procedure can consider the competing objectives of multiple stakeholders often present in engineering design. The CPS approach was extended to optimize the performance of a landmark tall building for wind loads. A 1:200 multi-degree-of-freedom (MDOF) aeroelastic model was created to represent the building in a BLWT. Aeroelastic models directly simulate the scaled dynamic behavior of the building including effects of aerodynamic damping, vortex shedding, coupling within modes, and higher modes. The model was equipped with a series of variable stiffness devices (adjustable leaf springs) in the base to enable quick adjustments to the model’s dynamics. Additionally, the model was equipped with an active fin system (AFS) consisting of individually controllable fins installed at the four corners to modify the building aerodynamics and suppress vortex-induced vibrations. Multiple design problems were explored where the model’s dynamics and aerodynamics were refined using heuristic optimization algorithms to minimize costs while satisfying acceleration and drift limits. The traditional design process for wind requires lengthy collaboration between designers and wind tunnel operators. This process may include the construction of a limited set of building models, leading to a non-exhaustive exploration of potential designs. Using mechatronic models guided by optimization algorithms enables optimum designs to be attained quicker than conventional methods. In future work, the proposed cyber-physical framework can be expanded to integrate machine learning and other computational tools to improve efficiency and reduce the reliance on experimental testing