Daniel Zeng - US grants

EIA-9983304
Chen, Hsinchun
University of Arizona

Digital Government: COPLINK Center: Information and Knowledge Management for Law Enforcement

The information and knowledge management problems facing many government agencies stem from barriers to access and utilization resulting from the content and format of information. These problems make information (and eventually knowledge) creation and utilization and complex and daunting process. New knowledge management technologies have started to emerge in a number of different applications and organizations, such as virtual enterprising, joint ventures, aerospace engineering and digital libraries. However, there has been no systematic attempt to study the technical, social and managerial foundation, theory and methodology of knowledge management that can be adopted in various social and industrial contexts. The COPLINK Center for Excellence aims to achieve the following two goals: 1) Develop knowledge management systems technologies and methodology that are appropriate for capturing, analyzing, visualizing and sharing law enforcement related information in social and organizational contexts. The basis of such research will be grounded in information retrieval, computational linguistics, information visualization, artificial intelligence, multimedia systems, multi-agent systems, and telecommunications. 2) Study of organizational, social, cultural and methodological impacts and changes that organizations need to make to maximize and leverage on a law enforcement agency's investments in information and knowledge management. The academic foundation for such research will be based on social informatics, decision theory, communication theory, cognitive psychology and managerial and organizational research.

The proposed research is aimed at designing and developing new resources for information and knowledge management in a heterogeneous distributed environment for law enforcement. Important problem areas to be addressed are: system scalability, group-based monitoring of dynamically changing data, analyzing group behavior in search and notification, and incremental searching, among others
The technical approach will be implemented in an agent-based framework and empirical studies will be performed to evaluate the proposed prototype in two law enforcement agencies.

Students from a variety of disciplines take Microeconomics courses to learn how various types of markets function and how enterprises and consumers make buying and selling decisions in these markets. As such, Microeconomics education plays an important role in preparing future business leaders and practitioners and serves as part of general business and social sciences training for students in other fields of study. Currently, Microeconomics courses are typically taught in a traditional lecture format. Recent developments in economic theory and electronic commerce, however, call for significant innovations in course content design and delivery. An emerging trend is to allow the students to actively participate in economic decision-making through various market institutions, including recently emerging Internet-based online market institutions, to gain hands-on experience and acquire economic insights. Constructivist learning theory supports this educational approach. It promises to revolutionize the way in which Microeconomics courses will be taught in this new Millennium. Although several efforts have been initiated to create online Microeconomics contents, including experimentation tools and software, they have been developed in a system development and content collection paradigm that is closed and therefore cannot scale. In this project we are creating a Digital Library (DL)-based, open approach to deal with the challenges of developing an extensible and scalable collection of Microeconomics related contents.
(a) From the perspective of the application domain, i.e., Microeconomics, we are making contributions in creating new types of digital contents, including simulated IT-enhanced market institutions and intelligent trading systems implemented as software agents. These agents are emerging as part of the IT-enhanced electronic market institutions that have the potential of greatly reducing economic transaction costs and improving the quality of economic decision-making.
(b) From the viewpoint of the National STEM Digital Library, we are creating an Open Archives Initiative (OAI)-compliant collection of Microeconomics education contents that incorporates experimental software and automated e-commerce agents. A major DL research task that we are undertaking is the development of a metadata representation of active objects such as software modules (e.g., economics experimental software). This research has the potential of being applied in other DL collections involving software and simulation environments.
(c) From the educational viewpoint, we are developing new integrated Microeconomics curricula leveraging the developed active objected-based DL. We are studying the impact of these new curricula, and investigating related changes in course management and teaching methodologies. We are combining research, teaching, and evaluation expertise and resources from several academic departments and labs at the University of Arizona. Four key contributing entities are: (1) the Economic Science Lab, a premier institution on experimental economics methodology and applications, (2) the Artificial Intelligence Lab, a leading institution on DL, Internet computing, and software agents, (3) the Hoffman E- Commerce Lab, an instructional and research facility focusing on e-commerce teaching and research, and (4) the University Faculty Center for Instructional Innovation, a teaching evaluation facility with emphasis on the impact of IT on education.

Abstract

EIA-0326348
Hsinchun, Chen
Title: ITR: COPLINK Center for Intelligence and Security Informatics Research- A Crime Data Mining Approach to Developing "Border Safe" Research.



The main intended intellectual contribution of our research is three-fold: (a) developing new data mining, text mining, and knowledge discovery models and techniques that are motivated by law enforcement applications but can also be applied in other domains demonstrating similar characteristics, (b) developing new representations, models, and computational methods for scalable networks from other data mining applications, and (c) studying the acceptance and adoption of the developed crime data mining technologies in real-world settings and obtaining a comprehensive understanding of related policy implications including information sharing and privacy issues.
The broader impacts of this research include: reducing cognitive and information overload in law enforcement applications; improving intelligence and law enforcement agencies' abilities to detect, prevent, and respond to crimes and terrorism events; fostering information sharing and collaboration among law enforcement agencies; and providing a large-scale research testbed for NSF KDD and "border safe" researches.
The proposed research effort will leverage our highly successful past and ongoing work on the COPLINK system, our prior research experience on data mining, text mining, web computing, and information retrieval in other application domains, and our extensive ongoing partnerships with local, state, and federal law enforcement agents.

EIA- 0317269
Hsinchun Chen
University of Arizona

Title: NSF Workshop: Symposium on Intelligence and Security Informatics

This NSF Workshop: Symposium on Intelligence and Security Informatics aims to provide an intellectual forum of discussions among previously disparate communities: academic researchers (in information technology, computer science, public policy, and social studies), local, state, and federal law enforcement and intelligence experts, and information technology industry consultants and practitioners. The workshop will bring together noted informatics, computer science, and policy researchers and progressive leaders in law enforcement and security communities to engage in productive dialogues and explore avenues of collaboration. The workshop will help identify promising computer science and informatics techniques and methodologies for national security applications, and help develop close and productive partnerships between researchers and local and federal law enforcement practitioners. The Symposium on Intelligence and Security Informatics will solicit high-quality research papers of relevance to intelligence and security research, which will be peer reviewed by both researchers and practitioners.

Infectious disease outbreaks, either naturally occurring or caused by terror attacks, pose a critical threat to public health and national security. Information systems and infectious disease informatics (IDI) research are playing an increasingly important role in developing a comprehensive approach to prevent, detect, respond to, and manage infectious disease outbreaks. Computerized datasets on infectious diseases are currently used for disease reporting, including those developed by various federal, state, and local health, agriculture, and environment/wildlife agencies. However, such datasets are typically not interoperable, particularly in across jurisdiction and across species contexts, reducing their effective use in data modeling and analysis, disease surveillance, and disease management-related decision-making. In addition, the information management environment used by public health officials and researchers to analyze large amounts of infectious disease data and develop predictive models needs major improvements.

A partnership has been developed with expertise in IDI, mission-critical Web-based interoperable systems, data security and access control, advanced data mining and visualization techniques, disease surveillance and predictive modeling, and information systems evaluation. The partnership includes: (1) the Artificial Intelligence Laboratory at the University of Arizona, (2) the Information Systems Group at the University of Utah, (3) the New York State Department of Health and its partner Health Research, Inc., and (4) the California State Department of Health Services and its partner PHFE Management Solutions.

Building on ongoing IDI research and infrastructure development efforts, research is aimed at (a) developing an integrated and scalable information sharing, monitoring, and analysis environment across jurisdictions and species for major infectious diseases, (b) developing novel data analysis, surveillance, and visualization techniques to meet the critical needs of IDI, and (c) gaining a systematic understanding of related policy, user evaluation, and technology adoption issues.

The intended intellectual contributions are threefold: (1) developing and evaluating system performance and scalability models and related algorithms needed for the efficient operation of large-scale realtime information query and monitoring/surveillance systems such as the NIDII, (2) developing and evaluating a set of novel spatio-temporal data analysis and online surveillance techniques which can be used in both IDI and other applications needing similar capabilities (e.g., crime analysis), and (3) developing a comprehensive user evaluation and technology adoption framework and conducting a detailed user evaluation and organizational impact study of the developed IDI system and related technologies.

The proposed work will have the following major broader impacts: (a) The research team will develop a working infectious disease information system across jurisdictions and disease types, providing an integrated data sharing, access, analysis, visualization, and surveillance environment for researchers, public health officials, and law enforcement and national security officials who need to assess risk of and respond to biological terror attacks. (b) The work will bring together previously disparate research and practitioner communities to conduct IDI research of significant practical relevance. In addition, it will foster cross-fertilization between law enforce and national security research and IDI.

The proposed Second Symposium on Intelligence and Security Informatics (ISI-2004) aims to provide an intellectual forum for discussion among usually disparate communities: academic researchers in information technologies, computer science, public policy, and social sciences; local, state, and federal law enforcement and intelligence experts; and information technology industry consultants and practitioners. The speakers and attendees, including noted informatics, computer science, and policy researchers as well as progressive leaders in law enforcement and security communities will engage in productive dialogue and explore avenues of collaboration. The organizers of the meeting will solicit high-quality research papers of relevance to intelligence and security research, which will be evaluated by appropriate researchers and practitioners for presentation as well as publication. Active intelligence and security informatics research can and will improve knowledge discovery and dissemination, and enhance information sharing and collaboration across law enforcement communities; the Second ISI Symposium supports that outcome.

Economics (82)

Economics is a critical component of the undergraduate curriculum, and the integration of experiments into economics courses has proven beneficial in helping students to learn microeconomics principles. Such experiments enable undergraduates to reflect on their responses to economic incentives and on the role of institutional arrangements, thus gaining a deeper understanding of economic models than they have acquired using less-interactive learning environments. However, many institutions lack the resources to develop their own dedicated experimental economics facilities. Building on work to develop EconPort, an economics digital library, this project is undertaking a national effort to disseminate experiments to hundreds of instructors from a diverse set of two- and four-year colleges around the country. Instructors learn about the experiments, and how to integrate them into their courses, at workshops that are held primarily in conjunction with economics conferences around the country. Formative project evaluation is informing the development and presentation of the workshop materials; summative evaluation addresses the efficacy of the workshops and how the use of economics experiments shapes successful teaching strategies.

The science of Intelligence and Security Informatics (ISI) focuses on the development and use of advanced information technologies, including methodologies, models and algorithms, infrastructure, systems, and tools for national/international and homeland security related applications through an integrated technological, organizational, and policy-based approach. ISI also encompasses the areas of terrorism research, biosurveillance, and intelligence analysis as well as security-related public policy. The ISI conferences have been instituted to provide an intellectual forum for discussion among disparate and often separated communities: academic researchers in information technologies, computer science, public policy, and the social sciences; local, state, and federal law enforcement and intelligence experts; epidemiologists and other public health community members; and information technology industry consultants and practitioners.

This grant will support the 2006 International Conference on Intelligence and Security Informatics (ISI-2006) May 23-24, 2006, in order to bring together noted informatics, computer science, and policy researchers as well as members of the public health, law enforcement and security communities to engage in dialogue and explore potential avenues of collaboration. ISI-2006 will be co-located with the 7th Annual National Conference on Digital Government Research and will be cosponsored by the US intelligence agencies and Dept. of Homeland Security. This should further broaden the possibilities for participation in this still-emerging scientific discipline. Additional events and meetings may be held both before and after the conference to facilitate planning and community dialogue. The meeting will solicit high-quality research papers of relevance to intelligence and security research, which will be peer reviewed by both researchers and practitioners for presentation as well as publication. The expectation is that active intelligence and security informatics research will improve knowledge discovery and dissemination, and enhance information sharing and collaboration across law enforcement communities.

This award will support the first US-China International Workshop on Digital Government Research and Practice (IntDG 2006), October 12-13, 2006, in Beijing, China. Digital government research is rapidly maturing in the U.S. Various digital government projects at all levels of the public sector are also being actively pursued in a wide range of domains with important intellectual progress and practical lessons learned. However, digital government research has been typically confined within the context of a single country, resulting in alack of comparative and transnational understanding. In addition, there is a critical need for digital government researchers and practitioners from different countries to share their findings and lessons learned, and develop a core set of common principles and methodologies to promote the further advancement of the field and practice.

This proposed international workshop is part of the emerging effort from the U.S. digital government research community to tackle some of these challenges arising in the international context. The specific objectives of this workshop are three-fold: (a) create an intellectual forum to bring together key digital government researchers in both U.S. and China to exchange research ideas, discuss emerging and future digital government research, and explore the international dimension of digital government research; (b) foster collaboration between U.S. and Chinese digital government researchers, and promote understanding and encourage joint efforts between researchers, funding agencies, and practitioners from both countries; and (c) explore collaborative opportunities between the professional digital government societies from both countries. The specific thematic emphases of this workshop will include digital city, environment, and public health. The workshop is planned as a two-day event with presenters from both U.S. and China. The Chinese Academy of Sciences, as the host of this planned workshop, is a co-sponsor and co-organizer of the event.

The objective of this research is to identify the market formats, agent designs, and composite information service specifications that, in realistic information technology (IT) environments, best promote economic prosperity. The global economy is in the midst of large-scale transformation driven by innovations in IT and the explosive growth of the Internet. IT is reshaping markets and consumer and enterprise behavior, while at the same time business realities determine which IT innovations are viable. Little is yet known about the economic and social impacts of this transformation. Significant new research is needed on various types of IT-enhanced economic environments, including: markets with asynchronous participation; markets with automated agents; new market formats enabled by IT; and new composite information services. Automated trading agents play an increasing role in the IT-enabled markets, and their interaction with human traders demands close scrutiny.

The methods to be employed in this project include the development of new theoretical models and the testing and refinement of the models in controlled experiments with human subjects. To date, the most detailed scientific knowledge of trader behavior and market performance is confined to classic market formats and to very simple goods. This research will expand that classical knowledge, test its robustness, and open new lines of inquiry by considering a broader range of market formats (one-sided auctions, two-sided markets and new hybrids), a broader range of goods (including new composite IT service products), and a broader range of behavior (including human interaction with automated agents).

The scientific knowledge generated by the research will disseminate swiftly into the community of e-commerce practitioners, and will help provide a sounder basis for integrating IT into the world economy. The platforms for running the various market formats and automated agents will be incorporated into the National Science Digital Library, enhancing infrastructure for teaching and research. Teaching, training and learning will be promoted directly for numerous graduate students who serve as research assistants and programmers; some undergraduates will also help with the programming and hundreds will serve as laboratory subjects who become experienced in market trading and controlling market agents. Given the ethnicity of students at the campuses, and given the history of employment at the labs, a large share of the educational benefits are likely to accrue to women and members of minority groups.

This Small Business Innovation Research (SBIR) Phase I proposal aims to create an information management system to monitor infectious disease outbreaks. The goal of this SBIR project is to build upon the ongoing BioPortal effort to develop an integrated infrastructure for infectious disease information collection, sharing, analysis, and visualization and to demonstrate its feasibility in real-world public health management settings. Deliverables include a scalable and flexible messaging module to facilitate real-world public health data collection and reporting, novel spatio-temporal data analysis techniques with visualization, an integrated, Web-based, one-stop information sharing and analysis environment, and a user study to assess commercial feasibility and technology adoption.

The proposed work is expected to deliver a viable system architecture design and advanced data analysis functions to be part of the next-generation public health information infrastructure. The proposed informatics infrastructure will have a wide range of potential users including state and county epidemiologists, general public health workers, researchers and policy makers, physicians, triage nurses, livestock veterinaries, domestic animal veterinaries, plant disease researchers and practitioners, and law enforcement agencies monitoring and responding to biosecurity events, among others. We also plan to expand into other market segments including the private sector.

This award will support a US-China collaborative workshop to exchange information and develop a research agenda for syndromic surveillance (defined below) within the larger context of infectious disease informatics. The workshop will take place in late 1997 in Beijing China, with attendees consisting equally of US and Chinese researchers and health practitioners, including government and academic experts. A workshop in this topic is appropriate because of increasing concern over the deadly and costly threats of infectious diseases caused by natural disasters or bioterrorism attacks. New methodologies are needed for identifying and tracking emerging infectious diseases and epidemic outbreaks. While traditional disease surveillance often relies on time-consuming laboratory diagnosis and the reporting of notifiable diseases is often slow and incomplete, a new breed of public health surveillance systems has the potential to significantly speed up detection of disease outbreaks. These new, computer-based surveillance systems offer valuable and timely information to hospitals as well as to state, local, and federal health officials. They are capable of real-time or near real-time detection of serious illnesses and potential bioterrorism agent exposures, allowing for a rapid public health response. This public health surveillance approach is generally called syndromic surveillance, which is defined as "an ongoing, systematic collection, analysis, and interpretation of 'syndrome'-specific data for early detection of public health aberrations." The rationale behind syndromic surveillance lies in the fact that specific diseases of interest can be monitored by syndromic presentations that can be shown in a timely manner such as nurse calls, medication purchases, and school or work absenteeism. In addition to early detection and reporting of monitored diseases, syndromic surveillance also provides a rich data repository and highly active communication system for situation awareness and event characterization. Multiple participants provide interconnectivity among disparate and geographically separated sources of information to facilitate a clear understanding of the evolving situation. Researchers from a wide range of backgrounds will participate, including but not limited to epidemiology, statistics, applied mathematics, information systems, computer science and machine learning/data mining. Approximately 25 individuals will participate.

This public health informatics Small Grant for Exploratory Research is a small-scale, exploratory, high-risk proposal that is potentially transformative in its research collaborations between the US and China. The proposal team is building on the momentum gained from two US-China public health informatics workshops held in Beijing in March 2008. New partnerships are expected to emerge. The outcomes have the potential to transform approaches to public health informatics, not only in US and China, but potentially across the globe, in particular in exploring transnational social networks and taking advantage of the kinds of data collection and integration methodologies and technologies employed by the two countries' public health agencies. It affords the opportunity to provide new and longer-term research and educational programs between US and Chinese institutions and practitioners.

As society becomes more dependent on cyber infrastructure, the security of networks and information technologies has become a growing concern. Individuals, businesses, and governmental organizations are now common victims of cyber-attacks that seek to steal private data, gain remote control over remote systems, and cause harm to networks and systems through other malicious means. Additionally, critical infrastructures such as smart power grids and communication networks are facing an increasing number of cyber-based threats. As a result, many researchers and security practitioners have begun to investigate cyber attacker communities in order to learn more about cyber attacker behaviors, emerging threats, and the cybercriminal supply chain. Unfortunately, there is a lack of established science for cyber security research. The lack of literature is problematic for researchers wanting to learn more so that they may contribute to and advance the current state of cyber security research. For example, many cyber attacker communities take careful measures to hide themselves by employing anti-crawling measures. This would be a challenge for many researchers and security practitioners. Furthermore, some may find cyber attacker community discussion difficult to interpret due to cyber attacker jargon, advanced security concepts, or foreign contents belonging to cyber attacker groups spanning across different countries or regions.

For these reasons, research studying hacker communities is greatly needed, as well as research that advances others? capacity to understand and investigate contents from such communities. Specifically, the development of automated tools and analyses increases the potential for more cyber security research. Web mining and machine learning technologies can be used in tandem with social science methodologies to help answer many questions related to hacker behaviors and culture, illegal markets and covert networks, cybercriminal supply chain, malware analysis, emerging security threats, and other matters. There are many opportunities for extending current cyber security research by combining hacker community data with social science methodologies, computational techniques, and security analysis.

In this research, important questions about hacker behaviors, markets, community structure, community contents, artifacts, and cultural differences are explored. Automated techniques to collect and analyze data from forums, Internet Relay Chat, and honeypots will be developed. The development of such tools will help further proactive approaches for preventing cyber-based threats, rather than taking the traditional approach of reacting when something "bad" happens. Better understanding of hacker communities across multiple geopolitical regions will support a better understanding of cybercriminal behavior, and improved and safer practices for security researchers and practitioners.

The proposed integrated computational framework and the resulting algorithms and software will also allow social science researchers and security practitioners to closely examine how cyber attacker groups form, develop, and spread their ideas; identify important and influential cyber criminals in the online world; and develop the means to recognize online hacker identities through their communication and interaction styles. Knowing more about cyber criminals, hackers, and their illegal black markets can help policy makers and security professionals make better decisions about how to prevent or respond to attacks.

The proposed work also contributes to the educational and professional development of the student research associates who contribute to it. They will learn sound research methods, and how to write about and present their work for scientific and other professional audiences.

DESCRIPTION (provided by applicant): E-cigarettes are being widely viewed as a disruptive technology with the potential to reshape the tobacco industry and perhaps even pharmaceutical companies that market nicotine replacement products. E-cigarette vendors, consumers, and other related stakeholders have been engaged in voluminous discussions in social media, which has become a critical source for understanding e- cigarette use behavior, health effects, and marketing practice. Yet, research in the intersection of e- cigarettes and social media analytics is almost non-existent, let alone automated systems that could potentially significantly improve the e-cigarette researchers and regulatory bodies' information gathering and analysis capabilities to facilitate evidence-based scientific inquiries and policy-making. This proposed interdisciplinary e-cigarette research is primarily motivated to provide social media data- driven scientific findings and technology-driven informatics tools to address the FDA CTP research priorities concerning understanding of reasons for e-cigarette use, e-cigarettes' health effects and efficacy as a smoking reduction and cessation aid, and vendors' marketing practice and related stakeholders' response. The specific aims of the proposed efforts are as follows. Aim 1 is focused on developing a dataset covering a significant portion of e-cigarette-related discussions in the English-based social media, as well as related social networking activities. Aim 2 is concerned with identifying e-cigarette consumers from the developed data collection, extracting reasons for e-cigarette use among social media users, and understanding e-cigarettes' health effects and efficacy for smoking reduction and cessation. Aim 3 focuses on understanding e-cigarette marketing in social media and corresponding responses of the related stakeholders. Aim 4 is concerned with the development of an integrated informatics platform for social media-based e-cigarette research. The proposed work aims to implement a social media analytics plan that can increase our knowledge of e-cigarette use reasons, health effects, efficacy for smoking reduction and cessation, marketing practice, related stakeholders' response in the U.S. Our data could deliver significant benefit to regulatory agencies like the FDA so that they can develop a better understanding of marketing and media that could come under their regulatory review. From the point of view of data sources, our studies will tap into th wealth of social media for analytical and regulatory purposes. We will also develop novel methods and tools to enable automatic analysis of large-scale social media datasets relevant to e-cigarettes. The proposed empirical studies using these tools are expected to generate fresh insights that complement existing research, much of which relies on survey data and anecdotes only. An integrated Web-based social media informatics system, along with a live data collection dedicated to e-cigarette research, will provide much-needed information and situational awareness support to benefit CTP missions and regulatory work.

An adverse drug reaction (ADR) is any undesired response to a medication. ADRs have been linked with significant morbidity and mortality, accounting for as much as 5% of hospital admissions. The problem stems from the fact that the ADR profile of a given drug is rarely complete at the time of official approval. The typically limited pre-approval evaluation often results in the possibility that when the drug is finally approved for use in the general population (with significant diversity in race, gender, age, lifestyle), some previously unidentified ADRs are often observed. For psychotropic medications, the problem becomes compounded by the fact that most people with psychiatric diseases tend to have other health issues, with the individual taking multiple medications (both psychotropic and non-psychotropic) at the same time, with often unknown interactions between them. Given the huge quantities of data on drugs, drug interactions, and diseases, and the possibility offered by social media sources in obtaining more information about particular drugs and their side effects, the problem of post-marketing drug surveillance could be turned into a computational problem. This work will have relevance to government agencies charged with drug approval and disease monitoring (e.g., the Food and Drug Administration (FDA), Centers for Disease Control (CDC), public health agencies), pharmaceutical companies, and the general public. The proposed work will have impact beyond drug surveillance as the methods can be applied to other scenarios such as financial markets, national security, or other healthcare problems. Graduate and undergraduates students will be involved in the project, thereby gaining experience in doing research. Journal papers and conference presentations will be used to disseminate research results.

The project takes a new approach to the problem of adverse drug event surveillance by relying heavily on the collective intelligence of the web community, with significant emphasis on social media and online sources. This calls for more serious attention to the ubiquity, veracity and diversity of data from these sources. Thus the general goal is to develop the CRUFS (credibility, recency, uniqueness, frequency and salience) framework as a uniform and innovative foundation for assessing different data channels in social media analysis of adverse drug events. The project will study methods to extract reliable signals from unreliable, noisy, redundant, and potentially deceptive online data, a core challenge in social media analytics. The project also proposes novel methods for ADR signal detection and signal fusion based on causality networks. The results will change the current passive surveillance that relies on voluntary reports, by making the public an integral part of a proactive drug surveillance system.