Robert S. Chen

Natural disaster hotspots: case studies

These case studies complement the earlier groundbreaking work of Natural Disaster Hotspots: A Global Risk Analysis published in April 2005. Three case studies address specific hazards: landslides, storm surges and drought. An additional, three case studies address regional multi-hazard situations in Sri Lanka, the Tana River basin in Kenya, and the city of Caracas, Venezuela.

Cooperative design, development, and management of interdisciplinary data to support the global environmental change research community.

Abstract This article describes the organizational, collaborative, and project management processes of a scientific data center that serves the interdisciplinary global environmental change research community. Collaborating with representatives of the user community, the data center identifies, acquires, ingests, manages, and disseminates research-related information (RRI), such as scientific data and documents. Users and software developers cooperatively design online applications that integrate these resources into a wide variety of information products and services to be disseminated through a digital library to the globally dispersed community. Results from these participatory design and cooperative development activities include Web-based resource catalogs, training, peer education, help desk, and reference services to support scientific communication and decision-making among members of the interdisciplinary community.

Global Infrastructure: The Potential of SRTM Data to Break New Ground

This paper evolved out of a Global Infrastructure Mapping workshop organized by CIESIN of the Columbia Earth Institute and by NASA/JPL of the California Institute of Technology, held at Columbia University, New York, on 4-5 October 2000. The research by the Jet Propulsion Laboratory, California Institute of Technology, was carried out under a contract with the National Aeronautics and Space Administration. Partial funding for the workshop was provided by the NASA Socioeconomic Data and Applications Center (SEDAC) under contract NAS598162 to Columbia University.

Towards Sustainable Stewardship of Digital Collections of Scientific Data

The digital revolution has vastly increased the ability of the scientific community to collect and store a tremendous variety and quantity of data in digital form, representing a potentially irreplaceable legacy that can support scientific discovery and scholarship in both the present and the future. However, it is not yet clear what organizations or institutions can and should maintain and store such data, ensuring their long-term integrity and usability, nor how such longterm stewardship should be funded and supported. Many traditional information preservation and access institutions such as libraries and museums are struggling to develop the skills, resources, and infrastructure needed for largescale, long-term digital data stewardship. Government agencies often have strong technical capabilities, but are subject to political and budgetary pressures and competing priorities. Private organizations and companies can bring to bear innovations not only in technology but also in economic approaches that could provide financial sustainability. Developing long-term collaborative partnerships between different types of organizations may be one approach to developing sustainable models for long-term data stewardship. The development of objective criteria and open standards for trusted digital data repositories is another important step towards sustainable data stewardship. A critical challenge is the development of viable economic models for ensuring that the resources needed for long-term stewardship are put in place, while at the same time addressing the needs of the scientific community and society more generally for open access to scientific data and information resources. The development of a robust spatial data infrastructure can not only help reduce both the shortand long-term costs of data stewardship, but also provide a framework for the establishment and evolution of trustworthy data repositories that will be available for future generations of users to discover, access, and use the scientific heritage that is being created today.

Curation of Scientific Data at Risk of Loss: Data Rescue and Dissemination

Data rescue offers an opportunity for digital repositories, including institutional repositories, data archives, and scientific data centers, to provide access to potentially valuable scientific data that is at risk of being lost. Rescue may be valuable not only to restore access to data of past scientific interest, such as environmental observations or social surveys, but also to recover historic information about the state of knowledge and science at the time the data was collected or assembled. Scientific data may need to be rescued at any stage along the data life cycle, and the extent of data curation that was completed prior to a data rescue effort may vary, depending on the circumstances that led to the need for data rescue. The level of effort required to complete a data rescue depends largely on the condition of the data being rescued, the availability and quality of data documentation and provenance information, and the accessibility of the data producers. In extreme cases, data organization and documentation are poor, and those knowledgeable about how the data was collected or developed are no longer available. In some cases, collections of data sets may need to be rescued from an existing archive that is no longer sustainable. In short, scientific data may be at risk of loss for a variety of reasons, and a data rescue effort can present new challenges for data curation and dissemination operations.

Independent Evaluation of a Scientific Data Center for Compliance with the ISO 16363 Requirements for Audit and Certification of Trustworthy Digital Repositories

This work is licensed under a Creative Commons Attribution 3.0 Unported License. Objectives: Scientific data centers and other digital repositories need to continuously improve so that they can meet the challenge of providing stewardship for the scientific data that are used by scientists, policy-makers, educators and their students, and the general public. As part of its efforts to continuously improve its capabilities and services offered to communities that are interested in using scientific data on human interactions in the environment, SEDAC, the NASA Socioeconomic Data and Applications Center, requested an independent test audit to evaluate its compliance with the draft requirements of ISO 16363:2012, the international standard for Audit and Certification of Trustworthy Digital Repositories. SEDAC has conducted various audits through the years as part of its self-improvement efforts. However, obtaining an independent test audit for compliance with the draft metrics in ISO 16363 offers an opportunity to identify ways in which the scientific data center could improve its organization and management, its processes for managing and disseminating data, and its systems and security infrastructure. Similarly, when organizations and auditors are authorized to offer certification of trustworthy digital repositories, SEDAC will be better prepared to apply for certification as a result of having been previously audited by independent evaluators for compliance with the draft ISO 16363 metrics.

Bridging Disciplines: Assessing the Interdisciplinary Impact of Open Data

Freely disseminating scientific data can contribute to multiple disciplines across the physical, social, health, and engineering sciences. If the impact of data centers is not measured, stakeholders will not know whether data centers, archives, and libraries, and the data that they disseminate, are having a positive impact on the conduct of science. Data citations provide evidence on the use of data in various stages of the research process, including problem definition, statistical analysis, modeling, and validation. Measuring the interdisciplinary citation of scientific data disseminated by a data center can reveal the degree to which the data center is supporting cross-disciplinary research. Analysis of a decade of data citations demonstrates the interdisciplinary use of scientific data and the impact that one data center has had across disciplinary boundaries.

Comparing Approaches for the Sustainability of Scientific Data Repositories

2013 Columbia University Research Data Symposium February 27, 2013, New York, NY Sustainable data systems are critical components of the cyberinfrastructure needed to provide long-term stewardship of scientific data, including Earth science data, throughout their entire life cycle. A variety of approaches may help ensure the sustainability of such systems, but these approaches must be able to survive the demands of competing priorities and decreasing budgets over long time periods. Analyzing and comparing various approaches can identify viable aspects of each approach and inform decisions for developing, managing, and supporting the cyberinfrastructure needed to facilitate discovery, access, and analysis of data by future communities of users. A typology of sustainability approaches is proposed, and example use cases are offered for assessing the approaches over time. These examples help illustrate the potential strengths and weaknesses of each approach under various conditions and with regard to different objectives, e.g., open vs. limited access. By applying the results of these analyses to their particular circumstances, systems stakeholders can assess their options for a sustainable systems approach, which may incorporate multiple sustainability options, along with other metrics to ensure the sustainability of the scientific data and information for which they are responsible. In addition, clarifying and comparing sustainability approaches should inform the design of new systems and the improvement of existing systems to meet the needs for long-term stewardship of scientific data, and support education and workforce development efforts needed to ensure that the appropriate scientific and technical skills are available to operate and further develop sustainable cyberinfrastructure.

Analyzing Data Citations to Assess the Scientific and Societal Value of Scientific Data

0 10 20 30 40 50 60 70 80 90 100 Agriculture, Multidisciplinary Agronomy Biodiversity Conservation Biology Cardiac & Cardiovascular Systems Chemistry, Applied Computer Science, Artificial Intelligence Computer Science, Interdisciplinary Applications Ecology Economics Energy & Fuels Engineering, Environmental Entomology Environmental Sciences Environmental Studies Evolutionary Biology Forestry Geography, Physical Geosciences, Multidisciplinary Health Care Sciences & Services Infectious Diseases Marine & Freshwater Biology Mathematical & Computational Biology Medical Informatics Medicine, Research & Experimental Meteorology & Atmospheric Sciences Multidisciplinary Sciences Operations Research & Management Science Parasitology Planning & Development Plant Sciences Public, Environmental & Occupational Health Social Sciences, Mathematical Methods Soil Science Statistics & Probability Tropical Medicine Veterinary Sciences Zoology Disciplines of Secondary Citations of Selected Articles Citing SEDAC Data