Ruth E. Duerr

Data Citation and Peer Review

A scientific publication is fundamentally an argument consisting of a set of ideas and expectations supported by observations and calculations that serve as evidence of its veracity. An argument without evidence is only a set of assertions. Consider the difference between the statement “The hairy woodpecker population is declining in the northwest region of the United States” and the statement “Hairy woodpecker populations in the northwest region of the United States have declined by 11% between 1992 and 2003, according to data from the Institute for Bird Populations (http://www.birdpop.org/).” Both or neither of these statements could be true, but only the second one can be verified. Scientific papers do, of course, present specific data points as evidence for their arguments, but how well do papers guide readers to the body of those data, where the the datas integrity can be further examined? In practice, a chasm may lie across the path of a reviewer seeking the source data of a scientific argument.

Representing scientific data sets in KML: Methods and challenges

Virtual Globes such as Google Earth and NASA World Wind permit users to explore rich imagery and the topography of the Earth. While other online services such as map servers provide ways to view, query, and download geographic information, the public has become captivated with the ability to view the Earths features virtually. The National Snow and Ice Data Center began to display scientific data on Virtual Globes in 2006. The work continues to evolve with the production of high-quality Keyhole Markup Language (KML) representations of scientific data and an assortment of technical experiments. KML files are interoperable with many Virtual Globe or mapping software packages. This paper discusses the science benefits of Virtual Globes, summarizes KML creation methods, and introduces a guide for selecting tools and methods for authoring KML for use with scientific data sets.

Formalizing the semantics of sea ice

We have initiated a project aimed at enhancing interdisciplinary understanding and usability of polar data by diverse communities. We have produced computer- and human-understandable models of sea ice that can be used to support the interoperability of a wide range of sea ice data. This has the potential to improve scientific predictive analyses and increase usage of the data by scientists, modelers, and forecasters as well as residents of communities that rely on sea ice. We have developed a family of ontologies, leveraging existing best in class models, including one module describing physical characteristics of sea ice, another describing sea ice charts, and a third modeling “egg codes” - an internationally accepted standard for symbolically representing sea ice within geographic regions. We used a semantic Web methodology to rapidly gather and refine requirements, design and iterate over the ontologies, and to evaluate the ontologies with respect to the use cases. We gathered requirements from a wide range of potential stakeholders reflecting the interests of operational ice centers, ice researchers, and indigenous people. We introduce the driving use case and provide an overview of the resulting open source ontologies. We also introduce some key technical considerations including the prominent role of provenance, terms of use, and credit in the model. We describe how the ontologies are being employed and highlight their compatibility with a wide range of existing standards previously developed by many of the stakeholder communities.

Advances in spatial data infrastructure, acquisition, analysis, archiving & dissemination

The authors review recent contributions to the state-of-thescience and benign proliferation of satellite remote sensing, spatial data infrastructure, near-real-time data acquisition, analysis on high performance computing platforms, sapient archiving, multi-modal dissemination and utilization for a wide array of scientific applications. The authors also address advances in Geoinformatics and its growing ubiquity, as evidenced by its inclusion as a focus area within the American Geophysical Union (AGU), European Geosciences Union (EGU), as well as by the evolution of the IEEE Geoscience and Remote Sensing Societys (GRSS) Data Archiving and Distribution Technical Committee (DAD TC).

Preservation of data for Earth system science - Towards a content standard

Various remote sensing agencies of the world have created a data rich environment for research and applications over the last three decades. Especially over the last decade, the volume and variety of data useful for Earth system science have increased quite rapidly. One of the key purposes of collecting these data and generating useful digital products containing derived geophysical parameters is to study the long-term trends in the Earths behavior. Long-term observational data and derived products are essential for validating results from models that predict the future behavior of the Earth system. Given the significant resources expended in gathering the observational data and developing the derived products, it is important to preserve them for the benefit of future generations of users. Preservation involves maintaining the bits with no loss (or loss within scientifically acceptable bounds) as they move across systems as well as over time, ensuring readability over time, and providing for long-term understandability and repeatability of previously obtained results. In order to ensure long-term understandability and repeatability, it is necessary to identify all items of content that must be preserved and plan for such preservation. This paper discusses the need for a standard enumerating and describing such content items and reports on the progress made by NASA and the Federation of Earth Science Information Partners (ESIP Federation) in the U.S. towards such a standard.

Ensuring Long-Term Access to Remotely Sensed Data With Layout Maps

The Hierarchical Data Format (HDF) has been a data format standard in National Aeronautic and Space Administration (NASA)s Earth Observing System Data and Information System since the 1990s. Its rich structure, platform independence, full-featured application programming interface (API), and internal compression make it very useful for archiving science data and utilizing them with a rich set of software tools. However, a key drawback for long-term archiving is the complex internal byte layout of HDF files, requiring one to use the API to access HDF data. This makes the long-term readability of HDF data for a given version dependent on long-term allocation of resources to support that version. Much of the data from NASAs Earth Observing System have been archived in HDF Version 4 (HDF4) format. To address the long-term archival issues for these data, a collaborative study between The HDF Group and NASAs Earth Science Data Centers (ESDCs) is underway. One of the first activities was an assessment of the range of HDF4-formatted data held by NASA to determine the capabilities inherent in the HDF format that were used in practice and for use in estimating the effort for full implementation across NASAs ESDCs. Based on the results of this assessment, methods for producing a map of the layout of the HDF4 files held by NASA were prototyped using a markup-language-based HDF tool. The resulting maps allow a separate program to read the file without recourse to the HDF API. To verify this, two independent tools based solely on the map files were developed and tested.

A New Approach to Preservation Metadata for Scientific Data: A Real World Example

The Open Archival Information System (OAIS) Reference Model was developed by the Consultative Committee for Space Data Systems (CCSDS) in the late 1990s and was adopted as an ISO standard in 2003 (ISO14721:2003) [1]. Recently, many data centers and archives around the world have started to adopt this protocol. As a notable example, the National Oceanographic and Atmospheric Administration (NOAA) of the United States of America adopted the model for their Comprehensive Large Array-data Stewardship System (CLASS). CLASS is expected to be the primary repository and access portal for NOAAs Earth science, satellite-remote-sensing data [2]. Because of the huge scale of these efforts, it is important to carefully consider the manner in which the OAIS Reference Model is implemented. The specifics of the implementation could impact the preservation and therefore the use and usability of vast quantities of remote sensing data for many years.

Optimizing apache nutch for domain specific crawling at large scale

Focused crawls are key to acquiring data at large scale in order to implement systems like domain search engines and knowledge databases. Focused crawls introduce non trivial problems to the already difficult problem of web scale crawling; To address some of these issues, BCube - a building block of the National Science Foundations EarthCube program - has developed a tailored version of Apache Nutch for data and web services discovery at scale. We describe how we started with a vanilla version of Apache Nutch and how we optimized and scaled it to reach gigabytes of discovered links and almost half a billion documents of interest crawled so far.

Towards a Standard Archival Format for Earth Science Data: Storing NASA ECS Data using HDF5 Archival Information Packages (AIP)

Lack of standard metadata and file formats make it challenging to archive and distribute remote sensing data. Although the Common Data Model (CDM) developed by Unidata has the potential of providing easy access to data stored in a variety of file formats, it would still be necessary to maintain each I/O library ever used to create a data product. Moreover, due to the nature of these data structures, I/O libraries are often complicated and expensive to maintain. As a consequence, the long-term archival of data stored in multiple formats becomes an expensive and challenging task. In this paper, we demonstrate an alternative solution, namely migration of data to a single standards-based archive format. Data from NASAs Earth Observing System (EOS) Data Centers formatted in Hierarchical Data Format (HDF) are used in the demonstration.

Establishing Trustworthy Repositories of Scientific Data: Opportunities and Benefits

Scientific progress often depends on the ability of the scientific community to build on the works of others. Such works include scientific data, published reports of findings, and other researchrelated information and artifacts that are produced as part of the scientific process. Providing capabilities for accessing and using such scientific works enables the reproducibility of published methods and results to identify opportunities for improvement. Access and use of science products also enables others to build on previous work. In an increasingly digital world, the science community accesses and uses relevant scientific resources that have been obtained from digital repositories, data centers, and archives, as well as from traditional sources such as publishers of journal articles. Digital repositories need to establish capabilities, which provide access to and enable the use of digital resources. These resources are needed by the science community to improve and build on the efforts of others. Digital repositories that provide free and unrestricted access to scientific data and research-related information can reduce the barriers to science. By reducing these barriers they will be able to offer opportunities for members of the scientific community to pursue research questions and challenges that were previously unapproachable. These may include opportunities for researchers to gather data from other domains and support interdisciplinary research. Opportunities to use the data products and services offered by digital repositories also can contribute to the development of the scientific community and to the emergence of new areas of study. Being able to access scientific data and other research resources supports future science and is important to the research community. Given their role as stewards, digital repositories must be considered by this community to be trustworthy. With limited resources available in many science domains, the scientific community as a whole cannot afford to lose science data and related resources. Digital resources may be particularly vulnerable to loss. Improving the infrastructure and practices for managing scientific data can reduce the potential for such losses. Trustworthy facilities are needed to curate, disseminate, and maintain these data and research-related materials. Furthermore, trustworthy repositories are needed to develop and improve data management services. They should also foster improvements in the capabilities and practices for scientific data stewardship. Establishing digital repositories as trustworthy stewards of scientific data and related research products and services offers potential opportunities and benefits for science and society that can be leveraged to further research, educational, or decision making objectives. The direct beneficiaries of science data repositories include the individuals who serve as producers, stewards, and users of science data as well as the organizations that fund and host the digital repositories. Other potential beneficiaries include those who are not community stakeholders, currently, but may have an interest in these resources in the future. Furthermore, as described below, society at large also could benefit from digital repositories that have been recognized as trustworthy stewards of scientific data. Data producers include scientists and other members of science project teams. Such data producers can compare digital repositories to determine those that are trustworthy, thereby enabling consumption of their data by interested researchers. If there is a variety of trustworthy repositories for their data, data producers can be selective and choose the repository that will best serve the community of potential users that the data producers are targeting for the use of their data products and services. Furthermore, selectivity among data producers for their choice repository could lead to competition among repositories that serve a particular science discipline, which may in turn lead to increased specialization of repositories to provide unique services. Science data stewards include professionals in data management, information systems, and data services. These stewards can iPres 2015 conference proceedings will be made available under a Creative Commons license. With the exception of any logos, emblems, trademarks or other nominated third-party images/text, this work is available for reuse under a Creative Commons Attribution 3.0 unported license. Authorship of this work must be attributed. View a copy of this licence. compare choices among employment opportunities where they will apply their knowledge and skills, while also contributing to the curation, preservation, and dissemination of scientific data products and services. Tools should be available to enable data stewards to prepare, process, and preserve data for the future. These tools should also enable the dissemination of data products and services to diverse communities of users. Data stewards who accept positions at trustworthy science data repositories can enjoy the opportunities for professional development. These opportunities may be more abundant for individuals working within organizations that have been designated as trustworthy providers of scientific resources. Trustworthy digital repositories of science data and their staff should be able to demonstrate sustainable capabilities for managing data curation operations, for diligently preserving and disseminating science data, and for ensuring the integrity of their systems. Users of science data products and services include researchers of all types, decision-makers, learners, and members of the general public. With improvements in the quality of products and services available from trustworthy digital repositories, these users can patronize trustworthy digital repositories that offer resources relevant to their goals and interests. Trustworthy repositories may recognize the potential for expanding their user base by supporting various levels of expertise, particularly in the science domain represented by the data that they archive and disseminate. As such, the availability of data products and services curated by trustworthy repositories for current and future users will enable use by increasingly diverse populations. Benefactors of trustworthy digital repositories of science data will be able to observe and demonstrate how their support of trustworthy resources that have been prepared and disseminated, contributes to the future of science and the overall benefit of humanity. Funders that support the development and operation of trustworthy digital repositories could include government agencies, foundations, and philanthropists. The costs incurred enable the stewardship and dissemination of science data products and services. Perhaps, with such evidence of the value of their contributions, funders will be able to provide trustworthy digital repositories with the support needed to sustain science data stewardship operations and to help prepare science data repositories with the capabilities necessary to meet future challenges for the curation and dissemination of science data. Organizations that host trustworthy digital repositories often include domain-specific data centers, archives, and institutional repositories. Upon attaining the status of trustworthy digital repositories, these organizations are likely to recruit the most qualified members of the science community based on their reputation for providing reliable data products and services. As more organizations become trustworthy digital repositories of science data, we also can expect the requirements of being trustworthy to increase. Just as other standards improve as technology evolves and new needs are recognized, the demands for increasing the requirements for trustworthy digital repositories, especially those that are responsible for science data, also should become more rigorous. This will ensure that science data and other research materials in digital form are being managed effectively for future use. Members of society who are not traditional users of science data or other scientific resources also can benefit from the emergence of trustworthy science data repositories. Open science data that are accessible from trustworthy digital repositories will offer societal benefits as the data are used and translated into knowledge that contributes to the well-being of society at large. For example, educational institutions will be able to leverage the data and other research materials available to improve opportunities for educators and their students to learn from such resources. In addition, the benefits of trustworthy digital repositories for science can be realized by society as scientific breakthroughs, made possible by the continuing availability of science data products and services, thereby contributing to the lives of current and future generations as data are used to inform decision-making. These are just a few of the opportunities and benefits that we can expect and hope for as digital repositories for science data attain the designation of being trustworthy. Taken together, the opportunities and benefits that can emerge from the availability of trustworthy digital repositories for science data can increase the maturity of the infrastructure and capabilities for managing, curating, disseminating, and preserving the digital data that exist today as well as those that will be produced in the future. Likewise, the availability of trustworthy science data repositories also has the potential to increase the professionalism of scientific data management practices, reducing the potential for the science data that have been created in digital form to be lost, through technological obsolescence, mismanagement, insufficient context for use, lapses in security, or other potential difficulties that could occur. Progress in the infrastructure for