Search

Despite growing recognition of the importance of public data to the modern economy and to scientific progress, long-term investment in the repositories that manage and disseminate scientific data in easily accessible-ways remains elusive. Repositories are asked to demonstrate that there is a net value of their data and services to justify continued funding or attract new funding sources. Here, representatives from a number of environmental and Earth science repositories evaluate approaches for assessing the costs and benefits of publishing scientific data in their repositories, identifying various metrics that repositories typically use to report on the impact and value of their data products and services, plus additional metrics that would be useful but are not typically measured. We rated each metric by (a) the difficulty of implementation by our specific repositories and (b) its importance for value determination. As managers of environmental data repositories, we find that some of the most easily obtainable data-use metrics (such as data downloads and page views) may be less indicative of value than metrics that relate to discoverability and broader use. Other intangible but equally important metrics (e.g., laws or regulations impacted, lives saved, new proposals generated), will require considerable additional research to describe and develop, plus resources to implement at scale. As value can only be determined from the point of view of a stakeholder, it is likely that multiple sets of metrics will be needed, tailored to specific stakeholder needs. Moreover, economically based analyses or the use of specialists in the field are expensive and can happen only as resources permit.

This paper presents the perspectives of data, informatics, and information scientists and practitioners regarding how data solutions can be developed for place-based community resilience. Data were collected from participants at an Earth Science Information Partners (ESIP) meeting in 2015. Results show that to develop such data solutions, terminology related to community resilience must be further clarified to coordinate better with data and informatics systems, and institutional support of place-based community resilience must be prioritized. In addition, accessibility and usability of developed data solutions are crucial, and gaps along the information pathway must be filled to better connect data practitioners and community resilience practitioners.

In this review, we adopt the definition that ‘Data citation is a reference to data for the purpose of credit attribution and facilitation of access to the data’ (TGDCSP 2013: CIDCR6). Furthermore, access should be enabled for both humans and machines (DCSG 2014). We use this to discuss how data citation has evolved over the last couple of decades and to highlight issues that need more research and attention. Data citation is not a new concept, but it has changed and evolved considerably since the beginning of the digital age. Basic practice is now established and slowly but increasingly being implemented. Nonetheless, critical issues remain. These issues are primarily because we try to address multiple human and computational concerns with a system originally designed in a non-digital world for more limited use cases. The community is beginning to challenge past assumptions, separate the multiple concerns (credit, access, reference, provenance, impact, etc.), and apply different approaches for different use cases.

Analog archival data can supplement modern digital research, but only if those data are preserved, described, and migrated to appropriate formats. The National Snow and Ice Data Center (NSIDC) at the University of Colorado Boulder (CU) is responsible for managing, archiving, and disseminating cryospheric and polar data. The clear majority of these data are digital, but the NSIDC also houses a collection of historical archival materials that include measurements related to the earth's glaciated regions prior to the development of modern instrumentation. Their formats, however, are not conducive to contemporary analysis, rendering them ostensibly “lost” to research. This paper describes a series of efforts to provide access to these collections that date back to their original acquisition, as long ago as the mid-nineteenth century, with focus primarily on activities over the last 15 years. The most recent effort was funded by the Council on Library & Information Resources and won the 2016 International Data Rescue Award. The intent is to highlight key challenges, and our proposed own solutions to those challenges, in designing a digitization project centered on providing online access to analog data in glaciological, geomorphological, and related research.

The Enabling FAIR Data project has brought together a broad spectrum of Earth, space, and environmental science leaders to ensure that data are findable, accessible, interoperable, and reusable.

We describe efforts to bring new methods of search analytics, machine learning, natural language processing and data visualization to address the challenge of finding and extracting meaning from unstructured text and multimedia content. We use the Polar domain to motivate the problem and our proposed solution. However, our techniques are applicable and scalable to other domains., This work was supported by the DARPA XDATA/Memex program and by the NSF EarthCube program under award ICER- 1639753. In addition, the NSF Polar Cyberinfrastructure award numbers PLR-1348450 and PLR-144562 funded a portion of the work. Effort supported in part by JPL, managed by the California Institute of Technology on behalf of NASA.

In recent years, a number of data identification technologies have been developed which purport to permanently identify digital objects. In this paper, nine technologies and systems for assigning persistent identifiers are assessed for their applicability to Earth science data (ARKs, DOIs, XRIs, Handles, LSIDs, OIDs, PURLs, URIs/URNs/URLs, and UUIDs). The evaluation used four use cases that focused on the suitability of each scheme to provide Unique Identifiers for Earth science data objects, to provide Unique Locators for the objects, to serve as Citable Locators, and to uniquely identify the scientific contents of data objects if the data were reformatted. Of all the identifier schemes assessed, the one that most closely meets all of the requirements for an Unique Identifier is the UUID scheme. Any of the URL/URI/IRI-based identifier schemes assessed could be used for Unique Locators. Since there are currently no strong market leaders to help make the choice among them, the decision must be based on secondary criteria. While most publications now allow the use of URLs in citations, so that all of the URL/URI/IRI based identification schemes discussed in this paper could potentially be used as a Citable Locator, DOIs are the identification scheme currently adopted by most commercial publishers. None of the identifier schemes assessed here even minimally address identification of scientifically identical numerical data sets under reformatting.