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1. Life-Cycle Decisions for Biomedical Data: The Challenge of Forecasting Costs

   National Academies of Sciences, Engineering (January 2020, Publications listing National Academy of Sciences National Academy of Engineering Institute of Medicine National Research Council)

   null (Ed.)

   Biomedical research results in the collection and storage of increasingly large and complex data sets. Preserving those data so that they are discoverable, accessible, and interpretable accelerates scientific discovery and improves health outcomes, but requires that researchers, data curators, and data archivists consider the long-term disposition of data and the costs of preserving, archiving, and promoting access to them. Life Cycle Decisions for Biomedical Data examines and assesses approaches and considerations for forecasting costs for preserving, archiving, and promoting access to biomedical research data. This report provides a comprehensive conceptual framework for cost-effective decision making that encourages data accessibility and reuse for researchers, data managers, data archivists, data scientists, and institutions that support platforms that enable biomedical research data preservation, discoverability, and use. 

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2. Unified methods in collecting, preserving, and archiving coral bleaching and restoration specimens to increase sample utility and interdisciplinary collaboration

   https://doi.org/10.7717/peerj.14176  

   Vega Thurber, Rebecca; Schmeltzer, Emily R.; Grottoli, Andréa G.; van Woesik, Robert; Toonen, Robert J.; Warner, Mark; Dobson, Kerri L.; McLachlan, Rowan H.; Barott, Katie; Barshis, Daniel J.; et al (January 2022, PeerJ)

   Coral reefs are declining worldwide primarily because of bleaching and subsequent mortality resulting from thermal stress. Currently, extensive efforts to engage in more holistic research and restoration endeavors have considerably expanded the techniques applied to examine coral samples. Despite such advances, coral bleaching and restoration studies are often conducted within a specific disciplinary focus, where specimens are collected, preserved, and archived in ways that are not always conducive to further downstream analyses by specialists in other disciplines. This approach may prevent the full utilization of unexpended specimens, leading to siloed research, duplicative efforts, unnecessary loss of additional corals to research endeavors, and overall increased costs. A recent US National Science Foundation-sponsored workshop set out to consolidate our collective knowledge across the disciplines of Omics, Physiology, and Microscopy and Imaging regarding the methods used for coral sample collection, preservation, and archiving. Here, we highlight knowledge gaps and propose some simple steps for collecting, preserving, and archiving coral-bleaching specimens that can increase the impact of individual coral bleaching and restoration studies, as well as foster additional analyses and future discoveries through collaboration. Rapid freezing of samples in liquid nitrogen or placing at −80 °C to −20 °C is optimal for most Omics and Physiology studies with a few exceptions; however, freezing samples removes the potential for many Microscopy and Imaging-based analyses due to the alteration of tissue integrity during freezing. For Microscopy and Imaging, samples are best stored in aldehydes. The use of sterile gloves and receptacles during collection supports the downstream analysis of host-associated bacterial and viral communities which are particularly germane to disease and restoration efforts. Across all disciplines, the use of aseptic techniques during collection, preservation, and archiving maximizes the research potential of coral specimens and allows for the greatest number of possible downstream analyses. 

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3. Implementing community best practice data and metadata capture into laboratory workflows using Sparrow

   Kuehn, S.C. (January 2022, EarthCube Annual Meeting 2022)

   An implementation of the Sparrow data system (https://sparrow-data.org) is currently being developed to support laboratory workflows for sample preparation, geochemical analysis, and SEM imaging in support of tephra research. Tephra, consisting of fragmental material ejected from volcanoes, has a multidisciplinary array of applications from volcanology to geochronology, archaeology, environmental change, and more. The international tephra research community has developed a comprehensive set of recommendations for data and metadata collection and reporting (https://doi.org/10.5281/zenodo.3866266) as part of a broader effort to adopt FAIR practices. Implementations of these recommendations now exist for field data via StraboSpot (https://strabospot.org/files/StraboSpotTephraHelp.pdf) and for samples, analytical methods, and geochemistry via SESAR and EarthChem (https://earthchem.org/communities/tephra/). Implementing these recommended practices in Sparrow helps to (1) cover laboratory workflows between field sample collection and project data archiving and (2) address a key researcher pain point. As re-emphasized by participants in the Tephra Fusion 2022 workshop earlier this year (Wallace et al., this meeting), the huge workload currently needed to capture and organize data and metadata in preparation for archiving in community data repositories is a major obstacle to achieving FAIR practices. By capturing this information on the fly during laboratory workflows and integrating it together in a single data system, this challenge may be overcome. We are implementing the tephra community recommendations as extensions to Sparrow’s core database schema. Data import pipelines and user interfaces to streamline metadata capture are also being developed. In the longer term, we aim to achieve interoperability with an ecosystem of tools and repositories like StraboSpot, SESAR, EarthChem, and Throughput. The results of these developments will be applicable not just to tephra but also to other research areas which utilize similar laboratory and analytical methods - e.g. sedimentology, mineralogy, and petrology. 

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4. Disaster reconnaissance framework for sustainable post-disaster materials management

   https://doi.org/10.1016/j.wasman.2023.07.010  

   Yeşiller, Nazli; Hanson, James L.; Wartman, Joseph; Turner, Benjamin; Gardiner, Andrea; Manheim, Derek C.; Choi, Juyeong (September 2023, Waste Management)

   A first foundational assessment is provided for disaster debris reconnaissance that includes identifying tools and techniques for reconnaissance activities, identifying challenges in field reconnaissance, and identifying and developing preliminary guidelines and standards based on advancements from a workshop held in 2022. In this workshop, reconnaissance activities were analyzed in twofold: in relation to post-disaster debris and waste materials and in relation to waste management infrastructure. A four-phase timeline was included to capture the full lifecycle of management activities ranging from collection to temporary storage to final management route: pre-disaster or pre-reconnaissance, post-disaster response (days/weeks), short-term recovery (weeks/months), and long-term recovery (months/years). For successful reconnaissance, objectives of field activities and data collection needs; data types and metrics; and measurement and determination methods need to be identified. A reconnaissance framework, represented using a 3x2x2x4 matrix, is proposed to incorporate data attributes (tools, challenges, guides), reconnaissance attributes (debris, infrastructure; factors, actions), and time attributes (pre-event, response, short-term, long-term). This framework supports field reconnaissance missions and protocols that are longitudinally based and focused on post-disaster waste material and infrastructure metrics that advance sustainable materials management practices. To properly frame and develop effective reconnaissance activities, actions for all data attributes (tools, challenges, guides) are proposed to integrate sustainability and resilience considerations. While existing metrics, tools, methods, standards, and protocols can be adapted for sustainable post-disaster materials management reconnaissance, development of new approaches are needed for addressing unique aspects of disaster debris management. 

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5. NSF-funded Fairness, Ethics, Accountability, and Transparency (FEAT) Workshop Report

   Howard, Ayanna; Borenstein, Jason; Gosha, Kinnis (October 2019, NSF Workshop Reports)

   Modern societies rely extensively on computing technologies. As such, there is a need to identify and develop strategies for addressing fairness, ethics, accountability, and transparency (FEAT) in computing-based research, practice, and educational efforts. To achieve this aim, a workshop, funded by the National Science Foundation, convened a working group of experts to document best practices and integrate disparate approaches to FEAT. The working group included different disciplines, demographics, and institutional types, including large research-intensive universities, Historically Black Colleges and Universities, Hispanic-Serving Institutions, teaching institutions, and liberal arts colleges. The workshop brought academics and members of industry together along with government representatives, which is vitally important given the role and impact that each sector can have on the future of computing. Relevant insights were gained by drawing on the experience of policy scholars, lawyers, statisticians, sociologists, and philosophers along with the more traditional sources of expertise in the computing realm (such as computer scientists and engineers). The working group examined best practices and sought to articulate strategies for addressing FEAT in computing-based research and education. This included identifying methodological approaches that researchers could employ to facilitate FEAT, instituting guidelines on what problem definition practices work best, and highlighting best practices for data access and data inclusion. The resulting report is the culmination of the working group activities in identifying systematic methods and effective approaches to incorporate FEAT considerations into the design and implementation of computing artifacts. 

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