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Despite widespread recognition of the importance of data exchange in transboundary waters' management, there is growing evidence that data exchange is falling short in practice. A possible explanation may be that data exchange occurs where and when it is needed. Needs for data exchange in shared waters, nonetheless, have not been systematically assessed. This paper evaluates data exchange needs in a set of transboundary basins and compares such needs with evidenced levels of data exchange. Our findings indicate that it may be possible to accelerate data exchange by identifying and promoting the exchange of data that respond to palpable need and serve practical use. [ABSTRACT FROM AUTHOR]

Guyana's capacity to address the impacts of climate change on its coastal environment requires the ability to monitor, quantify and understand coastal change over short-, medium- and long- term. Understanding the drivers of change in coastal and marine environment can be achieved through the accurate measurement and critical analyses of morphologies, flows, processes and responses. This manuscript presents a strategy developed to create a central resource, database and web-based platform to integrate data and information on the drivers and the changes within Guyana coastal and marine environment. The strategy involves four complimentary work packages including data collection, development of a platform for data integration, application of the data for coastal change analyses and consultation with stakeholders. The last aims to assess the role of the integrated data systems to support strategic governance and sustainable decision-making. It is hoped that the output of this strategy would support the country's climate-focused agencies, organisations, decision-makers, and researchers in their tasks and endeavours.

Hunting and trapping of gray wolves (Canis lupus) has increased dramatically in the "lower 48" states of the United States. We assess the data used to justify the intense hunting pressure on wolves, and find an absence of accessible biological data. We find there is a clear need for more transparent reporting of livestock losses, wolf kills, and especially the numbers and types of nontarget species captured in traps set for wolves. Also lacking is a full accounting of benefits and costs of hunting wolves, with a noteworthy failure to incorporate the ecosystem functions served by wolves. As apex predators, wolves warrant multi‐objective management as opposed to management focused largely on livestock interests and concerns. [ABSTRACT FROM AUTHOR]

Abstract Hunting and trapping of gray wolves (Canis lupus) has increased dramatically in the “lower 48” states of the United States. We assess the data used to justify the intense hunting pressure on wolves, and find an absence of accessible biological data. We find there is a clear need for more transparent reporting of livestock losses, wolf kills, and especially the numbers and types of nontarget species captured in traps set for wolves. Also lacking is a full accounting of benefits and costs of hunting wolves, with a noteworthy failure to incorporate the ecosystem functions served by wolves. As apex predators, wolves warrant multi‐objective management as opposed to management focused largely on livestock interests and concerns.

Though societal acceptance of same-sex unions has grown, resulting in more inclusive government programs and policies and expanded legal protections, analysts remain uncertain about how to identify and enumerate same-sex households. Presently, the counts available of same-sex households in the United States oftentimes disagree. We show that the origins of these conflicting counts can be traced back to definitional and measurement issues in household surveys. In this study, we demonstrate how counts of same-sex households conflict, mislead, and undermine the goal of accurately representing the population of households with same-sex couples. By providing alternative approaches to counting household with same-sex couples we highlight the challenges in enumerating these households. We draw upon three federal household surveys to demonstrate the inconsistencies in the counts of same-sex households and to illustrate our methods. We argue that our proposed methods lead to more comprehensive and credible counts of households containing same-sex couples.

This paper examines the role of pipe deterioration prediction approaches for optimizing maintenance, repair, and rehabilitation of buried water supply, wastewater collection, and drainage networks. It is appreciated that there are other ancillary assets within water supply and wastewater collection and drainage networks, but these were not considered in this paper. Currently there are a range of asset condition assessment frameworks, mainly based on asset defect location, identification, and characterization. These are infrequently applied in practice, mainly due to the restricted availability of asset defect inspection data. This paper reviews current deterioration modeling approaches and highlights the crucial need for broader, richer data sets (including both asset and surrounding environment data) to inform the development and application of such approaches. This paper describes what could be considered as an expanded ideal data set for deterioration modeling at a network and individual asset scale and indicates emerging new inspection technologies that should be capable of meeting the enhanced data needs. [ABSTRACT FROM AUTHOR]

Background: This paper describes a pilot study undertaken in 2018, to determine the key data needs of each of the different Ethiopian dairy sector stakeholder groups. The study aimed to characterise the emerging trends of dairy product production, processing, retailing and consumption in Ethiopia, and to identify and characterise current and future data needs of different stakeholders. Methods: The study undertook a mapping of the interactions between different stakeholders in the dairy sector, and an interactive evaluation of the institutional data repository and access options. Focus group discussions and interviews were held in three regions of the country prior to a two-day workshop in the capital Addis Ababa. Data needs were characterised by type, availability, format, level of detail, methods of dissemination, uptake and use, and the institutional arrangement, including the different roles of public and private sectors in decision making processes. Results: The study highlighted the main data needs and identified several broader institutional issues constraining the further development of the Ethiopian dairy sector. The stakeholder groups endorsed the reactivation of a national dairy board, independent of government but closely incorporating government, and with the buy-in and membership of private sector enterprises, including producers, processers, service providers and consumers, to provide clearer facilitative leadership on the dairy industry. Conclusions: The study workshop provided a timely discussion between diverse stakeholders, including government, and several potential organisations were suggested to host and manage a national dairy database. Importantly, the reactivation of a national dairy board was strongly endorsed. It was recommended that stakeholder links be established, sector-specific data needs be elevated to higher detail, and a national roll out of herd-specific data recording schemes was called for, to allow for effective evidence-based policies and decision making.

Background: This paper describes a pilot study undertaken in 2018, to determine the key data needs of each of the different Ethiopian dairy sector stakeholder groups. The study aimed to characterise the emerging trends of dairy product production, processing, retailing and consumption in Ethiopia, and to identify and characterise current and future data needs of different stakeholders. Methods: The study undertook a mapping of the interactions between different stakeholders in the dairy sector, and an interactive evaluation of the institutional data repository and access options. Focus group discussions and interviews were held in three regions of the country prior to a two-day workshop in the capital Addis Ababa. Data needs were characterised by type, availability, format, level of detail, methods of dissemination, uptake and use, and the institutional arrangement, including the different roles of public and private sectors in decision making processes. Results: The study highlighted the main data needs and identified several broader institutional issues constraining the further development of the Ethiopian dairy sector. The stakeholder groups endorsed the reactivation of a national dairy board, independent of government but closely incorporating government, and with the buy-in and membership of private sector enterprises, including producers, processers, service providers and consumers, to provide clearer facilitative leadership on the dairy industry. Conclusions: The study workshop provided a timely discussion between diverse stakeholders, including government, and several potential organisations were suggested to host and manage a national dairy database. Importantly, the reactivation of a national dairy board was strongly endorsed. It was recommended that stakeholder links be established, sector-specific data needs be elevated to higher detail, and a national roll out of herd-specific data recording schemes was called for, to allow for effective evidence-based policies and decision making.

Misuse and overuse of antimicrobials in livestock production are identified as drivers for antimicrobial resistance (AMR). To improve decision-making concerning livestock health, it is important to understand the impact of AMR in livestock and aquaculture, within and beyond farm level, as well as expenditure on antimicrobial use (AMU). Such understanding provides grounds for systematic disease prioritisation and establishes a baseline for understanding the value of different strategies to mitigate animal health problems and for the monitoring and evaluation of the impact of those strategies. Yet limited data availability and quality surrounding AMU and AMR create barriers to furthering the knowledge of such impact. These data constraints are also more prevalent in contexts that lack the necessary resources to develop and maintain systematic and centralised data collection and collation systems. Even in regions with robust AMU and AMR monitoring systems in place, data limitations remain, such that the expenditure on antimicrobials and impacts of AMR remain unclear. Additionally, the current research funding strategies have been less focused on primary data collection, adding further barriers to filling the data void and reducing the global AMU/AMR knowledge gap. To work around the data scarcity and leverage previous and ongoing research efforts, it is vital to gain comprehensive knowledge of the people, projects and research consortia dedicated to the topic of AMU/AMR.

To develop smart services to successfully operate as a component of smart service systems (SSS), they need qualitatively and quantitatively sufficient data. This is especially true when using statistical methods from the field of artificial intelligence (AI): training data quality directly determines the quality of resulting AI models. However, AI model quality is only known when AI training can take place. Additionally, the creation of not yet available data sources (e.g., sensors) takes time. Therefore, systematic specification is needed alongside SSS development. Today, there is a lack of systematic support for specifying data relevant to smart services. This gap can be closed by realizing the systematic approach SemDaServ presented in this article. The research approach is based on Blessing's Design Research Methodology (literature study, derivation of key factors, success criteria, solution functions, solution development, applicability evaluation). SemDaServ provides a three-step process and five accompanying artifacts. Using domain knowledge for data specification is critical and creates additional challenges. Therefore, the SemDaServ approach systematically captures and semantically formalizes domain knowledge in SysML-based models for information and data. The applicability evaluation in expert interviews and expert workshops has confirmed the suitability of SemDaServ for data specification in the context of SSS development. SemDaServ thus offers a systematic approach to specify the data requirements of smart services early on to aid development to continuous integration and continuous delivery scenarios. [ABSTRACT FROM AUTHOR]

To develop smart services to successfully operate as a component of smart service systems (SSS), they need qualitatively and quantitatively sufficient data. This is especially true when using statistical methods from the field of artificial intelligence (AI): training data quality directly determines the quality of resulting AI models. However, AI model quality is only known when AI training can take place. Additionally, the creation of not yet available data sources (e.g., sensors) takes time. Therefore, systematic specification is needed alongside SSS development. Today, there is a lack of systematic support for specifying data relevant to smart services. This gap can be closed by realizing the systematic approach SemDaServ presented in this article. The research approach is based on Blessing’s Design Research Methodology (literature study, derivation of key factors, success criteria, solution functions, solution development, applicability evaluation). SemDaServ provides a three-step process and five accompanying artifacts. Using domain knowledge for data specification is critical and creates additional challenges. Therefore, the SemDaServ approach systematically captures and semantically formalizes domain knowledge in SysML-based models for information and data. The applicability evaluation in expert interviews and expert workshops has confirmed the suitability of SemDaServ for data specification in the context of SSS development. SemDaServ thus offers a systematic approach to specify the data requirements of smart services early on to aid development to continuous integration and continuous delivery scenarios.

Advances in ocean observing technologies and modeling provide the capacity to revolutionize the management of living marine resources. While traditional fisheries management approaches like single-species stock assessments are still common, a global effort is underway to adopt ecosystem-based fisheries management (EBFM) approaches. These approaches consider changes in the physical environment and interactions between ecosystem elements, including human uses, holistically. For example, integrated ecosystem assessments aim to synthesize a suite of observations (physical, biological, socioeconomic) and modeling platforms [ocean circulation models, ecological models, short-term forecasts, management strategy evaluations (MSEs)] to assess the current status and recent and future trends of ecosystem components. This information provides guidance for better management strategies. A common thread in EBFM approaches is the need for high-quality observations of ocean conditions, at scales that resolve critical physical-biological processes and are timely for management needs. Here we explore options for a future observing system that meets the needs of EBFM by (i) identifying observing needs for different user groups, (ii) reviewing relevant datasets and existing technologies, (iii) showcasing regional case studies, and (iv) recommending observational approaches required to implement EBFM. We recommend linking ocean observing within the context of Global Ocean Observing System (GOOS) and other regional ocean observing efforts with fisheries observations, new forecasting methods, and capacity development, in a comprehensive ocean observing framework.

Mercury contamination in aquatic systems has been an issue to the natural ecosystem and human health. Environmental models have become a valuable decision-making tool and play a significant role in mercury pollution control and management. This paper gives an overview of currently available models for simulating mercury transport and fate in aquatic systems. The mercury transformation mechanisms included in these models were identified, as well as data limitations in the models' application. Future advances in understanding mercury transport, cycling, and biogeochemistry in both water column and sediment will improve the robustness of current modeling applications. Moreover, additional field data are critically needed to better predict the concentrations of multi-phase mercury species in various aquatic systems, including measurements in the water column, benthic sediments, and organisms. Field data are also crucial for model calibration and validation. Without this information it will not be possible to adequately understand the environmental factors controlling mercury fate in aquatic systems. The insufficient quantity of adequate measurements and the unsatisfactory accuracy of mercury models are, in numerous cases, supplemented by mass balances since they diminish the unreliability of models. Mercury science evolves gradually with the advancement of science and technology, which requires that mathematical modeling of mercury transport and transformation should be consistently updated. [ABSTRACT FROM AUTHOR]

There is increasing evidence that the impact of climate change on the productivity of grasslands will at least partly depend on their biodiversity. A high level of biodiversity may confer stability to grassland ecosystems against environmental change, but there are also direct effects of biodiversity on the quantity and quality of grassland productivity. To explain the manifold interactions, and to predict future climatic responses, models may be used. However, models designed for studying the interaction between biodiversity and productivity tend to be structurally different from models for studying the effects of climatic impacts. Here we review the literature on the impacts of climate change on biodiversity and productivity of grasslands. We first discuss the availability of data for model development. Then we analyse strengths and weaknesses of three types of model: ecological, process-based and integrated. We discuss the merits of this model diversity and the scope for merging different model types. [ABSTRACT FROM AUTHOR]

This opinion paper summarizes the results of an online survey on the role of experimental work in the hydrological sciences. The 20 survey questions covered various topics, such as advancements, needs, potentials and challenges in the hydrological sciences, and also touched on the issue of data sharing and data publication. A total of 336 hydrologists with both modelling and experimental backgrounds participated. [ABSTRACT FROM AUTHOR]

There is increasing evidence that the impact of climate change on the productivity of grasslands will at least partly depend on their biodiversity. A high level of biodiversity may confer stability to grassland ecosystems against environmental change, but there are also direct effects of biodiversity on the quantity and quality of grassland productivity. To explain the manifold interactions, and to predict future climatic responses, models may be used. However, models designed for studying the interaction between biodiversity and productivity tend to be structurally different from models for studying the effects of climatic impacts. Here we review the literature on the impacts of climate change on biodiversity and productivity of grasslands. We first discuss the availability of data for model development. Then we analyse strengths and weaknesses of three types of model: ecological, process-based and integrated. We discuss the merits of this model diversity and the scope for merging different model types.

Changing climatic, demographic, and land use conditions are projected to alter the provisioning of ecosystem services in estuarine, coastal, and nearshore marine ecosystems, necessitating mitigation and adaptation policies and management. The current paradigm of research efforts occurring in parallel to, rather than in collaboration with, decision makers will be insufficient for the rapid responses required to adapt to and mitigate for projected changing conditions. Here, we suggest a different paradigm: one where research begins by engaging decision makers in the identification of priority data needs (biophysical, economic, and social). This paper uses synthesized interview data to provide insight into the varied demands for scientific research as described by decision makers working on coastal issues in Oregon, USA. The findings highlight the need to recognize (1) the differing framing of ecosystem services by decision makers versus scientists; and (2) the differing data priorities relevant to inland versus coastal decision makers. The findings further serve to highlight the need for decision makers, scientists, and funders to engage in increased communication. This research is an important first step in advancing efforts toward evidence-based decision making in Oregon and provides a template for further research across the US. [ABSTRACT FROM AUTHOR]

Introduction: The system dynamics that are driving changes in health and health care in the United States are not well captured by standard data collection activities. We need systems of data that can inform policy and program development and reflect the increasing recognition that all aspects of people's lives-their work, families, and communities and not just formal health and health care services-support active and healthy living. Culture of Health Action Areas:Within the Culture of Health Framework, there are four action areas that are farther upstream in the sequence of change and point to additional need for more nuanced approach to data collection: building a shared value of health; fostering collaboration to improve well-being; creating health more equitable community environments; and transforming health and health care systems. These action areas define the Culture of Health framework that we hope will spur research and strategies across sectors to improve health. Conclusion: The action framework for advancing a culture of health will guide the Robert Wood Johnson Foundation's grant-making and strategic collaborations. The hope is that it will also catalyze changes in how researchers and organizations collect health related data at all levels. [ABSTRACT FROM AUTHOR]

There is mounting evidence that climatic changes have altered physical conditions in the Laurentian Great Lakes and will continue to do so. In the face of this challenge, fishery managers require useful information to support decision making. We utilized a mixed methods approach, including an email survey and focus groups with fishery managers, to identify information gaps in understanding the impacts of climate change on fishery management The fishery managers perceived climate change to be a threat to the fishery and identified specific climate change information that would be most useful for their work. This includes information on how climate change will affect fish populations, trophic interactions, and habitat conditions, as well as how climate change will interact synergistically with other management concerns. Our findings indicate that future research efforts should focus on species of commercial or recreational interest and species for which restoration plans already exist. Although modeling efforts that incorporate both biotic and abiotic factors may be useful to fishery management stakeholders, to enhance utility for managers, researchers should work with the information users to understand the pertinence of various temporal and spatial scales when designing studies and presenting information. Many fishery managers believe that valuable information related to climate change, particularly long-term datasets, already exists but has not been made easily accessible or brought to their attention. Finally, in order to increase the awareness and use of their climate research, researchers should present at relevant meetings in addition to just emailing reports and publishing scientific manuscripts. [ABSTRACT FROM AUTHOR]

• Data needs for sustainable disaster debris management are identified. • Time-sensitive data are characterized using a four-phase planning framework. • Social network analysis is used to prioritize the collection of the identified data. • Effective reconnaissance methods are needed to capture important post-disaster data. Recycling and reuse are major components of disaster debris management with significant environmental, economic, and social benefits. To develop quantitative and sustainable debris management practices, a broad range of data is required. Existing studies have not comprehensively delineated the data and analysis requirements for quantitative assessment of sustainable debris management, which limits proper disaster data collection and restricts the development of approaches to efficiently quantify, characterize, and allocate disaster waste among existing and emerging debris management pathways. This study aimed to fill this gap by reviewing previous investigations to identify the data required to quantitatively assess both critical and practical aspects of sustainable disaster debris management. The literature review indicated that the most significant data for post-disaster debris management relate to i) the amount and composition of debris; ii) availability of temporary debris management sites; iii) hazards and environmental concerns; iv) economics; v) social considerations; and vi) funding policies. Considering the time-sensitive nature of different disaster debris data types, a four-phase planning framework is proposed for timely collection of data: pre-disaster, post-disaster response, short-term recovery, and long-term recovery. With significant identified data needs and finite amount of resources for data collection, particularly during post-disaster phases, social network analysis (SNA) is used to quantitively evaluate the relative importance of the data needs. Overall, it is recommended to develop comprehensive debris management inventories that aggregate diverse pre-disaster datasets, along with integrated specialized reconnaissance investigations to collect post-disaster data, most of which are identified as high priority. [ABSTRACT FROM AUTHOR]

Background :  This paper describes a pilot study undertaken in 2018, to determine the key data needs of each of the different Ethiopian dairy sector stakeholder groups.  The study aimed to characterise the emerging trends of dairy product production, processing, retailing and consumption in Ethiopia, and to identify and characterise current and future data needs of different stakeholders. Methods :  The study undertook a mapping of the interactions between different stakeholders in the dairy sector, and an interactive evaluation of the institutional data repository and access options.  Focus group discussions and interviews were held in three regions of the country prior to a two-day workshop in the capital Addis Ababa.  Data needs were characterised by type, availability, format, level of detail, methods of dissemination, uptake and use, and the institutional arrangement, including the different roles of public and private sectors in decision making processes. Results :  The study highlighted the main data needs and identified several broader institutional issues constraining the further development of the Ethiopian dairy sector.  The stakeholder groups endorsed the reactivation of a national dairy board, independent of government but closely incorporating government, and with the buy-in and membership of private sector enterprises, including producers, processers, service providers and consumers, to provide clearer facilitative leadership on the dairy industry. Conclusions :  The study workshop provided a timely discussion between diverse stakeholders, including government, and several potential organisations were suggested to host and manage a national dairy database. Importantly, the reactivation of a national dairy board was strongly endorsed.  It was recommended that stakeholder links be established, sector-specific data needs be elevated to higher detail, and a national roll out of herd-specific data recording schemes was called for, to allow for effective evidence-based policies and decision making., Competing Interests: No competing interests were disclosed., (Copyright: © 2022 Perry BD et al.)

We studied a database that recorded all requests to the French National Soil Data Centre between April 2008 and November 2009 when a total of 440 requests were made. Our hypothesis is that an analysis of such requests can provide an insight into awareness of soil issues and data needs. These requests covered a wide range of topics. The most important threats were contamination, erosion and soil organic carbon decline. Soil acidification appeared to be no longer a priority concern. We found a lack of awareness of topics such as soil sealing and soil compaction. Gaps in data coverage are stressed and we highlight some data that were inadequate for some users’ needs. [ABSTRACT FROM AUTHOR]

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The work conducted at the National Institute of Standards and Technology over the last 7 years on the systematic synthesis and assessment of fundamental knowledge on low-energy electron interactions with plasma processing gases is briefly summarized and discussed. This work deals mostly with the primary electron interaction processes. Assessed data on electron collision cross sections and rate coefficients are discussed and their multiple value is indicated. Data needs are identified for electron interactions with ground-state, excited, and transient species, and for electron energy losses. It is indicated that the currently limited knowledge on electron reactions at surfaces and interfaces can be aided by related existing knowledge on electron interactions in dense gases, liquids, clusters, and molecular layers on cold surfaces. [Copyright &y& Elsevier]

New experimental data on heat capacities of pure liquid organic and some inorganic compounds were compiled, and recommended values were developed by critical assessment of literature calorimetrically determined heat capacities. The bulk of the work covered data published in the primary literature between 1993 and 1999 and some data of 2000. This paper presents a survey of some recent measurements of liquid heat capacity and highlights needs for new data on liquid heat capacity for large production organic contaminants, hazardous air pollutants and drinking water contaminants. Results of the critical assessment of data were published in the Journal of Physical and Chemical Reference Data. [ABSTRACT FROM AUTHOR]

Integrated analysis of land-use change in support of informed policy-making for sustainable land use at various spatial levels makes heavy requirements for quality data. This paper aims to structure the principal methodological and practical issues of data needs for this task. The data needs for local level analyses of land-use change are given special attention. The paper adopts an integrated economic–environmental modeling framework and suggests the main types of data needed. Four main data dimensions are distinguished: system of spatial reference, system of temporal reference, definitions, and data collection procedures (sources, collection instruments and techniques, recording and retrieval systems, data format, frequency of data collection). To evaluate the suitability of current data sets as well as to guide the collection of new ones, a scheme based on substantive and practical criteria is employed. The former include compatibility, consistency, and reliability of data, while the latter include availability, ease and cost of data collection/retrieval, and transferability of data. The evaluation indicates the broad gaps in current data sets along the four main data dimensions. Based on this evaluation, the paper suggests framework guidelines to address the main data issues identified. RID="" ID="" 1CLAUDE: Coordinating Land Use and Land Cover Data and Analyses in Europe. European Commission Concerted Action project (DG-XII); DAPLARCH: Data Plan Development for Land Use and Land Cover Change Research. Program sponsored by IGBP-IHDP (LUCC and DIS). Street, Durham, North Carolina 27707, USA [ABSTRACT FROM AUTHOR]