cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35078/z6q3un
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Diamantina | Município: Santana do Pirama

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.6084/m9.figshare.22713661.v1
title: <strong>Field Survey of 2021 Typhoon Rai –Odette- in the Philippines</strong>

description: Typhoon Rai struck the Philippines on the 16th December 2021, damaging and inundating many coastal areas along the Visayas region of the country due to the high winds, storm surges and wind driven waves it generated. In order to understand the various damage mechanisms, the authors conducted a field survey to measure the storm surge heights at several locations in the provinces of Cebu and Bohol. As part of the survey, local residents were interviewed to understand the phenomena and survey the height reached by the storm surge. The maximum storm surge level measured were 2.54 m, 4.24 m and 4.06 m along the provinces of Cebu and Bohol. Finally, some interesting characteristics of the storm surge are summarised, and the lessons learnt in terms of disaster risk management are discussed
DOI: 10.5281/zenodo.7876253
title: Datasets of issue-commit and issue-method links extracted from GitHub repositories

description: Contains issue-commit and issue-method links extracted from GitHub repositories. Available on GitHub: https://github.com/pragma-once/utilizing-bert-for-traceability/releases
DOI: 10.5281/zenodo.7876252
title: Datasets of issue-commit and issue-method links extracted from GitHub repositories

description: Contains issue-commit and issue-method links extracted from GitHub repositories. Available on GitHub: https://github.com/pragma-once/utilizing-bert-for-traceability/releases
DOI: 10.5281/zenodo.7544930
title: GoNEXUS SEF application: Andalusia practical case study

description: Data for the figures in the journal article: Gonzalez-Rosell A, Arfa I and Blanco M (2023) Introducing GoNEXUS SEF: a solutions evaluation framework for the joint governance of water, energy, and food resources. Sustainability Science. https://doi.org/10.1007/s11625-023-01324-1 Figure 3. Generation of new quantitative evidence: Percentage of variation of indicators between the water price scenario (WP) and baseline scenario (BS) for the year 2030. Source: Own elaboration based on the participatory SDM results (González-Rosell et al., 2020). Figure 4. Cross-impact matrix of the indicator system and solution from Table 2 for the water pricing in the Andalusia case study. Source: Own elaboration. Figure 5. Analysis of the degree of distribution of the network system based on the cross-impact matrix in Figure 4. Source: Own elaboration. Figure 6. (a) Full network graph: links between 16 indicators and WP solution based on the cross-impact matrix. (b) Tree network graph of the total influence of the WP solution at the first and second order based on the cross-impact matrix. Colour scale as in Figure 8. Synergies (green) and trade-off (red) of the WP solution on policy objectives and nexus objectives in Andalusia. Source: Own elaboration.
description: {"references": ["Gonz\u00e1lez-Rosell A, Blanco M, and Arfa I (2020) Integrating Stakeholder Views and System Dynamics to Assess the Water\u2013Energy\u2013Food Nexus in Andalusia. Water, 12(11), 3172, https://doi.org/10.3390/w12113172"]}
DOI: 10.5281/zenodo.7544931
title: GoNEXUS SEF application: Andalusia practical case study

description: Data for the figures in the journal article: Gonzalez-Rosell A, Arfa I and Blanco M (2023) Introducing GoNEXUS SEF: a solutions evaluation framework for the joint governance of water, energy, and food resources. Sustainability Science. https://doi.org/10.1007/s11625-023-01324-1 Figure 3. Generation of new quantitative evidence: Percentage of variation of indicators between the water price scenario (WP) and baseline scenario (BS) for the year 2030. Source: Own elaboration based on the participatory SDM results (González-Rosell et al., 2020). Figure 4. Cross-impact matrix of the indicator system and solution from Table 2 for the water pricing in the Andalusia case study. Source: Own elaboration. Figure 5. Analysis of the degree of distribution of the network system based on the cross-impact matrix in Figure 4. Source: Own elaboration. Figure 6. (a) Full network graph: links between 16 indicators and WP solution based on the cross-impact matrix. (b) Tree network graph of the total influence of the WP solution at the first and second order based on the cross-impact matrix. Colour scale as in Figure 8. Synergies (green) and trade-off (red) of the WP solution on policy objectives and nexus objectives in Andalusia. Source: Own elaboration.
description: {"references": ["Gonz\u00e1lez-Rosell A, Blanco M, and Arfa I (2020) Integrating Stakeholder Views and System Dynamics to Assess the Water\u2013Energy\u2013Food Nexus in Andalusia. Water, 12(11), 3172, https://doi.org/10.3390/w12113172"]}
DOI: 10.35078/egnbks
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Diamantina | Município: Santana do Pirapama

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.15468/dl.va9xnc
title: Occurrence Download

description: A dataset containing 3014 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is South Africa",
 {
 "or" : [
 "TaxonKey is Polygonum aviculare L.",
 "TaxonKey is Polydora hoplura Claparède, 1868",
 "TaxonKey is Polydora websteri Hartman, 1943",
 "TaxonKey is Polycera hedgpethi Er.Marcus, 1964",
 "TaxonKey is Polistes dominula (Christ, 1791)",
 "TaxonKey is Poicephalus rufiventris (Ruppell, 1845)",
 "TaxonKey is Poicephalus rueppellii (G.R.Gray, 1849)",
 "TaxonKey is Pogonognathellus flavescens (Tullberg, 1871)",
 "TaxonKey is Pogona vitticeps (Ahl, 1926)",
 "TaxonKey is Poecilia reticulata Peters, 1859",
 "TaxonKey is Poa trivialis L.",
 "TaxonKey is Poa pratensis L.",
 "TaxonKey is Poa compressa L.",
 "TaxonKey is Poa annua L.",
 "TaxonKey is Plutella xylostella (Linnaeus, 1767)",
 "TaxonKey is Plodia interpunctella (Hübner, 1813)",
 "TaxonKey is Ploceus nigerrimus Vieillot, 1819",
 "TaxonKey is Plexippus paykulli (Audouin, 1826)",
 "TaxonKey is Plectranthus barbatus var. grandis (L.H.Cramer) Lukhoba & A.J.Paton",
 "TaxonKey is Platycerium bifurcatum (Cav.) C.Chr.",
 "TaxonKey is Platorchestia platensis (Krøyer, 1845)",
 "TaxonKey is Platanus ×acerifolia (Aiton) Willd.",
 "TaxonKey is Plantago virginica L.",
 "TaxonKey is Plantago major L.",
 "TaxonKey is Plantago lanceolata L.",
 "TaxonKey is Planococcus ficus (Signoret, 1875)",
 "TaxonKey is Planococcus citri (Risso, 1813)",
 "TaxonKey is Pityrogramma calomelanos (L.) Link",
 "TaxonKey is Pituophis melanoleucus (Daudin, 1803)",
 "TaxonKey is Pituophis deppei (Duméril, 1853)",
 "TaxonKey is Pituophis catenifer (Blainville, 1835)",
 "TaxonKey is Pittosporum undulatum Vent.",
 "TaxonKey is Pittosporum crassifolium Banks & Sol. ex A.Cunn.",
 "TaxonKey is Pistia stratiotes L.",
 "TaxonKey is Pissodes nemorensis E.F.Germar, 1823",
 "TaxonKey is Pisolithus tinctorius (Pers.) Coker & Couch",
 "TaxonKey is Pisolithus microcarpus (Cooke & Massee) G.Cunn.",
 "TaxonKey is Pisolithus arhizus (Scop.) Rauschert",
 "TaxonKey is Piophila casei (Linnaeus, 1758)",
 "TaxonKey is Pinus taeda L.",
 "TaxonKey is Pinus roxburghii Sarg.",
 "TaxonKey is Pinus radiata D.Don",
 "TaxonKey is Pinus pinea L.",
 "TaxonKey is Pinus pinaster Aiton",
 "TaxonKey is Pinus patula Schiede ex Schltdl. & Cham.",
 "TaxonKey is Pinus halepensis Mill.",
 "TaxonKey is Pinus elliottii Engelm.",
 "TaxonKey is Pinus canariensis C.Sm.",
 "TaxonKey is Pinnixa occidentalis Rathbun, 1894",
 "TaxonKey is Pineus pini (Goeze, 1778)",
 "TaxonKey is Pineus boerneri Annand, 1928",
 "TaxonKey is Pinauay ralphi (Bale, 1884)",
 "TaxonKey is Pieris brassicae (Linnaeus, 1758)",
 "TaxonKey is Phytophthora pinifolia Alv.Durán, Gryzenh. & M.J.Wingf.",
 "TaxonKey is Phytophthora cinnamomi Rands"
 ]
 }
 ]
}

 The dataset includes 3014 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002449-200127171203522/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5c8zvc
title: Occurrence Download

description: A dataset containing 1134574 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dendrocopos major (Linnaeus, 1758))",
 "HasCoordinate is true",
 "DecimalLatitude is greater than or equal to 29.93667",
 "DecimalLatitude is less than or equal to 51.91193",
 "DecimalLongitude is greater than or equal to -14.67522",
 "DecimalLongitude is less than or equal to 39.79752",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation)",
 "Year is greater than or equal to 1970",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1134574 records from 2942 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041144-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.12440285
title: Data from "Membrane Fusion and Drug Delivery with Carbon Nanotube Porins" by Nga T. Ho, Marc Siggel, Karen V. Camacho, Ramachandra M. Bhaskara , Jacqueline M. Hicks, Yun-Chiao Yao, Yuliang Zhang, Jurgen Kofinger , Gerhard Hummer, and Aleksandr Noy

description: Data from "Membrane Fusion and Drug Delivery with Carbon Nanotube Porins"
DOI: 10.6084/m9.figshare.12440285.v1
title: Data from "Membrane Fusion and Drug Delivery with Carbon Nanotube Porins" by Nga T. Ho, Marc Siggel, Karen V. Camacho, Ramachandra M. Bhaskara , Jacqueline M. Hicks, Yun-Chiao Yao, Yuliang Zhang, Jurgen Kofinger , Gerhard Hummer, and Aleksandr Noy

description: Data from "Membrane Fusion and Drug Delivery with Carbon Nanotube Porins"
DOI: 10.6084/m9.figshare.13220622
title: Walking through the forests of the future: using data-driven virtual reality to visualize forests under climate change

description: Communicating and understanding climate induced environmental changes can be challenging, especially using traditional representations such as graphs, maps or photos. Immersive visualizations and experiences offer an intuitive, visceral approach to otherwise rather abstract concepts, but creating them scientifically is challenging. In this paper, we linked ecological modeling, procedural modeling, and virtual reality to provide an immersive experience of a future forest. We mapped current tree species composition in northern Wisconsin using the Forest Inventory and Analysis (FIA) data and then forecast forest change 50 years into the future under two climate scenarios using LANDIS-II, a spatially-explicit, mechanistic simulation model. We converted the model output (e.g., tree biomass) into parameters required for 3D visualizations with analytical modeling. Procedural rules allowed us to efficiently and reproducibly translate the parameters into a simulated forest. Data visualization, environment exploration, and information retrieval were realized using the Unreal Engine. A system evaluation with experts in ecology provided positive feedback and future topics for a comprehensive ecosystem visualization and analysis approach. Our approach to create visceral experiences of forests under climate change can facilitate communication among experts, policy-makers, and the general public.
DOI: 10.6084/m9.figshare.13220622.v1
title: Walking through the forests of the future: using data-driven virtual reality to visualize forests under climate change

description: Communicating and understanding climate induced environmental changes can be challenging, especially using traditional representations such as graphs, maps or photos. Immersive visualizations and experiences offer an intuitive, visceral approach to otherwise rather abstract concepts, but creating them scientifically is challenging. In this paper, we linked ecological modeling, procedural modeling, and virtual reality to provide an immersive experience of a future forest. We mapped current tree species composition in northern Wisconsin using the Forest Inventory and Analysis (FIA) data and then forecast forest change 50 years into the future under two climate scenarios using LANDIS-II, a spatially-explicit, mechanistic simulation model. We converted the model output (e.g., tree biomass) into parameters required for 3D visualizations with analytical modeling. Procedural rules allowed us to efficiently and reproducibly translate the parameters into a simulated forest. Data visualization, environment exploration, and information retrieval were realized using the Unreal Engine. A system evaluation with experts in ecology provided positive feedback and future topics for a comprehensive ecosystem visualization and analysis approach. Our approach to create visceral experiences of forests under climate change can facilitate communication among experts, policy-makers, and the general public.
DOI: 10.6084/m9.figshare.14114530
title: Participatory modelling for climate change adaptation: the poultry sector in Nigeria

description: Strategies for agricultural climate change adaptation are needed to ensure that sub-Saharan Africa can continue to feed itself, given its rapidly growing population and the expected impacts of climate change on food production. The poultry sector is an important component of the African food system, but national climate change adaptation plans in many countries fail to take into account the specific contextual challenges faced by poultry producers. We developed a participatory system dynamics modelling tool to involve stakeholders from the poultry sector in Nigeria in analyzing how climate impacts would affect the sector, with the goal of generating insights for state (sub-national) and national scale policy makers. A second goal of the exercise was to facilitate social learning and knowledge sharing on adaptation strategies among the stakeholders. Given the high uncertainty of the conditions surrounding the Nigerian poultry sector, the model's use is primarily as a discussion tool for poultry sector stakeholders, including policy makers, to share concerns and develop adaptation strategies. It served this purpose, as evidenced by the creation of a manual for poultry producers from the exercise. Similar stakeholder engagement efforts can stimulate knowledge sharing around climate change adaptation for problems around which limited data and high uncertainty exist. <b>Key policy insights</b>Participatory system dynamics modelling is shown to be a useful tool for integrating national and community-level priorities for policy and management under climate change in the Nigerian poultry sector.Effective climate change adaptation will require building resilience to large-scale external drivers such as global trade dynamics, which are highly influential in the system.In order to effectively move from planning to implementation, climate change adaptation processes must facilitate social learning and knowledge sharing around the long-term consequences of policy and management choices. Participatory system dynamics modelling is shown to be a useful tool for integrating national and community-level priorities for policy and management under climate change in the Nigerian poultry sector. Effective climate change adaptation will require building resilience to large-scale external drivers such as global trade dynamics, which are highly influential in the system. In order to effectively move from planning to implementation, climate change adaptation processes must facilitate social learning and knowledge sharing around the long-term consequences of policy and management choices.
DOI: 10.6084/m9.figshare.14114530.v1
title: Participatory modelling for climate change adaptation: the poultry sector in Nigeria

description: Strategies for agricultural climate change adaptation are needed to ensure that sub-Saharan Africa can continue to feed itself, given its rapidly growing population and the expected impacts of climate change on food production. The poultry sector is an important component of the African food system, but national climate change adaptation plans in many countries fail to take into account the specific contextual challenges faced by poultry producers. We developed a participatory system dynamics modelling tool to involve stakeholders from the poultry sector in Nigeria in analyzing how climate impacts would affect the sector, with the goal of generating insights for state (sub-national) and national scale policy makers. A second goal of the exercise was to facilitate social learning and knowledge sharing on adaptation strategies among the stakeholders. Given the high uncertainty of the conditions surrounding the Nigerian poultry sector, the model's use is primarily as a discussion tool for poultry sector stakeholders, including policy makers, to share concerns and develop adaptation strategies. It served this purpose, as evidenced by the creation of a manual for poultry producers from the exercise. Similar stakeholder engagement efforts can stimulate knowledge sharing around climate change adaptation for problems around which limited data and high uncertainty exist. <b>Key policy insights</b>Participatory system dynamics modelling is shown to be a useful tool for integrating national and community-level priorities for policy and management under climate change in the Nigerian poultry sector.Effective climate change adaptation will require building resilience to large-scale external drivers such as global trade dynamics, which are highly influential in the system.In order to effectively move from planning to implementation, climate change adaptation processes must facilitate social learning and knowledge sharing around the long-term consequences of policy and management choices. Participatory system dynamics modelling is shown to be a useful tool for integrating national and community-level priorities for policy and management under climate change in the Nigerian poultry sector. Effective climate change adaptation will require building resilience to large-scale external drivers such as global trade dynamics, which are highly influential in the system. In order to effectively move from planning to implementation, climate change adaptation processes must facilitate social learning and knowledge sharing around the long-term consequences of policy and management choices.
DOI: 10.6084/m9.figshare.13711730.v1
title: Carbon accounting for negative emissions technologies

description: Negative emissions technologies (NETs) are an essential part of most scenarios for achieving the Paris Agreement goal of limiting warming to below 2°C and for all scenarios that limit warming to 1.5 °C. The deployment of these technologies requires carbon accounting methods for a range of different purposes, such as determining the effectiveness of specific technologies or incentivising NETs. Although the need for carbon accounting methods is discussed within the literature on NETs, there does not appear to be a clear understanding of the range of different accounting challenges. Based on a systematic literature review this study identifies five distinct accounting issues related to NETs: 1. estimating total system-wide change in emissions/removals; 2. non-permanence; 3. non-equivalence of ‘no overshoot’ and ‘overshoot and removal’; 4. accounting for incentives for NETs; and 5. the temporal distribution of emissions/removals. Solutions to these accounting challenges are proposed, or alternatively, areas for further research and the development of solutions are highlighted. One key recommendation is that carbon accounting methods should follow a ‘reality principle’ to report emissions and removals when and where they actually occur, and an important overall conclusion is that it is essential to use the correct accounting method for its appropriate purpose. For example, consequential methods that take account of total system-wide changes in emissions/removals should be used if the purpose is to inform decisions on the deployment or incentivisation of NETs. Attributional methods, however, should be used if the purpose is to construct static descriptions of possible net zero worlds. <b>Key policy insights</b>Negative emissions technologies (NETs) raise a number of distinct carbon accounting challenges, the importance of which varies across different NETs.Attributional life cycle assessment is not an appropriate method for estimating the system-wide changes caused by the deployment of NETs.Consequential greenhouse gas accounting methods should be used to estimate system-wide changes, and should be used as much as possible for guiding incentives for NETs.Greenhouse gas accounting methods should follow a ‘reality principle’ to report emissions and removals when and where they actually occur. Negative emissions technologies (NETs) raise a number of distinct carbon accounting challenges, the importance of which varies across different NETs. Attributional life cycle assessment is not an appropriate method for estimating the system-wide changes caused by the deployment of NETs. Consequential greenhouse gas accounting methods should be used to estimate system-wide changes, and should be used as much as possible for guiding incentives for NETs. Greenhouse gas accounting methods should follow a ‘reality principle’ to report emissions and removals when and where they actually occur.