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Background Animal pollination is an important ecosystem function and service, ensuring both the integrity of natural systems and human well-being. Although many knowledge shortfalls remain, some high-quality data sets on biological interactions are now available. The development and adoption of standards for biodiversity data and metadata has promoted great advances in biological data sharing and aggregation, supporting large-scale studies and science-based public policies. However, these standards are currently not suitable to fully support interaction data sharing. Results Here we present a vocabulary of terms and a data model for sharing plant–pollinator interactions data based on the Darwin Core standard. The vocabulary introduces 48 new terms targeting several aspects of plant–pollinator interactions and can be used to capture information from different approaches and scales. Additionally, we provide solutions for data serialization using RDF, XML, and DwC-Archives and recommendations of existing controlled vocabularies for some of the terms. Our contribution supports open access to standardized data on plant–pollinator interactions. Conclusions The adoption of the vocabulary would facilitate data sharing to support studies ranging from the spatial and temporal distribution of interactions to the taxonomic, phenological, functional, and phylogenetic aspects of plant–pollinator interactions. We expect to fill data and knowledge gaps, thus further enabling scientific research on the ecology and evolution of plant–pollinator communities, biodiversity conservation, ecosystem services, and the development of public policies. The proposed data model is flexible and can be adapted for sharing other types of interactions data by developing discipline-specific vocabularies of terms.

In this paper, we discuss how we are using metadata schemas and controlled vocabularies to improve interoperability between Brazilian agriculture and livestock trading data providers. A new metadata schema is being created based on a community-based approach. This method relies on knowledge from specialists to define a list of relevant metadata properties for a given domain. In the first step of the research, we extracted metadata from three datasets maintained by three Brazilian public institutions: the Center for Advanced Studies in Applied Economics (Cepea), the Institute of Applied Economic Research (Ipea), and The National Supply Company (Conab). The extracted metadata were the input to the definition of a list of 15 potential metadata properties that specialists are validating. Made available in DSpace on 2022-10-25T15:10:28Z (GMT). No. of bitstreams: 1 AP-Building-Community-Based-FAIR-2022.pdf: 258413 bytes, checksum: 9fd35929d8c05b5bf8ae3becbcc56af7 (MD5) Previous issue date: 2022 Edition of the 18th International Conference on Semantic Systems, Vienna, Austria. SEMANTiCS 2022.

Human demands on resources such as food and energy are increasing through time while global challenges such as climate change and biodiversity loss are becoming more complex to overcome, as well as more widely acknowledged by societies and governments. Reports from initiatives like the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) have demanded quick and reliable access to high-quality spatial and temporal data of species occurrences, their interspecific relations and the effects of the environment on biotic interactions. Mapping species interactions is crucial to understanding and conserving ecosystem functioning and all the services it can provide (Tylianakis et al. 2010, Slade et al. 2017). Detailed data has the potential to improve our knowledge about ecological and evolutionary processes guided by interspecific interactions, as well as to assist in planning and decision making for biodiversity conservation and restoration (Menz et al. 2011). Although a great effort has been made to successfully standardize and aggregate species occurrence data, a formal standard to support biotic interaction data sharing and interoperability is still lacking. There are different biological interactions that can be studied, such as predator-prey, host-parasite and pollinator-plant and there is a variety of data practices and data representation procedures that can be used. Plant-pollinator interactions are recognized in many sources from the scientific literature (Abrol 2012, Ollerton 2021) for the importance of ecosystem functioning and sustainable agriculture. Primary data about pollination are becoming increasingly available online and can be accessed from a great number of data repositories. While a vast quantity of data on interactions, and on pollination in particular, is available, data are not integrated among sources, largely because of a lack of appropriate standards. We present a vocabulary of terms for sharing plant-pollinator interactions using one of the existing extensions to the Darwin Core standard (Wieczorek et al. 2012). In particular, the vocabulary is meant to be used for the term measurementType of the Extended Measurement Or Facts extension. The vocabulary was developed by a community of specialists in pollination biology and information science, including members of the TDWG Biological Interaction Data Interest Group, during almost four years of collaborative work. The vocabulary introduces 40 new terms, comprising many aspects of plant-pollinator interactions, and can be used to capture information produced by studies with different approaches and scales. The plant-pollinator interactions vocabulary is mainly a set of terms that can be both understood by people or interpreted by machines. The plant-pollinator vocabulary is composed of a defining a set of terms and descriptive documents explaining how the vocabulary is to be used. The terms in the vocabulary are divided into six categories: Animal, Plants, Flower, Interaction, Reproductive Success and Nectar Dynamics. The categories are not formally part of the vocabulary, they are used only to organize the vocabulary and to facilitate understanding by humans. We expect that the plant-pollinator vocabulary will contribute to data aggregation from a variety of sources worldwide at higher levels than we have experienced, significantly amplify plant-pollinator data availability for global synthesis, and contribute to knowledge in conservation and sustainable use of biodiversity.

O GeoInfo é um repositório que disponibiliza os dados de pesquisa espacial gerados pela Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) para compreender a dinâmica da agricultura no território brasileiro. Considerando os esforços necessários para a implantação e institucionalização do repositório, a ausência de estudos da Ciência da Informação relacionados à investigação do impacto dos usos feitos a partir dos dados e informações disponibilizados em repositórios de dados de pesquisa, bem como o processo de avaliação de impactos utilizado pela EMBRAPA desde 1989, é oportuno investigar o impacto do repositório para seu público-alvo, qual seja, especialistas de geociências. Assim, o objetivo deste trabalho é apresentar os resultados de uma avaliação de impactos realizada com o GeoInfo, a partir da metodologia - Ambitec-TICs: Módulo de critérios e indicadores de impactos para Tecnologias de Informação e Comunicação -, especificamente para a dimensão social, existente no Ambitec-TICs. Made available in DSpace on 2021-05-06T02:11:16Z (GMT). No. of bitstreams: 1 5899.pdf: 589235 bytes, checksum: 4985b2b0753250e89f4c9a3f1e10121d (MD5) Previous issue date: 2021

Agrobiodiversity, or biodiversity for food and agriculture, plays a major role in the sustainability of food production. As stated by FAO 2019, agrobiodiversity can provide food production systems and society with a variety of services as ecosystem services, crops resilience to threats, sustainable intensification, livelihoods, food security and nutrition. The official definition of the concept has been given by CBD 2000 as "a broad term that includes all components of biological diversity of relevance to food and agriculture, and all components of biological diversity that constitute the agroecosystem: the variety and variability of animals, plants and micro-organisms, at the genetic, species and ecosystem levels, which are necessary to sustain key functions of the agro-ecosystem, its structure and processes". Thus, agrobiodiversity is primarily based on species and their function in agroecosystems. Many projects for sharing agrobiodiversity data in a structured way have emerged over the years. One realizes in looking at the Bioversity International (2018) crop descriptors list that the earliest groups of descriptors for crops and some associated data emerged back in the 1970s. In the same list, there are four multi-crop descriptors and derived standards, which are broad standards for crop-related data, namely: Core descriptors for in situ conservation of crop wild relatives v.1 (Thormann et al. 2013); FAO/Bioversity multi-crop passport descriptors V.2.1 (Alercia et al. 2015); Descriptors for farmers' knowledge of plants (Aknazarov et al. 2009); Descriptors for Genetic Marker Technologies (Vicente et al. 2004). Core descriptors for in situ conservation of crop wild relatives v.1 (Thormann et al. 2013); FAO/Bioversity multi-crop passport descriptors V.2.1 (Alercia et al. 2015); Descriptors for farmers' knowledge of plants (Aknazarov et al. 2009); Descriptors for Genetic Marker Technologies (Vicente et al. 2004). These standards share some core elements in common, as taxon, location, a period of collecting, and were intended to be used in the context of data on the occurrence of species in nature. Darwin Core, a TDWG standard commonly used for sharing data of taxon occurrence in nature (Wieczorek et al. 2012), is a globally used metadata standard, representing "a large majority of the 1.4 billion of species occurrence records shared by the Global Biodiversity Information Facility (GBIF), published by more than 1561 organizations in 59 countries in January 2020" (Body et al. 2020). Darwin Core is a standardized language that applies unique Internationalized Resource Identifiers (IRIs) to each element assigned as a metadata element, plus a label and a definition. It improves the interoperability between databases in the context of the Semantic Web (Duerst and Suignard 2005). We believe it is possible to use Darwin Core to represent agrobiodiversity data if a metadata extension is developed to enroll the agrobiodiversity concepts missing in Darwin Core. Thus, a research project held at the University of São Paulo in partnership with Brazilian Agricultural Research Corporation started to map concepts and descriptors from the literature for agrobiodiversity data representation. This project is the sequence of the research initiated by Soares et al. 2019. The crop descriptors published by Bioversity International (2018) may be integrated into the metadata extension, but also other standards like Global Genome Biodiversity Network (GGBN) Data Standard v1 (Droege et al. 2016) and the Darwin Core germplasm extension (DwC-germplasm). At the moment, we are designing a mind map to organize the agrobiodiversity concepts. We expect the metadata extension will be useful for the scientific community to share agrobiodiversity data as linked data, applying Resource Description Framework (RDF) as a resource relationship model, for example.

The Brazilian agribusiness sector has been witnessing increasing modernization, caused by the extensive adoption of technologies, with increase in productivity and reduction of risks In addition, the use of digital technologies in farms has recently been increasing, engendering the emerging field of digital agriculture. In this context, this article presents a startup acceleration program, called TechStart Agro Digital, an initiative of Embrapa Agricultural Informatics and Venture Hub with the support of various stakeholders in the agricultural innovation ecosystem. Further, this article presents a methodology for technological and business acceleration focused on agribusinesses, which was proposed by the two institutions, and its application in the first cycle of the program in 2019. The results show that the 11 startups that graduated from the program demonstrated an improvement and growth six months after the acceleration program, and validate the potential of the program in facilitating the development of technologies that are more consolidated and focused on the real problems of agriculture. The post-program follow-up indicates that these agricultural technology startups and organizations (AgTechs) have helped rural producers effectively and efficiently, thereby adding value to Brazilian agriculture. RESUMO O agronegócio brasileiro vem se modernizando pela intensa adoção de tecnologias, com aumento de produtividade e redução de riscos. Mais recentemente, observa-se um crescente aumento no uso das tecnologias digitais no campo, fazendo emergir a chamada Agricultura Digital. Neste contexto, este artigo apresenta o Programa de Aceleração de startups, denominado TechStart Agro Digital, uma iniciativa da Embrapa Informática Agropecuária e da aceleradora Venture Hub com o apoio de vários atores do ecossistema de inovação agrícola. Este trabalho apresenta a metodologia de aceleração tecnológica e de negócios com foco no agronegócio, proposta pelas duas instituições, ilustrando sua aplicação no primeiro ciclo do programa em 2019. Os resultados demonstram que as 11 startups graduadas no Programa demonstraram um aperfeiçoamento e crescimento após os 6 meses de aceleração, viabilizando a proposição de tecnologias mais consolidadas e focadas nos reais problemas da agricultura. O acompanhamento pós-programa indica que estas AgTechs têm auxiliado o produtor rural, efetiva e eficazmente, agregando valor à agricultura brasileira.

RESUMO. Apresenta uma proposta de princípios para criação de uma exten-são de metadados para o padrão Darwin Core para o domínio da agrobiodiversidade, com recorte temático nas interações ecológi-cas. O objetivo da pesquisa é apresentar princípios e recomenda-ções de melhores práticas para a criação de metadados como uma extensão ao Darwin Core. A metodologia consistiu em analisar o modelo , que é um modelo conceitual para representação de dados da biodiversidade desenvolvido pela Em-brapa, para verificar a possibilidade de usar esse modelo como insumo terminológico. Além desse modelo, foi feita análise da lite-ratura especializada para compreender as interações ecológicas. O núcleo de termos do padrão de metadados Darwin Core também foi analisado a fim de se compreender os aspectos semânticos e sintáticos do Darwin Core, que são fundamentais para a criação da extensão de metadados. Ao final do artigo, apresenta-se uma amostra dos resultados que se espera obter ao final da aplicação da metodologia que está em fase de desenvolvimento. Made available in DSpace on 2020-02-12T18:10:16Z (GMT). No. of bitstreams: 1 APPadraometadados.pdf: 562562 bytes, checksum: b227c15210cd21ca3948793ca90484f3 (MD5) Previous issue date: 2019

This research aims to propose principles to creating a metadata extension to the Darwin Core standard that addresses the agrobiodiversity data, with a thematic scope on ecological interactions. These principles have been compiled from the scientific literature, giving special attention to recommendations of the DCMI Abstract Model, which outlines the principles for creating metadata. The DCMI Abstract Model governs the creation of the Dublin Core metadata standard upon which Darwin Core is based. The requirements of ISO/IEC 11179-4/2004 standard for the definition of metadata were also taken into consideration. The research is in progress, so what is exposed in this article are preliminary results. A prototype of a metadata record for the field of ecological interactions, which is the scope of research within agrobiodiversity, was created to demonstrate the format that metadata will have when the extension is finalized. This research represents an initial effort to propose more effective tools for agrobiodiversity data management, but it is necessary to mature and deepen the discussions around the conceptual aspects of the ecological interactions in agrobiodiversity and the relationship of the new metadata extension with the term set of the Darwin Core, as well a robust methodology to create DwC extensions is still pending of being developed. This research aims to propose principles to creating a metadata extension to the Darwin Core standard that addresses the agrobiodiversity data, with a thematic scope on ecological interactions. These principles have been compiled from the scientific literature, giving special attention to recommendations of the DCMI Abstract Model, which outlines the principles for creating metadata. The DCMI Abstract Model governs the creation of the Dublin Core metadata standard upon which Darwin Core is based. The requirements of ISO/IEC 11179-4/2004 standard for the definition of metadata were also taken into consideration. The research is in progress, so what is exposed in this article are preliminary results. A prototype of a metadata record for the field of ecological interactions, which is the scope of research within agrobiodiversity, was created to demonstrate the format that metadata will have when the extension is finalized. This research represents an initial effort to propose more effective tools for agrobiodiversity data management, but it is necessary to mature and deepen the discussions around the conceptual aspects of the ecological interactions in agrobiodiversity and the relationship of the new metadata extension with the term set of the Darwin Core, as well a robust methodology to create DwC extensions is still pending of being developed.

Sob as premissas do acesso aberto, o atual contexto de produção da ciência vem expressando valor ao compartilhamento e abertura dos dados de pesquisa. No Brasil, o Decreto Lei n. 6.666/08, que instituiu a Infraestrutura Nacional de Dados Espaciais (Inde), estabelece-se como um exemplo bem sucedido de iniciativa para a abertura de dados espaciais, tendo influenciado a Embrapa a promover a abertura de seus dados espaciais gerados no âmbito de suas pesquisas. Para a disponibilização do dado de pesquisa, é preciso considerar as questões associadas à representação do dado, ou precisamente, a descrição dos metadados como elemento crucial para que o dado possa disponibilizado. Diante disso, o objetivo deste trabalho é apresentar a experiência da Embrapa em estruturar o processo da organização e representação dos dados espaciais, contextualizando-os sob as considerações da Ciência da Informação e Geociências. Made available in DSpace on 2018-01-09T16:09:41Z (GMT). No. of bitstreams: 1 4889.pdf: 510859 bytes, checksum: ee3063a5658a908f1cf6e837112cae9b (MD5) Previous issue date: 2017-12-21 Suplemento. Trabalhos apresentados na 8a Conferência Luso Brasileira sobre Acesso Aberto - ConfOA. Na publicação: Davi Oliveira Custódio, Bibiana Teixeira Almeida, Margareth Simões, Gustavo Bayma-Silva.

Resumo. A geoinformação é essencial para o planejamento e monitoramento das atividades agropecuárias, justificando o emprego de esforços para reuni-la e padronizá-la de acordo com as diretrizes governamentais e possibiltando sua disponibilização à sociedade em geral. O objetivo deste trabalho é apresentar a experiência da Embrapa em construir sua Infraestrutura de Dados Espaciais, denominada GeoInfo, uma iniciativa para organizar, preservar, documentar e ofertar dados geoespaciais abertos produzidos nas pesquisas da empresa, ampliando o potencial de aplicação dessa informação na produção e difusão de conhecimento e inovação. O GeoInfo implementa os padrões da Infraestrutura Nacional de Dados Espaciais e viabiliza a interoperabilidade de dados geoespaciais provenientes de diferentes fontes, inclusive sob o aspecto semântico. Essa iniciativa possibilita a integração das informações geoespaciais produzidas na Embrapa com diversas informações disponíveis em nosso país e permite que a redundância de esforços na obtenção e produção de dados geoespaciais sejam evitados. Made available in DSpace on 2017-12-21T23:35:59Z (GMT). No. of bitstreams: 1 GeoInfo.pdf: 1278892 bytes, checksum: 2cd5fb0bd47329844a25d32038e1f36b (MD5) Previous issue date: 2017-12-21 Suplemento. Trabalhos apresentados na 8a Conferência Luso Brasileira sobre Acesso Aberto - ConfOA. Na publicação: Davi Oliveira Custódio, Bibiana Teixeira Almeida, Margareth Simões, Gustavo Bayma-Silva.

O compartilhamento de recursos computacionais, o acesso distribuído a grandes conjuntos de dados e o uso de plataformas digitais para colaboração e comunicação são características que distinguem a e-Science do paradigma científico tradicional. Esse trabalho situa a Gestão de Dados de Pesquisa como elemento propulsor do avanço científico e tecnológico no paradigma emergente da e-Science, e alerta quanto aos desafios que se impõem às universidades e organizações atuantes no setor de Pesquisa e Desenvolvimento. Além de explorar os princípios e os fundamentos da Gestão de Dados de Pesquisa, o trabalho propõe, a partir de uma abordagem pragmática, um roteiro para a implantação de um programa institucional de Gestão Dados de Pesquisa. Made available in DSpace on 2017-12-06T23:32:13Z (GMT). No. of bitstreams: 1 Agestaodedadosdepesquisa....pdf: 410353 bytes, checksum: 2790f4bdf7cb2c8fad115317151cdbfa (MD5) Previous issue date: 2017-12-06

Additional Supporting Information may be found online at: http://onlinelibrary.wiley.com/doi/10.1002/ecs2.1561/full, Drought is a global issue that is exacerbated by climate change and increasing anthropogenic water demands. The recent occurrence of drought in California provides an important opportunity to examine drought response across ecosystem classes (forests, shrublands, grasslands, and wetlands), which is essential to understand how climate influences ecosystem structure and function. We quantified ecosystem resistance to drought by comparing changes in satellite-derived estimates of water-use efficiency (WUE = net primary productivity [NPP]/evapotranspiration [ET]) under normal (i.e., baseline) and drought conditions (ΔWUE = WUE2014 − baseline WUE). With this method, areas with increasing WUE under drought conditions are considered more resilient than systems with declining WUE. Baseline WUE varied across California (0.08 to 3.85 g C/mm H2O) and WUE generally increased under severe drought conditions in 2014. Strong correlations between ΔWUE, precipitation, and leaf area index (LAI) indicate that ecosystems with a lower average LAI (i.e., grasslands) also had greater C-uptake rates when water was limiting and higher rates of carbon-uptake efficiency (CUE = NPP/LAI) under drought conditions. We also found that systems with a baseline WUE ≤ 0.4 exhibited a decline in WUE under drought conditions, suggesting that a baseline WUE ≤ 0.4 might be indicative of low drought resistance. Drought severity, precipitation, and WUE were identified as important drivers of shifts in ecosystem classes over the study period. These findings have important implications for understanding climate change effects on primary productivity and C sequestration across ecosystems and how this may influence ecosystem resistance in the future., The authors would like to acknowledge the excellent support provided by the Open Science for Synthesis-2014 training (supported by the National Science Foundation under Grant No. OCI-1216894) at the National Center for Ecological Analysis and Synthesis (NCEAS), a center funded by the University of California, Santa Barbara, and the State of California. The authors would like to thank OSS instructors Nancy Baron, Ben Bolker, Stephanie Hampton, Matthew Jones, Karthik Ram, Mark Schildhauer, and the participants of the OSS training. The authors would also like to thank the Goulden Lab at the University of California Irvines. A. J. Pérez-Luque acknowledges funding received by NCEAS and to MICINN (Spanish Government) for the PTA 2011-6322- I contract; D. P. Drucker acknowledges support from the USAID and the U.S. Department of State through the Sustainable Landscapes Brazil program; and M.G. Tulbure acknowledges funding from the Australian Research Council Early Career Researcher Award (DE140101608).