35 research outputs found
PrincÃpios para a criação de uma extensão de metadados sobre interações ecológicas na agrobiodiversidade para o padrão Darwin Core
Information is an intrinsic element to human relations. When transmitted or stored in digital media, it needs to be well described so it can be efficiently retrieved, accessed and interpreted by society. Among the themes of interest to society today, agrobiodiversity is a broad concept that involves organisms and ecosystems related to agricultural production and crops. For computational systems, the representation of information produced about agrobiodiversity can be done with metadata. However, the existing metadata standards do not fully include the representation of some concepts of agrobiodiversity, as in the Darwin Core (DwC) standard. The aim of this research was to present principles for the creation of an extension of metadata for the DwC standard, having as scope the ecological interactions in the context of agrobiodiversity. To achieve the research aim, the methodology, characterized as exploratory, qualitative, applied and descriptive, was divided into two stages: 1) exploration of methodological and terminological inputs; 2) terminological definition and metadata modeling. The execution of the first stage of the methodology was organized into four substeps: a) systematic analysis of the literature on ecological interactions; b) analysis of the main core of DwC terms; c) analysis of the extensions to the DwC metadata standard; d) correlated terminological analysis of the classes of the model , DwC and concepts of ecological interactions. The first substep resulted in a conceptual model on ecological interactions; the second substep resulted in the translation of the definitions of the terms of the main core of the DwC and respective analyzes; the third substep presented a summary of the content of the metadata extensions developed for DwC in other projects; and, finally, the fourth substep consisted of analyzing in a correlated manner the classes of the model, which was developed by Embrapa in order to organize information on agrobiodiversity, the DwC term classes and their extensions and the conceptual model of ecological interactions. The second stage of the methodology resulted in three metadata elements, created to represent the interaction of parasitism, represented as a metadata record in Extensible Markup Language (XML). It is considered that the greatest contribution of this research was to present a set of methodological principles for the creation of an extension of metadata for the representation of ecological interactions in the context of agrobiodiversity, which can foster improvements in agricultural practices, which are important for the entire community. society, as well as for the field of information science studies
Aplicação de metadados na padronização de registros de ocorrência de espécies no contexto da ciência cidadã para a biodiversidade: um estudo de caso
This study deals with the interoperability between different biodiversity informationsystems, with respect to the description of species occurrence records, with a view to sharing data.The objective of the study was to analyze how the interoperability occurs between informationalenvironments: a) a species occurrence record between iNaturalist (iNat) and Global BiodiversityInformation Facility (GBIF) and b) biological interactions data between iNaturalist (iNat) and GlobalBiotic Interactions (GloBI). The methodological procedures are of exploratory and descriptiveobjectives, with a qualitative approach, and adopted the single case study technique, analyzing howthe semantic interoperability occurs between the selected informational environments. Analyses of the data imported by GBIF and GloBI were carried out, having as origin the data from iNat, highlightinghow interoperability occurred between these systems. The results showed that the use of metadatastandards allows different information environments to share data among themselves, ensuringsemantic interoperability between their metadata. Specifically, between iNat-GBIF and iNat-GloBI,semantic interoperability occurs through the use of metadata standards and controlled vocabularies.The GBIF system automatically recognized and indexed the data record created in iNat with DarwinCore (DwC) metadata. The same was true for GloBI, which automatically recognized and indexed theiNat data record. As a limitation, it is indicated that the metadata analysis was restricted to a smallgroup, leading to the suggestion of future study in a broader scope, also involving other metadatastandards
WorldFAIR Project (D10.1) Agriculture-related pollinator data standards use cases report
Although pollination is an essential ecosystem service that sustains life on Earth, data on this vital process is largely scattered or unavailable, limiting our understanding of the current state of pollinators and hindering effective actions for their conservation and sustainable management. In addition to the well-known challenges of biodiversity data management, such as taxonomic accuracy, the recording of biotic interactions like pollination presents further difficulties in proper representation and sharing. Currently, the widely-used standard for representing biodiversity data, Darwin Core, lacks properties that allow for adequately handling biotic interaction data, and there is a need for FAIR vocabularies for properly representing plant-pollinator interactions. Given the importance of mobilising plant-pollinator interaction data also for food production and security, the Research Data Alliance Improving Global Agricultural Data Community of Practice has brought together partners from representative groups to address the challenges of advancing interoperability and mobilising plant-pollinator data for reuse. This report presents an overview of projects, good practices, tools, and examples for creating, managing and sharing data related to plant-pollinator interactions, along with a work plan for conducting pilots in the next phase of the project.
We present the main existing data indexing systems and aggregators for plant-pollinator interaction data, as well as citizen science and community-based sourcing initiatives. We also describe current challenges for taxonomic knowledge and present two data models and one semantic tool that will be explored in the next phase. In preparation for the next phase, which will provide best practices and FAIR-aligned guidelines for documenting and sharing plant-pollinator interactions based on pilot efforts with data, this Case Study comprehensively examined the methods and platforms used to create and share such data. By understanding the nature of data from various sources and authors, the alignment of the retrieved datasets with the FAIR principles was also taken into consideration. We discovered that a large amount of data on plant-pollinator interaction is made available as supplementary files of research articles in a diversity of formats and that there are opportunities for improving current practices for data mobilisation in this domain. The diversity of approaches and the absence of appropriate data vocabularies causes confusion, information loss, and the need for complex data interpretation and transformation. Our explorations and analyses provided valuable insights for structuring the next phase of the project, including the selection of the pilot use cases and the development of a ‘FAIR best practices’ guide for sharing plant-pollinator interaction data. This work primarily focuses on enhancing the interoperability of data on plant-pollinator interactions, envisioning its connection with the effort WorldFAIR is undertaking to develop a Cross-Domain Interoperability Framework.
Visit WorldFAIR online at http://worldfair-project.eu.
WorldFAIR is funded by the EC HORIZON-WIDERA-2021-ERA-01-41 Coordination and Support Action under Grant Agreement No. 101058393
A aplicação do método de análise de conteúdo na ciência da informação: um estudo preliminar no contexto das teses e dissertações da UFMG
It presents a mapping on the application of the content analysis method in the theses and dissertations of the School of Information Science at the Federal University of Minas Gerais. The objective of the study is to verify which themes of Information Science apply the method of content analysis and how their techniques are being applied. The methodology applied was content analysis, specifically the thematic categorical analysis technique. The results showed that most studies that apply the content analysis method use it as a complementary method, usually during the analysis of data from interviews or documents. They also point out that the most used content analysis technique is the thematic categorical analysis.Presenta un mapeo sobre la aplicación del método de análisis de contenido en las tesis y disertaciones de la Facultad de Ciencias de la Información de la Universidad Federal de Minas Gerais. El objetivo del estudio es verificar qué temas de las Ciencias de la Información aplican el método de análisis de contenido y cómo se están aplicando sus técnicas. La metodologÃa aplicada fue el análisis de contenido, especÃficamente la técnica de análisis categorial temática. Los resultados mostraron que la mayorÃa de los estudios que aplican el método de análisis de contenido lo utilizan como método complementario, generalmente durante el análisis de datos de entrevistas o documentos. También señalan que la técnica de análisis de contenido más utilizada es el análisis categorial temático.Apresenta um mapeamento sobre a aplicação do método da análise de conteúdo nas teses e dissertações da Escola de Ciência da Informação da Universidade Federal de Minas Gerais. O objetivo do estudo é verificar quais temáticas da Ciência da Informação aplicam o método da análise de conteúdo e como suas técnicas estão sendo aplicadas. A metodologia aplicada foi a análise de conteúdo, especificamente a técnica de análise categorial temática. Os resultados evidenciaram que a maior parte dos estudos que aplicam o método de análise de conteúdo a utilizam como método complementar, geralmente durante a análise de dados de entrevistas ou documentos. Também apontam que a técnica da análise de conteúdo mais utilizada é a análise categorial temática
Flower-Insect Timed Counts (FIT Count):protocol adaptation and preliminary results in Brazil
FIT Count (Flower-Insect Timed Counts) is a citizen science initiative that seeks to monitor flower visitation by diverse pollinator groups, including bumblebees, stingless bees, honeybees, flies, hummingbirds, among others. The protocol entails determining a 50 x 50 cm plot area around a target plant species, photographing the plant and conducting a standardized 10-minute survey on this area to estimate the frequency of flower visits by different pollinator groups. Conducting FIT Counts in different habitats and locations produces data on the temporal and spatial dynamics of these interactions (Carvell 2022, UK Pollinator Monitoring Scheme 2018).FIT Count methodology was originally developed by the UK Pollinator Monitoring Scheme (PoMS) and has been used in the United Kingdom since 2017, with over 8,500 counts conducted to date. In 2021, the FIT Count application (app) was launched in the United Kingdom, and became available in Brazil, Chile, Argentina, and some other European countries in 2022. After installation, users may select in which country the observations will be conducted and their preferred language, either English or the main native language of participating countries. The adaptation of the application for use by Brazilian citizen scientists involved not only the translation of the interface, but also relied on the expertise of a local team who helped select which plant species and pollinator groups would be appropriate and representative of biodiversity within the country (Fig. 1). The application is supported by a website that features a dedicated page for each country. Users can download the app on Google Play or App Store (Fig. 2).To allow the participation of non-experts, who generally are not familiar with taxonomy or species identification, the flower visitors are identified in general categories such as bumblebees and carpenter bees (grouped together), flies, and others (see Fig. 1), representing the main functional groups of pollinators. If a flower visitor cannot be identified, it should be classified as "other insect" or marked as "I don't know". Including the possibility of uncertainty in flower visitor identification was a suggestion of the Brazilian team for quality assurance during data collection.Currently, 834 flower visits have been counted by 15 participants, who performed 109 FIT Counts across Brazil as a pilot testing phase of the app. Two training workshops were held to disseminate the app, and an illustrated guide was published to help participants identify flower types and flower visitor groups (Koffler 2022). Nineteen plant species were monitored, but most flower-visits counted were on basil (Ocimum basillicum, n = 47) and false heather (Cuphea hyssopifolia, n = 33). The mean number of flower visitors per FIT Count was 8 (min = 0, max = 45). While most visits were performed by honeybees, participants also recorded visits by beetles, butterflies or moths, small insects, solitary bees, wasps and other insects. Next steps include assessing data quality and promoting strategic partnerships to further disseminate this citizen science initiative. For instance, quality control measures may include assessing whether participants perform the protocol steps according to instructions and whether plants and flower visitors are correctly identified and counted. Also, we are exploring the prospective implementation of the Darwin Core standard (Darwin Core Task Group 2009) along with the Plant-Pollinator Interactions vocabulary (Salim 2022) to standardize data description
Monitoreo de visitas florales mediante el Conteo Cronometrado de Visitantes Florales (FIT Count)
El Conteo Cronometrado de Visitantes Florales (de aquà en adelante denominado como FIT Count) es un sencillo protocolo de ciencia ciudadana que tiene como objetivo colectar datos sobre eventos de visita en flores por una amplia gama de polinizadores, incluyendo abejorros, abejas sin aguijón, abejas melÃferas, moscas y picaflores. Cada FIT Count está estandarizado a una duración de 10 minutos y se realiza en un parche floral determinado, usando un cuadrante de 50 x 50 cm. Dado que la polinización depende de las interacciones de los insectos (u otros visitantes florales) con las flores, es importante para un programa de ciencia ciudadana de largo plazo el poder evaluar cómo estas interacciones cambian en el tiempo y el espacio. El protocolo FIT Count nos permite afrontar este desafÃo mediante la obtención de datos de abundancia de visitantes florales en distintos hábitats y lugares. ¡También ofrece una excelente oportunidad de aprendizaje y de acercar a las personas a los polinizadores y las flores, dado que cualquier persona puede participar!Fil: Carvell, Claire. UK Centre for Ecology & Hydrology; Reino UnidoFil: Chiazzese, Jim. UK Centre for Ecology & Hydrology; Reino UnidoFil: Zattara, Eduardo Enrique. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Fontúrbel, Francisco E.. Pontificia Universidad Católica de ValparaÃso; ChileFil: Muschett Rivera, Giselle. Instituto de Ecologia y Biodiversidad; ChileFil: Pirani Ghilardi Lopes, Natalia. Universidad Federal Do Abc; BrasilFil: Miranda Soares, Filipi. Universidade de Sao Paulo; Brasi
Desdobramentos da Implementação da Rede GO FAIR Agro Brasil no Biênio 2021-2023
This work aims to present to the brazilian community the efforts and works developed in the 2021-2023 biennium for the implementation of the GO FAIR Agro Brasil Thematic Implementation Network. The inter-institutional actions undertaken are highlighted, as a means to promote the dissemination of knowledge about sharing and reuse of research data in agricultural sciences supported by the FAIR principles. As a result, the work shows the path taken so far and the new products built with broad participation from the communities of Agricultural Sciences and alike
Flower-insect timed counts (FIT Count): protocol adaptation and preliminary results in Brazil
FIT Count (Flower-Insect Timed Counts) is a citizen science initiative that seeks to monitor
flower visitation by diverse pollinator groups, including bumblebees, stingless bees,
honeybees, flies, hummingbirds, among others. The protocol entails determining a 50 x 50
cm plot area around a target plant species, photographing the plant and conducting a
standardized 10-minute survey on this area to estimate the frequency of flower visits by
different pollinator groups. Conducting FIT Counts in different habitats and locations
produces data on the temporal and spatial dynamics of these interactions
Unveiling Knowledge Organization Systems’ Artifacts for Digital Agriculture with Lexical Network Analysis
WorldFAIR (D10.3) Agricultural biodiversity FAIR data assessment rubrics
The WorldFAIR Case Study on Agricultural Biodiversity (WP10) addresses the challenges of advancing interoperability and mobilising plant-pollinator interactions data for reuse. Previous efforts, reported in WorldFAIR Deliverable 10.1, ‘Agriculture-related pollinator data standards use cases report’ (Trekels et al., 2023), provided an overview of projects, good practices, tools, and examples for creating, managing and sharing data related to plant-pollinator interactions. It also outlined a work plan for conducting pilot studies. Deliverable 10.2 (Drucker et al., 2024) presented Agricultural Biodiversity Standards, Best Practices and Guidelines Recommendations. This deliverable presented results from six pilot studies that adopted standards and recommendations from the earlier report. The current report complements the efforts with Agricultural Biodiversity FAIR data assessment rubrics.We introduce a set of FAIR assessment tools tailored to the plant-pollinator interactions domain. These tools are designed to help researchers and institutions evaluate adherence to the FAIR principles. In the discovery phase, we found that a significant amount of data on plant-pollinator interactions is available as supplementary files of research articles, in a diversity of formats such as PDFs, Excel spreadsheets, and text files. The diversity of approaches and the lack of appropriate data vocabularies lead to confusion, information loss, and the need for complex data interpretation and transformation. Our proposed framework primarily targets researchers in this domain who wish to assess the FAIRness of the data they produce and take action to improve it. However, we believe it can also benefit data reviewers, data stewards, data repository managers and librarians dealing with plant-pollinator data. Our approach focuses on being as familiar as possible with the researcher's practices, language, and jargon. Ultimately, we aim to promote data publishing and reuse in the plant-pollinator interactions domain.We present a ‘Rubric for the assessment of Plant-Pollinator Interactions Data’ with examples from the data from the pilots developed in Deliverable 10.2 and in relation to the FAIR Implementation Profile (FIP) created by Work Package 10. We conduct ‘dataset assessments’ of available data from research projects surveyed in the discovery phase. Additionally, we describe in detail the ‘Automated FAIR-enabled Data Reviews’ generated by the Global Biotic Interactions (GLoBI) infrastructure, with examples from the pilots. We believe the tools described in this report will encourage data publishing and reuse in the plant-pollinator interactions domain. Moving from diverse approaches and siloed initiatives to widely available FAIR plant-pollination interactions data for scientists and decision-makers will enable the development of integrative studies that enhance our understanding of species biology, behaviour, ecology, phenology, and evolution