Academic literature on the topic 'Occurrence data portal'

Over the last decade, the Symbiota open-source software has been readily available to establish occurrence-based data portals that represent the taxonomic and geographic expertise of a specific community of researchers. Reasons for establishing a data portal vary, but often focus on:data mobilization via the creation of public data access points (e.g., in-house search and export tools, Application Programming Interface (API) access, publication tools pushing data up to aggregators);tools and workflows that support active specimen digitization projectsa method for staging and preparing datasets for analysis to answer specific research questions (e.g., data assessment, correction, augmentation).The software functions as a Content Management System (CMS) allowing any dataset to be collaboratively augmented, modified, and managed online. Currently, the software provides support for over 1000 collection datasets to manage their specimen data directly within a Symbiota portal as a live managed dataset. Portals often include "snapshot" data imported from externally managed systems, which are updated on a regular schedule. Depending on the goals of a project, portals will vary in the composition of live to snapshot collections, though most contain a mixture of both. In this respect, data portals serve as intermediate aggregators, integrating multiple specimen datasets that collectively represent a community-based research perspective.Symbiota portals typically function as mid-level data aggregators that are community driven by a group of researchers with expertise within a specific taxonomic domain. This decentralized approach has been shown to promote the emergence of multiple regionally, taxonomically, or institutionally localized, self-identifying communities of practice<em>.</em> Each community is empowered to control the social and informational design and versioning of their local data infrastructures and signals. The upfront cost of decentralization is more than offset by the long-term benefit of achieving sustained expert engagement, higher-quality data products, and ultimately more societal impact for biodiversity data.In contrast to the vision of pushing data from the source to the global aggregators and ultimately out to the research community, Symbiota records are distributed across a growing array of sub-aggregators. For instance, Arizona State University Vascular Plant Herbarium's specimen data consist of a live managed dataset within SEINet with subsets of their data pushed out to the Portal de Biodiversidad de Guatemala and the Cooperative Taxonomic Resource for American Myrtaceae Symbiota portals as snapshot record sets. Not only does this support research associated with each of the portal communities, it exposes the records to researchers with local and taxonomic expertise to review, correct, and comment on the occurrence data. While the Symbiota portals provide tools for these communities to annotate the distributed snapshot records, the annotations need to be directed back to the source collection. Aside from the technical challenges, there are social negotiations that need to be considered. Collection managers might not want to integrate external edits, or the collection might be understaffed without anyone to approve the information transfer. Issues associated with "round-tripping" back to the source are complicated. Nevertheless, global coordination is feasible through automatable data sharing agreements that enable efficient propagation and translation of biodiversity data across communities.Within this presentation, we will explore ways specimen and annotation data have been shared across the Symbiota portal network, as well as the associated technical and social challenges we have encountered. We will also present recent enhancements in tracking project metadata, data provenance, record annotations, and the establishment of a public API architecture. These developments are leveraged to regulate machine-to-machine annotation propagation to enhance interoperability by providing support for real-time transmission of occurrence annotations across the distributed network of Symbiota portals. By demonstrating methods and challenges associated with data sharing across the Symbiota portal network, we strive to contribute to the global discussion of data sharing, but more importantly, solicit input and direction from the greater community on how we can improve data sharing beyond the Symbiota network.

Recognizing the abundance and the accumulation of information and data on biodiversity that are still poorly exploited and even unfunded, the REBIOMA project (Madagascar Biodiversity Networking), in collaboration with partners, has developed an online dataportal in order to provide easy access to information and critical data, to support conservation planning and the expansion of scientific and professional activities in Madagascar biodiversity. The mission of the REBIOMA data portal is to serve quality-labeled, up-to-date species occurrence data and environmental niche models for Madagascar's flora and fauna, both marine and terrestrial. REBIOMA is a project of the Wildlife Conservation Society Madagascar and the University of California, Berkeley. REBIOMA serves species occurrence data for marine and terrestrial regions of Madagascar. Following upload, data is automatically validated against a geographic mask and a taxonomic authority. Data providers can decide whether their data will be public, private, or shared only with selected collaborators. Data reviewers can add quality labels to individual records, allowing selection of data for modeling and conservation assessments according to quality. Portal users can query data in numerous ways. One of the key features of the REBIOMA web portal is its support for species distribution models, created from taxonomically valid and quality-reviewed occurrence data. Species distribution models are produced for species for which there are at least eight, reliably reviewed, non-duplicate (per grid cell) records. Maximum Entropy Modeling (MaxEnt for short) is used to produce continuous distribution models from these occurrence records and environmental data for different eras: past (1950), current (2000), and future (2080). The result is generally interpreted as a prediction of habitat suitability. Results for each model are available on the portal and ready for download as ASCII and HTML files. The REBIOMA Data Portal address is http://data.rebioma.net, or visit http://www.rebioma.net for more general information about the entire REBIOMA project.

Symbiota (Gries et al. 2014) is an open-source software platform designed to function as a biodiversity Content Management System (CMS) for specimen-based datasets. Primarily in North America though also increasingly on other continents, the Symbiota software platform has risen to prominence in the past ten years as one of the more heavily accessed mid-level aggregation tools for assembling, managing, and distributing datasets associated with biological collections. There are more than 50 public Symbiota portals being managed and promoted by various biodiversity projects and communities. Together, these portals assist in the distribution and mobilization of more than 55 million specimen and 20 million image records associated with hundreds of institutions.The central premise of a standard Symbiota installation is to function as a mini-aggregator capable of integrating multiple occurrence datasets that collectively represent a community-based research data perspective. Datasets are typically limited to geographic and taxonomic scopes that best represent the community of researchers leading the project. Symbiota portals often publish "snapshot records" that originate from external management systems but otherwise align with the portal's community of practice and data focus. Specimen management tools integrated into the Symbiota platform also support the ability to manage occurrence data directly within the portal as "live datasets". The software has become widely adopted as a data management platform. Approximately 550 specimen datasets consisting of more than 14 million specimen records are being directly managed within a portal instance. The appeal of Symbiota as an occurrence management tool is also exemplified by the fact that 18 of the 30 federally funded Thematic Collection Networks (https://www.idigbio.org/content/thematic-collections-networks) have elected to use Symbiota as their central data management system.Symbiota's well-developed data ingestion tools, coupled with the ability to store import profile definitions, allows data snapshots to be partially coordinated with source data managed within a variety of remote systems such as Specify (https://specifysoftware.org), EMu (https://emu.axiell.com), Integrated Publishing Toolkit (IPT, https://gbif.org/ipt) publishers, as well as other Symbiota instances. As with Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio) publishing models, data snapshots are periodically refreshed, based on transfer protocols compliant with Darwin Core (DwC) data exchange standards. The Symbiota data management tools provide the means for the community of experts running the portal to annotate and augment snapshot datasets with the goal of improving the overall fitness-for-use of the aggregated dataset. Even though a data refresh from the source dataset would effectively replace the data improvement with the original flawed data, the system's ability to maintain data versioning of all annotations made within the portal allows data improvements to be reapplied. However, inadequate support for bi-directional data flow between the portal and the source collection effectively isolates the annotations within the portal.On one hand, the mini-aggregator model of Symbiota can be viewed as compounding the further fragmentation of occurrence data. Rather than conforming to the vision of pushing data from the source, to the global aggregators and ultimately the research community, specimen data are being pushed from source collections to a growing array of mini-aggregators. On the other hand, community portals have the ability to incentivize experts and enthusiasts to publish high-quality, "data-intelligent" biodiversity data products with the potential of channeling data improvements back to the source.This presentation will begin with a historical review of the development of the Symbiota model including major shifts in the evolution of the development goals. We will discuss the benefits and shortcomings of the data model and provide a description of schema modifications that are currently in development. We will also discuss the successes and challenges associated with building data commons directly associated with communities of researchers. We will address the software's role in mobilizing occurrence data within North America and the efficacy of adhering to the FAIR use principles of making datasets findable, accessible, interoperable, and reusable (Wilkinson et al. 2016). Finally, we will discuss interoperability developments that we hope will improve the flow of data annotations between decentralized networks of data portals and the original data providers at the source.

AbstractThe transition from printed to online dictionaries demands a re-assessment of and adaptations to dictionary structures. This paper focuses on some aspects of the data distribution structure and the different search positions in dictionaries that can accommodate lexicographic data. It is shown that the traditional search positions should be increased. A dictionary as a whole can be regarded as a search region and a dictionary portal as a search domain. The emergence of dictionary portals compels lexicographers to expand the data distribution structure. The occurrence of dictionaries within a dictionary portal that contains different search regions necessitates the notion of a comprehensive data distribution structure. Further research is needed to investigate the interactive relation between a comprehensive data distribution structure and the access and mediostructure of a dictionary.

AbstractThe transition from printed to online dictionaries demands a re-assessment of and adaptations to dictionary structures. This paper focuses on some aspects of the data distribution structure and the different search positions in dictionaries that can accommodate lexicographic data. It is shown that the traditional search positions should be increased. A dictionary as a whole can be regarded as a search region and a dictionary portal as a search domain. The emergence of dictionary portals compels lexicographers to expand the data distribution structure. The occurrence of dictionaries within a dictionary portal that contains different search regions necessitates the notion of a comprehensive data distribution structure. Further research is needed to investigate the interactive relation between a comprehensive data distribution structure and the access and mediostructure of a dictionary.

GBIF Benin, hosted at the University of Abomey-Calavi, has published more than 338,000 occurrence records in 87 datasets and checklists. It has been a Global Biodiversity Information Facility (GBIF) node since 2004 and is a leader in several projects from the Biodiversity Information for Development (BID) programme. GBIF facilitates collaboration between nodes at different levels through its Capacity Enhancement Support Programme (CESP) [https://www.gbif.org/programme/82219/capacity-enhancement-support-programme]. One of the actions included in the CESP guidelines is called ‘Mentoring activities’. Its main goal is the transfer of knowledge between partners such as information, technologies, experience, and best practices. Sharing architecture and development is the key solution to solve some technical challenges or impediments (hosting, staff turnover, etc.) that GBIF nodes could face. The Atlas of Living Australia (ALA) team developed a functionality called ‘data hub’. It gives the possibility to create a standalone website with a dedicated occurrence search engine that seeks among a range of data (e.g. specific genus, geographic area). In 2017, GBIF Benin and GBIF France wanted to strengthen their partnership and started a CESP project. One of the core objectives of this project is the creation of the Atlas of Living Benin using ALA modules. GBIF France developers, with the help of the GBIF Benin team, are in the process of configuring a data hub that will give access to Beninese data only, while at the same time Atlas of Living France will give access to French data only. Both data portals will use the same back end, therefore the same databases. Benin is the first African GBIF node to implement this kind of infrastructure. On this poster, we will present the Atlas of Living Benin specific architecture and how we have managed to distinguish data coming from Benin and coming from France.

GBIF Benin, hosted at the University of Abomey-Calavi, has published more than 338,000 occurrence records in 87 datasets and checklists. It has been a Global Biodiversity Information Facility (GBIF) node since 2004 and is a leader in several projects from the Biodiversity Information for Development (BID) programme. GBIF facilitates collaboration between nodes at different levels through its Capacity Enhancement Support Programme (CESP) [<u>https://www.gbif.org/programme/82219/capacity-enhancement-support-programme</u>]. One of the actions included in the CESP guidelines is called 'Mentoring activities'. Its main goal is the transfer of knowledge between partners such as information, technologies, experience, and best practices. Sharing architecture and development is the key solution to solve some technical challenges or impediments (hosting, staff turnover, etc.) that GBIF nodes could face. The Atlas of Living Australia (ALA) team developed a functionality called 'data hub'. It gives the possibility to create a standalone website with a dedicated occurrence search engine that seeks among a range of data (e.g. specific genus, geographic area). In 2017, GBIF Benin and GBIF France wanted to strengthen their partnership and started a CESP project. One of the core objectives of this project is the creation of the Atlas of Living Benin using ALA modules. GBIF France developers, with the help of the GBIF Benin team, are in the process of configuring a data hub that will give access to Beninese data only, while at the same time Atlas of Living France will give access to French data only. Both data portals will use the same back end, therefore the same databases. Benin is the first African GBIF node to implement this kind of infrastructure. On this poster, we will present the Atlas of Living Benin specific architecture and how we have managed to distinguish data coming from Benin and coming from France.

Recognizing the abundance and the accumulation of information and data on biodiversity that are still poorly exploited and even unfunded, the REBIOMA project (Madagascar Biodiversity Networking), in collaboration with partners, has developed an online dataportal in order to provide easy access to information and critical data, to support conservation planning and the expansion of scientific and professional activities in Madagascar biodiversity. The mission of the REBIOMA data portal is to serve quality-labeled, up-to-date species occurrence data and environmental niche models for Madagascar’s flora and fauna, both marine and terrestrial. REBIOMA is a project of the Wildlife Conservation Society Madagascar and the University of California, Berkeley. REBIOMA serves species occurrence data for marine and terrestrial regions of Madagascar. Following upload, data is automatically validated against a geographic mask and a taxonomic authority. Data providers can decide whether their data will be public, private, or shared only with selected collaborators. Data reviewers can add quality labels to individual records, allowing selection of data for modeling and conservation assessments according to quality. Portal users can query data in numerous ways. One of the key features of the REBIOMA web portal is its support for species distribution models, created from taxonomically valid and quality-reviewed occurrence data. Species distribution models are produced for species for which there are at least eight, reliably reviewed, non-duplicate (per grid cell) records. Maximum Entropy Modeling (MaxEnt for short) is used to produce continuous distribution models from these occurrence records and environmental data for different eras: past (1950), current (2000), and future (2080). The result is generally interpreted as a prediction of habitat suitability. Results for each model are available on the portal and ready for download as ASCII and HTML files. The REBIOMA Data Portal address is http://data.rebioma.net, or visit http://www.rebioma.netfor more general information about the entire REBIOMA project.

Atlas of Living Australia (ALA) (https://www.ala.org.au/) is the Global Biodiversity Information Facility (GBIF) node of Australia. They developed an open and free platform for sharing and exploring biodiversity data. All the modules are publicly available for reuse and customization on their GitHub account (https://github.com/AtlasOfLivingAustralia). GBIF Benin, hosted at the University of Abomey-Calavi, has published more than 338 000 occurrence records from 87 datasets and 2 checklists. Through the GBIF Capacity Enhancement Support Programme (https://www.gbif.org/programme/82219/capacity-enhancement-support-programme), GBIF Benin, with the help of GBIF France, is in the process of deploying the Beninese data portal using the GBIF France back-end architecture. GBIF Benin is the first African country to implement this module of the ALA infrastructure. In this presentation, we will show you an overview of the registry and the occurrence search engine using the Beninese data portal. We will begin with the administration interface and how to manage metadata, then we will continue with the user interface of the registry and how you can find Beninese occurrences through the hub.

Atlas of Living Australia (ALA) (<u>https://www.ala.org.au/</u>) is the Global Biodiversity Information Facility (GBIF) node of Australia. They developed an open and free platform for sharing and exploring biodiversity data. All the modules are publicly available for reuse and customization on their GitHub account (<u>https://github.com/AtlasOfLivingAustralia</u>). GBIF Benin, hosted at the University of Abomey-Calavi, has published more than 338 000 occurrence records from 87 datasets and 2 checklists. Through the GBIF Capacity Enhancement Support Programme (<u>https://www.gbif.org/programme/82219/capacity-enhancement-support-programme</u>), GBIF Benin, with the help of GBIF France, is in the process of deploying the Beninese data portal using the GBIF France back-end architecture. GBIF Benin is the first African country to implement this module of the ALA infrastructure. In this presentation, we will show you an overview of the registry and the occurrence search engine using the Beninese data portal. We will begin with the administration interface and how to manage metadata, then we will continue with the user interface of the registry and how you can find Beninese occurrences through the hub.

Sturge-Weber syndrome is a rare disorder presenting with a capillary malformation, better known as a port-wine birthmark, on the upper face, glaucoma, and a leptomeningeal angioma. Most children develop seizures and strokes, with variable degrees of neurodevelopmental impairments including hemiparesis, visual field deficits, cognitive deficits, epilepsy, and migraines. In 2013, a somatic activating mutation in GNAQ was identified in the capillary malformations and leptomeningeal angiomas of Sturge-Weber patients. In the diagnosis of Sturge-Weber syndrome, contrast-enhanced imaging is essential to the diagnosis of brain involvement. Functional imaging has demonstrated impaired venous drainage and a role for seizures in exacerbating perfusion deficits. Aggressive seizure management is fundamental to treatment. Some data supports the use of low-dose aspirin to reduce the occurrence of strokelike episodes and seizures.

AbstractValuation studies have shown that drought occurrences have more severe economic impact compared to other natural disasters such as floods. In Kenya, drought has presented complex negative effects on farming communities. The main objective of this chapter is to analyze the economic impacts of drought and identify appropriate climate change adaptation measures in Kenya. To achieve this objective, an empirical approach, combined with secondary data mined from World Bank Climate Knowledge Portal and FAOSTAT databases, has been used in three main steps. First, historical links between population size and land degradation, temperature and rainfall changes with drought events were established. Second, economic impacts of drought on selected economic indicators such as quantities of staple food crop, average food value production, number of undernourished people, gross domestic product, agriculture value added growth, and renewable water resources per annum in Kenya were evaluated. Third, different climate change adaptation measures among farmers in Makueni county were identified using focused group discussions and in-depth interviews, for which the use of bottom-up approach was used to elicit responses. Findings from the binary logistic regression model show a statistical relationship between drought events and a selected set of economic indicators. More specifically, drought events have led to increased use of pesticides, reduced access to credit for agriculture and the annual growth of gross domestic product. One of the main recommendations of this chapter is to involve farmers in designing and implementing community-based climate change adaptation measures, with support from other relevant stakeholders.

The neoteric occurrence, the pandemic, and global crisis entails the extensive use of web portals to unfurl information. While this has built the cognizance of the common man, the infinitely unnoticed enumeration of malicious content on the web has escalated copiously. Spurious data and fake information has done more harm than what is actually unraveled to the public; however, scrupulously meticulous measures to agonize their source and delve into mitigating these data has become quite a challenge. This indignation delves into step-wise analysis of identifying the hoax through systematically programmed algorithms using natural language processing.

Introduction: Tension headache has become a major health problem for medical students. This can trigger a worsening in the quality of life of the student and hinder their learning, corroborating for an impaired education. Better understanding of the topic is necessary so the academics can have a better overview of the problem. Objective: Clarify the relationship between tension headache and the quality of life of medical students. Methods: Articles from the last ten years were selected on the Scielo and Google Scholar portal platforms, which made it possible through an online scenario. Results: The mechanisms of tension headache are controversial and their pathophysiology complex and poorly understood. In crises, analgesics, antiinflammatories, muscle relaxants and/or caffeine are applied. In the articles studied, epidemiological data suggest that most students (99%) have already had a headache case during their lifetime and such occurrences are related to moments of stress and tiredness (74%). It is visible, that the academic affected by various activities, is a target for the disease. Conclusion: The prevalence of tension headache in the medical student was higher than that of the general population, with stress as the main reason. then a resolution on the issue of pain regarding stress is necessary since it proved to be inappropriate.

Mobile applications that provide GPS-based route navigation advice or driver diagnostics are gaining popularity. However, these applications currently do not have knowledge of whether the driver is performing a lane change. Having such information may prove valuable to individual drivers (e.g., to provide more specific navigation instructions) or road authorities (e.g., knowledge of lane change hotspots may inform road design). The present study aimed to assess the accuracy of lane change recognition algorithms that rely solely on mobile GPS sensor input. Three trips on Dutch highways, totaling 158 km of driving, were performed while carrying two smartphones (Huawei P20, Samsung Galaxy S9), a GPS-equipped GoPro Max, and a USB GPS receiver (GlobalSat BU343-s4). The timestamps of all 215 lane changes were manually extracted from the forward-facing GoPro camera footage, and used as ground truth. After connecting the GPS trajectories to the road using Mapbox Map Matching API (2022), lane changes were identified based on the exceedance of a lateral translation threshold in set time windows. Different thresholds and window sizes were tested for their ability to discriminate between a pool of lane change segments and an equally-sized pool of no-lane-change segments. The overall accuracy of the lane-change classification was found to be 90%. The method appears promising for highway engineering and traffic behavior research that use floating car data, but there may be limited applicability to real-time advisory systems due to the occasional occurrence of false positives.

Birds are an important component of park ecosystems. Due to their high body temperature, rapid metabolism, and high ecological position in most food webs, birds are also good indicators of the effects of local and regional ecosystem changes. Patterns in the community composition, distribution, and occurrence of breeding birds provide a metric for assessing ecological integrity and sustainability in southeastern U. S. ecosystems. Further, trends in these attributes in relation to activities occurring at Cumberland Island National Seashore (e.g., management actions, natural disturbance, invasive-species treatment) will improve our understanding of the effects of various management actions and other stressors on the condition of seashore resources. This report summarizes data collected during implementation of the SECN landbird community monitoring protocol (Byrne et al. 2014) at Cumberland Island National Seashore in 2012. 1. Automated recording devices collected bird detection/ non-detection data (i.e., presence/absence) from 30 out of 31 spatially balanced random locations at the seashore. 2. Approximately 1,700 minutes of recordings were collected May–June, to represent a closed population, and were evaluated to detect the presence of vocalizing birds. 3. Fifty-five species of birds were detected during the sampling effort. 4. Northern cardinal, Carolina wren, white-eyed vireo, blue-gray gnatcatcher, northern parula, and tufted titmouse were the most frequently occurring and widely distributed species (i.e., occurring at 90% or more of all sampling locations). Yellow-throated warbler, redbellied woodpecker, and summer tanager were also widely distributed across the seashore, occurring at 80% or more of all sampling locations. 5. One non-native species, house finch, was detected during the sampling effort. 6. The full dataset, and associated metadata, can be acquired from the NPS data store at the Integrated Resource Management Applications portal (https:// irma.nps.gov/App/Portal/Home).

Birds are an important component of park ecosystems. Due to their high body temperature, rapid metabolism, and high ecological position in most food webs, birds are also good indicators of the effects of local and regional ecosystem changes. Patterns in the community composition, distribution, and occurrence of breeding birds provide a metric for assessing ecological integrity and sustainability in southeastern U.S. ecosystems. Further, trends in these attributes in relation to activities occurring at Fort Sumter National Monument (e.g., management actions, natural disturbance, invasive-species treatment) will improve our understanding of the effects of various management actions and other stressors on the condition of monument resources. This report summarizes data collected during implementation of the SECN landbird community monitoring protocol (Byrne et al. 2014) at Fort Sumter National Monument in 2012. 1. Automated recording devices collected bird detection/ non-detection data from four spatially balanced random locations within the monument. 2. Approximately 80 minutes of recordings were collected in May and June, to represent a closed population, and were evaluated to detect the presence of vocalizing birds. 3. Thirty-three species of birds were detected during the sampling effort. 4. Carolina wren, house finch, and northern cardinal were the most frequently occurring and widely distributed species (i.e., occurring at all sampling locations). Blue jay, brown thrasher, Carolina chickadee, chimney swift, fish crow, mourning dove, northern mockingbird, purple martin, and red-winged blackbird were also widely distributed across the monument, occurring at 75% of all sampling locations. 5. Two non-native species, house finch and house sparrow, were detected during the sampling effort. 6. Blue-gray gnatcatcher, great crested flycatcher, and orchard oriole represent new detections and will be added to the monument species list. 7. The full dataset, and associated metadata, can be acquired from the NPS data store at the Integrated Resource Management Applications portal (https://irma. nps.gov/App/Portal/Home).

The application of portable XRF spectrometry (pXRF) for determining concentrations of uranium (U), thorium (Th) and potassium (K) was evaluated using a combination of 12 Certified Reference Materials, 17 Standard Reference Materials, and 25 rock samples collected from areas of known U occurrences or mineralization. Samples were analysed by pXRF in Soil, Mining Cu/Zn and Mining Ta/Hf modes. Resulting pXRF data were compared to published recommended values, obtained by total or near total digestion methods with ICP-MS and ICP-OES analysis. Results for pXRF show a linear relationship, for thorium, potassium, and uranium (&amp;amp;lt;5000 ppm U) as compared to the recommended concentrations. However, above 5000 ppm U, pXRF results show an exponential relationship with under reporting of pXRF concentrations compared to recommended values. Accuracy of the data can be improved by post-analysis correction using linear regression equations for potassium and thorium, and samples with &amp;amp;lt;5000 ppm uranium; an exponential correction curve is required at &amp;amp;gt;5000 ppm U. In addition, pXRF analyses of samples with high concentrations of uranium (e.g. &amp;amp;gt;1 wt.% U) significantly over-estimated potassium contents as compared to the published values, indicating interference between the two elements not calibrated by the manufacturer software.