The data set contains fields from Lower Saxony and Bremen, which were transformed into the INSPIRE data model "land use". Fields are contiguous, agriculturally used areas that are managed by a producer and cultivated with one type of fruit or are completely set aside. The data is updated three times a year: at the end of the application phase, after the main overlap cleanup and when the main payment is made.

BEAT COVID Viral Ct

BEAT COVID Info LUMC

BEAT COVID Viral Ct: Research laboratory data of LUMC BEAT COVID cohort. Prospective observational WMO study including 191 COVID-19 patients from April 2020 to March 2021. Over 400 different laboratory variables were measured, listed in the attached tables. Principle Investigator, Anna Roukens, LUCID. Website: https://w3id.org/lumc/lucid/beatcovid_viralct

The googleanalyticsbasic extension for CKAN provides a simple way to integrate Google Analytics tracking into your CKAN-based data catalog. It injects the Google Analytics asynchronous tracking code into the page headers of your CKAN site, enabling basic page view tracking. This allows you to monitor site traffic and user behavior via the Google Analytics dashboard and therefore gain insights into how users interact with your data portal. This extension is compatible with CKAN versions 2.9 and 2.10. Key Features: Easy Google Analytics Integration: Simplifies the process of adding Google Analytics tracking to a CKAN site. You do not need to edit templates or write complex code, as the extension handles the injection of the tracking code. Asynchronous Tracking: Uses the asynchronous Google Analytics tracking code, which is designed to minimize any potential impact on page load times. Configuration via INI File: Enables the setting of Google Analytics tracking IDs via the CKAN configuration file (development.ini or similar). The extension uses a space-separated list of these google ids. Basic Page Tracking: Provides standard page view tracking functionality within Google Analytics. This is suited to monitoring how many hits each CKAN page receives and gives you an overview of site engagement. Compatibility: Supports CKAN versions 2.9 and 2.10. Use Cases: Usage Monitoring: Administrators can track essential metrics such as page views and user visits. Effectiveness Assessment: Evaluating the performance of data portals over time is improved with analytical insights. Informed Decisions: Providing data-driven basis for decisions, such as the prioritization of new features. Technical Integration: The googleanalyticsbasic extension integrates with CKAN by adding the required HTML to CKAN's pages using CKAN's plugin system. You need to activate the plugin in your CKAN configuration file and specify the Google Analytics tracking IDs you want to use. The extension then automatically inserts the tracking code into the appropriate sections of your CKAN pages. This is a simple process that requires no modification of the CKAN core code or installed template files. Benefits & Impact: By implementing the googleanalyticsbasic extension, CKAN site administrators can effortlessly monitor website traffic and user behaviour. This understanding can refine data portal content, improve site usability, and ultimately drive greater data accessibility and user engagement. This monitoring leads to better content development and resource prioritisation across the CKAN catalog.

This dataset comprises road centerlines for all roads in San Diego County. Road centerline information is collected from recorded documents (subdivision and parcel maps) and information provided by local jurisidictions (Cities in San Diego County, County of San Diego). Road names and address ranges are as designated by the official address coordinator for each jurisidcition. Jurisdictional information is created from spatial overlays with other data layers (e.g. Jurisdiction, Census Tract).The layer contains both public and private roads. Not all roads are shown on official, recorded documents. Centerlines may be included for dedicated public roads even if they have not been constructed. Public road names are the official names as maintained by the addressing authority for the jurisdiction in which the road is located. Official road names may not match the common or local name used to identify the road (e.g. State Route 94 is the official name of certain road segments commonly referred to as Campo Road).Private roads are either named or unnamed. Named private roads are as shown on official recorded documents or as directed by the addressing authority for the jurisdiction in which the road is located. Unnamed private roads are included where requested by the local jurisidiction or by SanGIS JPA members (primarily emergency response dispatch agencies). Roads are comprised of road segments that are individually identified by a unique, and persistent, ID (ROADSEGID). Roads segments are terminated where they intersect with each other, at jurisdictional boundaries (i.e. city limits), certain census tract and law beat boundaries, at locations where road names change, and at other locations as required by SanGIS JPA members. Each road segment terminates at an intersection point that can be found in the ROADS_INTERSECTION layer.Road centerlines do not necessarily follow the centerline of dedicated rights-of-way (ROW). Centerlines are adjusted as needed to fit the actual, constructed roadway. However, many road centerline segments are created intially based on record documents prior to construction and may not have been updated to meet as-built locations. Please notify SanGIS if the actual location differs from that shown. See the SanGIS website for contact information and reporting problems (http://www.sangis.org/contact/problem.html).Note, the road speeds in this layer are based on road segment class and were published as part of an agreement between San Diego Fire-Rescue, the San Diego County Sheriff's Department, and SanGIS. The average speed is based on heavy fire vehicles and may not represent the posted speed limit.

The Belgian Coccinellidae dataset which is published, is the result of a merge of 4 datasets. The INBO (Research Institute for Nature and Forest; Flemish Region Database), the DFF database (The Walloon Region Database), Observations.be data provided by Natagora (The Walloon Region and Brussels Capital Region) and the Walloon Region Online Encoding Tool (DEMNA - OFFH, observatoire.biodiversite.wallonie.be/encodage) data. At present, the database contains about 80.000 records, of which 15% come from museum collections and literature data. Collection events minimally consist of species, number of individuals, stage (adults, larvae and pupae), observation date, observer and location. Original locations as well as collection material were attributed to 1x1 km or 5x5 km grid cells of the UTM grid (Universal Transverse Mercator). A large part of the Belgian territory has been surveyed for ladybird beetles: the database contains records for at least 85% of all 5x5km UTM grid cells (N = 1376) in Belgium. Additionally, data on substratum plants, height in the vegetation, sampling method, habitat type, surrounding landscape, slope orientation, soil type, humidity, vegetation cover and behaviour were noted. In 1999, the Belgian Ladybird Working Group Coccinula launched a large scale field survey on 40 native ladybird species (Coccinellinae, Chilocorinae and Epilachninae) and to date has more than 500 volunteers providing distribution data. They actively search for ladybird beetles in a variety of habitats using sweep nets, beating trays, visual search, light trapping, pitfall traps and other sampling methods. Distribution, habitat and substrate plant information is also noted on a standard recording form. The working group maintains a database of observations, literature and collection data of Coccinellidae from 1800 onwards. Preliminary atlases have been published for the whole Belgian territory (Branquart et al., 1999; Adriaens and Maes, 2004) and updated distribution maps are available online, on demand and through the working group's newsletter. The published dataset contains most of the data maintained by the working group. For the time being, only the original INBO database is published.

BEAT COVID Lab results LUMC

BEAT COVID Severity Score LUMC