The Facet extension for CKAN enhances data discovery and visualization capabilities within a CKAN instance. Designed to address specific requirements, likely within a research or data-driven organization, it introduces custom facets and allows the integration of OpenStreetMap (OSM) visualizations to dataset pages. This extension enriches the user experience by providing more tailored search filters and spatial data representation. Key Features: Custom Facets: Enables the creation of bespoke facet filters. These facets are tailored to meet the specific needs for data discovery. OSM Map Integration: Displays geospatial data associated with datasets on an OpenStreetMap, allowing users to visually explore and understand the geographic distribution of the data. ISEBEL Requirements: The extension was explicitly developed considering the requirements of ISEBEL (specific user case), suggesting the capacity to accommodate other project requirements regarding its custom facets. Technical Integration: The Facet extension integrates with CKAN by enabling and declaring facet within plugin section of your production.ini configuration file. Benefits & Impact: Using the Facet extension will allow for better control over the data discovery process and improve comprehension of datasets with a spatial data representation through the use of the OSM map integration.

Unique values and counts of metadata facet fields.

What is a facet?

A facet is a metadata element, usually from a controlled list, that provides counts of records in a query result with particular values for the metadata element. The DataCite JSON Response includes data on a variety of facets for each query done using the DataCite API.

Repository Facets

DataCite Commons uses facets on repository pages to provide an overview of repositories. For example, the Metadata Game Changers Commons page shows publication year, work types, licenses, creators and contributors, and some other facets as graphics and lists.

The facets provided by DataCite can be used to 1) understand characteristics of DataCite metadata, 2) understand some aspects of repository completeness, and 3) provide overviews of repositories.

Using Facets to Understand DataCite Metadata

DataCite includes facets and facet values in all query results, so they are a useful tool for answering some "big picture" questions about DataCite metadata. Some of these questions were explored during 2022 in DataCite Facets: Understanding DataCite Usage using a tool called DataCite Facets.

DataCite Facets and Repository Overviews

DataCite facets can be used to provide overviews of any DataCite Repository and understand some characteristics of the repositories. They can also be used, in some cases, to provide insights into some aspects of repository completeness.

Repository Facets and Metadata Completeness

Many useful repository measures focus on completeness of the metadata, i.e., the portion of records in the repository that include some metadata element. The DataCite facet data can provide some insight into completeness, but we must keep in mind that the facet data are limited to top ten values for most facets (except for published and resourceTypes, which can be > 10). The blog DataCite Facets and Metadata Completeness describes how some facets can be used to provide insights into metadata completeness.

This dataset provides selected facets downloaded using the DataCite API and associated statistics as a comma-separated-value (CSV) file.

Column definitions:

The dataset includes a number of columns for the selected facets:

Unique values and counts of metadata facet fields.

Unique values and counts of metadata facet fields.

These data represent a land facet classification created for the Pacific Northwest Duke Landscape Resilience project.

Unique values and counts of metadata facet fields.

Unique values and counts of metadata facet fields.

Customs records of are available for BRILLIANT FACETS BV. Learn about its Importer, supply capabilities and the countries to which it supplies goods

Facets can provide an interesting functionality in digital libraries. However, while some research shows facets are important, other research found facets are only moderately used. Therefore, in this exploratory study we compare two search interfaces; one where the facets panel is always visible and one where the facets panel is hidden by default. Our main research question is “Is folding the facets panel in a digital library search interface beneficial to academic users?” By performing an eye tracking study with N=24, we measured search efficiency, distribution of attention and user satisfaction. We found no significant differences in the eye tracking data nor in usability feedback and conclude that collapsing facets is neither beneficial nor detrimental.

This dataset contains the eye tracking data and user satisfaction data.

Unique values and counts of metadata facet fields.

Unique values and counts of metadata facet fields.

Facets Jewels Llc Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Unique values and counts of metadata facet fields.

Unique values and counts of metadata facet fields.

Utility dataset for visualisation pages of the data.orleans-metropole.fr portal

Research type facets and contribution type facets.

Note: Pasture and hay budgets added on 2023/02/09 Enterprise budgets contained in this database were developed as part of the Floridian Aquifer Collaborative Engagement for Sustainability (FACETS), a large-scale, multi-institutional, multi-disciplinary project funded by the United States Department of Agriculture (USDA) National Institute of Food and Agriculture (NIFA). The goal of this project is to promote the economic sustainability of agriculture and silviculture in North Florida and South Georgia while protecting water quantity, quality, and habitat in the Upper Floridan Aquifer and the springs and rivers it feeds. As part of the larger FACETS project, budgets were developed for various cropping and forest systems in North Florida and South Georgia. This dataset includes budgets developed for pine plantations, corn and peanut crops, and hay and pasture production in the Lower Suwannee River Basin, Florida. Preliminary budgets were created based on information obtained from semi-structured interviews with producers, suppliers, local businesses, and area extension professionals. Following the construction of the preliminary budget, the project team conducted a review, along with a project advisory committee of stakeholders from agricultural, environmental, regulatory, and scientific partner organizations to confirm and/or adjust any data reported. Any specific information that was derived outside of, or in addition to, the process noted above is shown in summary on the second worksheet in this workbook, titled "Meta Data."
Upon finalization of the preliminary budget, enterprise-level models were developed to predict the impacts of Best Management Practice (BMP) adoption on the financial viability of enterprises under various alternative scenarios (Management Systems). The budgets for these Management Systems represent adjustments to management practices. Summary descriptions of each of these management systems are located on the worksheet titled "Management System Descriptions."
See file list for descriptions of each data file. Resources in this dataset:Resource Title: FACETS Corn enterprise budgets. File Name: FACETS_CornBudget.xlsxResource Title: FACETS Forest enterprise budgets. File Name: FACETS_ForestBudget.xlsxResource Title: FACETS Peanut enterprise budgets. File Name: FACETS_PeanutBudget.xlsxResource Title: FACETS Hay enterprise budgets. File Name: FACETS_HayBudget.xlsxResource Title: FACETS Pasture enterprise budgets. File Name: FACETS_PastureBudgets.xlsxResource Title: README file list. File Name: file_list_FACETS_budgets.txt

Vegetation responses to experimental ecological restoration treatments at Tyson Research Centre of Washington University in Missouri, USA. These data include species-level cover responses to various factorial restoration treatments. Treatments were applied starting in 2009 and were measured in 2016. Treatment responses reflect these long term responses, but the dataset is comprised to one time point.

Customs records of Undisclo are available for FACETS JEWELS. Learn about its Importer, supply capabilities and the countries to which it supplies goods