The Q-Herilearn scale is a probabilistic scale of summative estimates that measures different aspects of the learning process in Heritage Education. It consists of seven factors (Knowing, Understanding, Respecting, Valuing, Caring, Enjoying and Transmitting). Each dimension is measured by means of seven indicators scored on a 4-point frequency response scale (1 = Never or almost never; 2 = Sometimes; 3 = Quite often; 4 = Always or almost always). Sufficient evidence of content validity has been obtained through a concordance analysis —which employed multi-facet logistic models (Many Facet Rasch Model MFRM)— of the scores of 40 judges, who estimated the relevance, adequacy, and clarity of each item. The metric properties of the scores were determined using ESEM —Exploratory Structural Equation Modeling—, EGA Exploratory Graph Analysis and Network Analysis. The scale was calibrated using Item Response Theory models: the Nominal Response Model and the Graded Response Model.

The Atlas of Canada National Scale Data 1:5,000,000 Series consists of boundary, coast, island, place name, railway, river, road, road ferry and waterbody data sets that were compiled to be used for atlas medium scale (1:5,000,000 to 1:15,000,000) mapping. These data sets have been integrated so that their relative positions are cartographically correct. Any data outside of Canada included in the data sets is strictly to complete the context of the data.

Asia Pacific Hyper-scale Data Center market USD 32544.7 million in 2024 and will grow at a compound annual growth rate (CAGR) of 8.2% from 2024 to 2031. Expanding IT infrastructure and growing presence of major players is expected to aid the sales to USD 55207.4 million by 2031

Les écailles ont été prélevées sur le saumon dans l'océan Pacifique Nord-Est et analysées pour obtenir des informations sur l'âge. Ces données ont été recueillies dans le cadre de l'expédition en haute mer du golfe d'Alaska de l'Année internationale du saumon (IYS) menée en février et mars 2019, afin d'améliorer encore la compréhension des facteurs ayant une incidence sur la survie hivernale du saumon en début de mer.

The global Truck Scale Data Management Software market is experiencing robust growth, driven by the increasing need for efficient and accurate weighing data in various industries. The market, valued at approximately $250 million in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This growth is fueled by several key factors. The rising adoption of cloud-based solutions offers scalability and accessibility, reducing infrastructure costs and improving data management capabilities. Furthermore, stringent regulatory compliance requirements across sectors like transportation and waste management are compelling businesses to invest in sophisticated weighing systems integrated with robust data management software. The increasing demand for real-time data analytics for optimized logistics and improved operational efficiency further fuels market expansion. Specific industry verticals, such as mining, heavy industry, and agriculture, are showing particularly strong adoption rates due to their dependence on precise weight measurements for inventory control, production planning, and billing accuracy. The integration of IoT sensors and advanced analytics capabilities is transforming truck scale data management, enabling predictive maintenance and proactive problem-solving. Market segmentation reveals significant opportunities in various application areas. Cloud-based solutions dominate the market due to their inherent advantages, though on-premise deployments retain a significant presence, particularly in industries with stringent data security concerns. Geographically, North America and Europe currently hold a substantial market share, driven by early adoption and established regulatory frameworks. However, emerging economies in Asia-Pacific are projected to witness significant growth due to increasing industrialization and infrastructure development. The competitive landscape features both established players like Mettler Toledo and Rice Lake Weighing Systems, along with emerging technology providers, leading to increased innovation and a wider range of solutions tailored to specific industry needs. The market's future trajectory remains positive, driven by technological advancements, regulatory pressures, and the continuous demand for enhanced operational efficiency across diverse sectors.

This dataset is about books and is filtered where the book is Data just right : introduction to large-scale data & analytics, featuring 7 columns including author, BNB id, book, book publisher, and ISBN. The preview is ordered by publication date (descending).

The Atlas of Canada National Scale Data 1:1,000,000 Series consists of boundary, coast, island, place name, railway, river, road, road ferry and waterbody data sets that were compiled to be used for atlas large scale (1:1,000,000 to 1:4,000,000) mapping. These data sets have been integrated so that their relative positions are cartographically correct. Any data outside of Canada included in the data sets is strictly to complete the context of the data.

Les écailles ont été prélevées sur le saumon dans l'océan Pacifique Nord-Est et analysées pour obtenir des informations sur l'âge. Ces données ont été recueillies dans le cadre de l'expédition en haute mer du golfe d'Alaska de l'Année internationale du saumon (IYS) menée en mars et avril 2020, afin d'améliorer encore la compréhension des facteurs ayant une incidence sur la survie hivernale du saumon en début de mer.

Genomics is narrowing uncertainty in the phylogenetic structure for many amniote groups. For one of the most diverse and species-rich groups, the squamate reptiles (lizards and snakes, amphisbaenians), an inverse correlation between the number of taxa and loci sampled still persists across all publications using DNA sequence data and reaching a consensus on the relationships among them has been highly problematic. Here, we use high-throughput sequence data from 289 samples covering 75 families of squamates to address phylogenetic affinities, estimate divergence times, and characterize residual topological uncertainty in the presence of genome scale data. Importantly, we address genomic support for the traditional taxonomic groupings Scleroglossa and Macrostomata using novel machine-learning techniques. We interrogate genes using various metrics inherent to these loci, including parsimony-informative sites, phylogenetic informativeness, length, gaps, number of substitutions, and site concordance to understand why certain loci fail to find previously well-supported molecular clades and how they fail to support species-tree estimates. We show that both incomplete lineage sorting and poor gene-tree estimation (due to a few undesirable gene properties, such as an insufficient number of parsimony informative sites), may account for most gene and species-tree discordance. We find overwhelming signal for Toxicofera, and also show that none of the loci included in this study supports Scleroglossa or Macrostomata. We comment on the origins and diversification of Squamata throughout the Mesozoic and underscore remaining uncertainties that persist in both deeper parts of the tree (e.g., relationships between Dibamia, Gekkota, and remaining squamates; and between the three toxiferan clades Iguania, Serpentes, and Anguiformes) and within specific clades (e.g., affinities among gekkotan, pleurodont iguanians, and colubroid families).

The Atlas of Canada National Scale Data 1:15,000,000 Series consists of boundary, coast and coastal islands, place name, railway, river, road, road ferry and waterbody data sets that were compiled to be used for atlas small scale (1:15,000,000 and 1:30,000,000) mapping. These data sets have been integrated so that their relative positions are cartographically correct. Any data outside of Canada included in the data sets is strictly to complete the context of the data.

This data set includes isotope and depth age data, and CO2 and CH4 data from the Dome C Antarctica ice core. This core is a 906 meter core that spans approximately 32,000 years. It was a thermally drilled core and was retrieved during the 1977-78 Antarctic field season as part of the International Antarctic Glaciological project.

This map image depicts a summary of the Australian 1:1 million scale digital geology dataset. The map image is designed for plotting at 1:5 million scale on A0 sized paper.

This dataset is about book subjects and is filtered where the books includes Data just right : introduction to large-scale data & analytics, featuring 10 columns including authors, average publication date, book publishers, book subject, and books. The preview is ordered by number of books (descending).

This dataset contains digitized scale measurement data from sockeye salmon scales taken in Alaska. The locations where scales were sampled are the Copper River, Coghill River, Egegik River, and Hugh Smith Lake. Salmon scales are aged by examining growth annuli on the scale. Sockeye salmon typically spend one to two winters in fresh water, and one to three winters in the ocean prior to returning to freshwater to spawn. Growth during summer months is rapid, and increases the size of the scale by widely spaced circular rings (circuli). Slow growth during winter months leads to more narrowly spaced circuli. In this dataset, measurements are presented as the length (in millimeters) between each circuli. Accompanying these individual measurements is the established age of the fish (in European notation, where a 13 would be 1 year in fresh water and 3 in the ocean), the sex of the fish, and the length of the fish. Included in this dataset are the original excel files for each aged stock, an Rmarkdown document which reformats and merges these files, and a csv file of all of the data contained within the excel files. The included PDF document details the methods for measuring annuli more clearly.

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Paleoceanography. The data include parameters of paleoceanography with a geographic location of North Atlantic Ocean. The time period coverage is from 14952 to 426 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

This data package includes all the Australian state and territory 1:1,000,000 scale surface geology digital datasets. For further information, see the following product catalog numbers:

New South Wales - 65529 Northern Territory - 65048 Queensland - 65530 South Australia - 65199 Tasmania - 65531 Victoria - 65532 Western Australia - 65829

The Annual Minimum Snow and Ice (MSI) Extent of the Atlas of Canada National Scale Data, are data sets compiled containing annual data from 2000 to present. The data sets were derived from research published by the Canada Centre for Remote Sensing which classified satellite imagery over Canada and neighbouring regions for the continued presence or absence of snow and ice from April 1 to September 20 each year. The Atlas of Canada MSI products consist of a vector dataset and a raster time-series animation application.

VECTOR DATASET

The vector dataset has been generalized to display at the scale of 1:1,000,000.

TIME-SERIES ANIMATION APPLICATION

The time-series animation application has not been generalized from its original scale (250 m pixels).

The application is disseminated through the Data Cube Platform, implemented by the Canada Centre for Mapping and Earth Observation, Natural Resources Canada using geospatial big data management techniques. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The time-series is also available as a Web Map Service (WMS) and Web Coverage Service (WCS).

CREDIT

Source data provided by Alexander P. Trishchenko, Canada Centre for Remote Sensing, Natural Resources Canada

Metadata record: https://open.canada.ca/data/en/dataset/808b84a1-6356-4103-a8e9-db46d5c20fcf

This dataset is about book series and is filtered where the books is Data just right : introduction to large-scale data & analytics. It has 10 columns such as book series, earliest publication date, latest publication date, average publication date, and number of authors. The data is ordered by earliest publication date (descending).

The Atlas of Canada National Scale Data 1:15,000,000 Series consists of boundary, coast and coastal islands, place name, railway, river, road, road ferry and waterbody data sets that were compiled to be used for atlas small scale (1:15,000,000 and 1:30,000,000) mapping. These data sets have been integrated so that their relative positions are cartographically correct. Any data outside of Canada included in the data sets is strictly to complete the context of the data.

Node set definitions.