The datasets provided encompass all the statistics found on the Canadian Cluster Map Portal. Moreover, additional information such as cluster-concordance and cluster descriptions are provided to allow for accurate analysis of the data.

K=7 cluster map based on N=13 participants.

Collection description

K-means cluster maps of orbitofrontal cortex with K=2, 3, 4, 5, 6, and 7 clusters based on resting-state fMRI data.

Subject species

homo sapiens

Modality

fMRI-BOLD

Analysis level

group

Cognitive paradigm (task)

rest eyes open

Map type

R

World cluster map of the world based on a Coastal zone (LOICZ) database received in 1995 from the Netherlands Institute for Sea Research (NIOZ).

Cluster Maps

This interactive map shows the spatial distribution of hydrochemical data across Southcentral Alaska using K-Means clustering. The dataset includes key hydrochemical measurements, and each cluster is represented by a unique color on the map. The map is generated using Leaflet and Folium libraries in Python.The static version is available in the main manuscript, while this HTML file provides a dynamic exploration of clustering results.Contact: Abhinav Choudhary (Chandigarh University, MSc Data Science)Date of creation: 2025-01-11

The datasets provided encompass all the statistics found on the Canadian Cluster Map Portal. Moreover, additional information such as cluster-concordance and cluster descriptions are provided to allow for accurate analysis of the data.

A database of geologic map of Three Sisters Volcanic Cluster as described in the original abstract: The geologic map represents part of a late Quaternary volcanic field within which scores of eruptions have taken place over the last 50,000 years, some as recently as ~1,500 years ago. No rocks of early Pleistocene (or greater) age crop out within the map area, although volcanic and derivative sedimentary rocks of Miocene and Pliocene age are widespread to the east and west and are certainly buried beneath the younger volcanic field. Of the 145 volcanic map units described herein, only 22 are certainly older than late Pleistocene (>126 ka), and 12 are postglacial (<15 ka). The oldest unit identified yields an age of 532+/-7 ka, and the second oldest, 374+/-6 ka. Compositionally, 10 percent of the units are true basalt; 36 percent, basaltic andesite; 20 percent, andesite; 21.5 percent, dacite; and only 12.5 percent, rhyodacite or rhyolite. Most of the 145 volcanic map unit ...

This data set describes Neighborhood Clusters that have been used for community planning and related purposes in the District of Columbia for many years. It does not represent boundaries of District of Columbia neighborhoods. Cluster boundaries were established in the early 2000s based on the professional judgment of the staff of the Office of Planning as reasonably descriptive units of the City for planning purposes. Once created, these boundaries have been maintained unchanged to facilitate comparisons over time, and have been used by many city agencies and outside analysts for this purpose. (The exception is that 7 “additional” areas were added to fill the gaps in the original dataset, which omitted areas without significant neighborhood character such as Rock Creek Park, the National Mall, and the Naval Observatory.) The District of Columbia does not have official neighborhood boundaries. The Office of Planning provides a separate data layer containing Neighborhood Labels that it uses to place neighborhood names on its maps. No formal set of standards describes which neighborhoods are included in that dataset.Whereas neighborhood boundaries can be subjective and fluid over time, these Neighborhood Clusters represent a stable set of boundaries that can be used to describe conditions within the District of Columbia over time.

Groups of geographically defined attendance areas. They include elementary and middle-level schools that feed into particular high schools and consortium schools.For further details: https://www2.montgomeryschoolsmd.org/departments/Clusteradmin/Clusters/indexFor more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620

Collection description

Subject species

homo sapiens

Map type

Other

This set of files was generated using the script demonstrating the use of MINERVA Net repository.

The script is available under:

https://gitlab.lcsb.uni.lu/minerva/api-scripts/-/blob/master/R/API-minervanet.R

The diagrams should be opened with the CellDesigner software (https://www.celldesigner.org/).

Map that mimics the geometry of 'fully developed slopes'.

This dataset is a series of digital map-posters accompanying the AdaptNRM Guide: Implications of Climate Change for Biodiversity: a community-level modelling approach.

These represent supporting materials and information about the community-level biodiversity models applied to climate change. Map posters are organised by four biological groups (vascular plants, mammals, reptiles and amphibians), two climate change scenario (1990-2050 MIROC5 and CanESM2 for RCP8.5), and six measures of change in biodiversity.

The map-posters present the nationally consistent data at locally relevant resolutions in eight parts – representing broad groupings of NRM regions based on the cluster boundaries for the NRM fund (http://www.climatechange.gov.au/reducing-carbon/land-sector-measures/nrm-fund/stream-2) and also Nationally.

Map-posters are provided in PNG image format at moderate resolution (300dpi) to suit A0 printing as well as in PDF format to suit initial printing. The posters were designed to meet A0 print size and digital viewing resolution. An additional set in PDF image format has been created for ease of download for initial exploration and printing on A3 paper. Some text elements and map features may be fuzzy at this lower resolution.

Each map-poster contains four dataset images coloured using standard legends encompassing the potential range in ecological similarity (from 0 to 1), even if that range is not represented in the dataset itself or across the map extent.

Each map series is provided in two parts: part 1 shows the two climate scenarios for vascular plants and mammals and part 2 shows reptiles and amphibians. Eight cluster maps for each series have a different colour theme and map extent. A national series is also provided. Annotation briefly outlines the topics presented in the Guide so that each poster stands alone for quick reference.

Example citation: Williams KJ, Raisbeck-Brown N, Harwood T, Prober S (2014) Novel ecological environments for vascular plants and mammals (1990-2050), A0 map-poster 3.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

This dataset has been delivered incrementally. All maps are now available, some that were previously available may have been updated. Please check that you are accessing the latest version of the dataset. Lineage: The map posters show case the scientific data. The data layers have been developed at approximately 250m resolution (9 second) across the Australian continent to incorporate the interaction between climate and topography, and are best viewed using a geographic information system (GIS). Each data layers is 1Gb, and inaccessible to non-GIS users. The map posters provide easy access to the scientific data, enabling the outputs to be viewed at high resolution with geographical context information provided.

Maps were generated using layout and drawing tools in ArcGIS 10.2.2

A check list of map posters and datasets is provided with the collection.

Map Series: 1.1 Potential degree of ecological change for vascular plants and mammals (1990-2050) 1.2 Potential degree of ecological change for reptiles and amphibians (1990-2050) 2.1 Disappearing ecological environments for vascular plants and mammals (1990-2050) 2.2 Disappearing ecological environments for reptiles and amphibians (1990-2050) 3.1 Novel ecological environments for vascular plants and mammals (1990-2050) 3.2 Novel ecological environments for reptiles and amphibians (1990-2050) 4.1 Change in effective area of similar ecological environments (intact) for vascular plants and mammals (1990-2050) 4.2 Change in effective area of similar ecological environments (intact) for reptiles and amphibians (1990-2050) 5.1 Change in effective area of similar ecological environments (cleared) for vascular plants and mammals (1990-2050) 5.2 Change in effective area of similar ecological environments (cleared) for reptiles and amphibians (1990-2050) 6.1 Composite ecological change for vascular plants and mammals (1990-2050) 6.2 Composite ecological change for reptiles and amphibians (1990-2050)

MCPS Cluster Service Areas

Self Organizing Map Syntax and Data

The advancement of techniques to visualize and analyze large-scale sequencing datasets is an area of active research and is rooted in traditional techniques such as heat maps and dendrograms. We introduce dendritic heat maps that display heat map results over aligned DNA sequence clusters for a range of clustering cutoffs. Dendritic heat maps aid in visualizing the effects of group differences on clustering hierarchy and relative abundance of sampled sequences. Here, we artificially generate two separate datasets with simplified mutation and population growth procedures with GC content group separation to use as example phenotypes. In this work, we use the term phenotype to represent any feature by which groups can be separated. These sequences were clustered in a fractional identity range of 0.75 to 1.0 using agglomerative minimum-, maximum-, and average-linkage algorithms, as well as a divisive centroid-based algorithm. We demonstrate that dendritic heat maps give freedom to scrutinize specific clustering levels across a range of cutoffs, track changes in phenotype inequity across multiple levels of sequence clustering specificity, and easily visualize how deeply rooted changes in phenotype inequity are in a dataset. As genotypes diverge in sample populations, clusters are shown to break apart into smaller clusters at higher identity cutoff levels, similar to a dendrogram. Phenotype divergence, which is shown as a heat map of relative abundance bin response, may or may not follow genotype divergences. This joined view highlights the relationship between genotype and phenotype divergence for treatment groups. We discuss the minimum-, maximum-, average-, and centroid-linkage algorithm approaches to building dendritic heat maps and make a case for the divisive “top-down” centroid-based clustering methodology as being the best option visualize the effects of changing factors on clustering hierarchy and relative abundance.

Building permit records in the City of Montgomery.

The top locations where reported collisions occurred between bicyclists and motor vehicles have been identified. The crash cluster analysis methodology for the top bicyclist clusters uses a fixed meter search distance of 100 meters (328 ft.) to merge crash clusters together. Located crashes between motor vehicles and bicyclists were identified by using the non-motorist type code within the CDS database (which may yield different results from using most harmful event, first harmful event, or sequence of events data fields). Furthermore, the methodology uses the Equivalent Property Damage Only (EPDO) weighting to rank the clusters. However, because of the relatively small number of reported bicyclists crashes in the crash data file, the clustering analysis used crashes from the ten year period from 2010-2019. Additionally, due to the larger geographic area encompassed by the bicyclist crash clusters, it was difficult to name them so they were left unnamed but can be viewed spatially.

PLEASE NOTE: this dataset has been retired. It has been superseded by data for Flood Risk Areas: https://environment.data.gov.uk/dataset/f3d63ec5-a21a-49fb-803a-0fa0fb7238b6

The Indicative Flood Risk Areas are primarily based on an aggregated 1km square grid Updated Flood Map for Surface Water (1 in 100 and 1000 annual probability rainfall), informally referred to as the “blue square map”.

• Cluster Maps – are aggregations of 3km by 3km squares that each contain at least 4 (in Wales) or 5 (in England) touching "blue squares" (i.e. 1km grid squares where one of the thresholds above is exceeded)

This dataset forms part of Indicative Flood Risk Areas (shapefiles)

A bundle download of all Indicative Flood Risk Areas spatial datasets is also available from this record. Please see individual records for full details and metadata on each product. Attribution statement: © Environment Agency copyright and/or database right 2016. All rights reserved.

The top locations where reported collisions occurred at intersections have been identified. The crash cluster analysis methodology for the top intersection clusters uses a fixed meter search distance of 25 meters (82 ft.) to merge crash clusters together. This analysis was based on crashes where a police officer specified one of the following junction types: Four way intersection, T-intersection, Y-intersection, five point or more. Furthermore, the methodology uses the Equivalent Property Damage Only (EPDO) weighting to rank the clusters. EPDO is based any type of injury crash (including fatal, incapacitating, non-incapacitating and possible) having a weighting of 21 compared to a property damage only crash (which has weighting of 1). The clustering analysis used crashes from the three year period from 2019-2021. The area encompassing the crash cluster may cover a larger area than just the intersection so it is critical to view these spatially.