Chart Viewer allows app viewers to explore your map beside charts related to your data. App authors can display multiple data-based graphics configured in Map Viewer to compliment information in the map. Up to ten charts can be included in the app and each can be viewed alongside your map or side by side with other charts for comparison.Examples:Present a bar chart representing average property value by county for a given areaCompare charts based on multiple population statistics in your datasetDisplay an interactive scatter plot based on two values in your dataset along with an essential set of map exploration toolsData RequirementsThis app requires a map with at least one chart configured. For more information, see the Charts help topic.Key App CapabilitiesMultiple layout options - Choose to display your charts stacked with the map or side by side with the mapManage charts - Reorder, rename, or turn off and on charts in the appMultiselect chart - Compare two charts in the panel at the same timeBookmarks - Enable bookmarks configured in the Map Viewer to include a collection of preset extentsHome, Zoom Controls, Legend, Layer List, SearchSupportabilityThis web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

This bar chart displays books by publication date using the aggregation count. The data is filtered where the book publisher is Centre for Multi-Cultural Education. The data is about books.

The PERM Sponsorship Trends linear chart visualizes the number of PERM cases filed by Tisch Multiple Sclerosis Research Center Of New York from 2020 to 2023, highlighting the company’s long-term sponsorship patterns. The horizontal bar chart titled Distribution of Job Fields Receiving PERM Sponsorship further categorizes sponsored roles by job type.

Sheet 1 (Raw-Data): The raw data of the study is provided, presenting the tagging results for the used measures described in the paper. For each subject, it includes multiple columns: A. a sequential student ID B an ID that defines a random group label and the notation C. the used notation: user Story or use Cases D. the case they were assigned to: IFA, Sim, or Hos E. the subject's exam grade (total points out of 100). Empty cells mean that the subject did not take the first exam F. a categorical representation of the grade L/M/H, where H is greater or equal to 80, M is between 65 included and 80 excluded, L otherwise G. the total number of classes in the student's conceptual model H. the total number of relationships in the student's conceptual model I. the total number of classes in the expert's conceptual model J. the total number of relationships in the expert's conceptual model K-O. the total number of encountered situations of alignment, wrong representation, system-oriented, omitted, missing (see tagging scheme below) P. the researchers' judgement on how well the derivation process explanation was explained by the student: well explained (a systematic mapping that can be easily reproduced), partially explained (vague indication of the mapping ), or not present.

Tagging scheme:
Aligned (AL) - A concept is represented as a class in both models, either

with the same name or using synonyms or clearly linkable names; Wrongly represented (WR) - A class in the domain expert model is incorrectly represented in the student model, either (i) via an attribute, method, or relationship rather than class, or (ii) using a generic term (e.g., user'' instead ofurban planner''); System-oriented (SO) - A class in CM-Stud that denotes a technical implementation aspect, e.g., access control. Classes that represent legacy system or the system under design (portal, simulator) are legitimate; Omitted (OM) - A class in CM-Expert that does not appear in any way in CM-Stud; Missing (MI) - A class in CM-Stud that does not appear in any way in CM-Expert.

All the calculations and information provided in the following sheets

originate from that raw data.

Sheet 2 (Descriptive-Stats): Shows a summary of statistics from the data collection,

including the number of subjects per case, per notation, per process derivation rigor category, and per exam grade category.

Sheet 3 (Size-Ratio):

The number of classes within the student model divided by the number of classes within the expert model is calculated (describing the size ratio). We provide box plots to allow a visual comparison of the shape of the distribution, its central value, and its variability for each group (by case, notation, process, and exam grade) . The primary focus in this study is on the number of classes. However, we also provided the size ratio for the number of relationships between student and expert model.

Sheet 4 (Overall):

Provides an overview of all subjects regarding the encountered situations, completeness, and correctness, respectively. Correctness is defined as the ratio of classes in a student model that is fully aligned with the classes in the corresponding expert model. It is calculated by dividing the number of aligned concepts (AL) by the sum of the number of aligned concepts (AL), omitted concepts (OM), system-oriented concepts (SO), and wrong representations (WR). Completeness on the other hand, is defined as the ratio of classes in a student model that are correctly or incorrectly represented over the number of classes in the expert model. Completeness is calculated by dividing the sum of aligned concepts (AL) and wrong representations (WR) by the sum of the number of aligned concepts (AL), wrong representations (WR) and omitted concepts (OM). The overview is complemented with general diverging stacked bar charts that illustrate correctness and completeness.

For sheet 4 as well as for the following four sheets, diverging stacked bar

charts are provided to visualize the effect of each of the independent and mediated variables. The charts are based on the relative numbers of encountered situations for each student. In addition, a "Buffer" is calculated witch solely serves the purpose of constructing the diverging stacked bar charts in Excel. Finally, at the bottom of each sheet, the significance (T-test) and effect size (Hedges' g) for both completeness and correctness are provided. Hedges' g was calculated with an online tool: https://www.psychometrica.de/effect_size.html. The independent and moderating variables can be found as follows:

Sheet 5 (By-Notation):

Model correctness and model completeness is compared by notation - UC, US.

Sheet 6 (By-Case):

Model correctness and model completeness is compared by case - SIM, HOS, IFA.

Sheet 7 (By-Process):

Model correctness and model completeness is compared by how well the derivation process is explained - well explained, partially explained, not present.

Sheet 8 (By-Grade):

Model correctness and model completeness is compared by the exam grades, converted to categorical values High, Low , and Medium.

The H1B Sponsorship Trends linear chart shows the number of H1B cases filed by Tisch Multiple Sclerosis Research Center Of New York from 2020 to 2023, providing a clear view of filing trends over time. Alongside, the horizontal bar chart titled Distribution of Job Fields Receiving H1B Sponsorship breaks down which roles and industries are most commonly sponsored.

(G) Expression pattern of genes associated with group I and II loci (from Fig. 2E) within differentially expressed gene sets. Significance calculated by prop.test R, (***) P<0.001. (H) Venn diagram shows overlap between SOX3 binding in NPCs and GPCs. Bar graph shows expression pattern of genes continuously bound by SOX3 NPCs and GPCs. (I) Venn diagram shows overlap between SOX3 and SOX9 binding in GPCs. Bar graph shows expression pattern of genes co-bound by SOX3 and SOX9 in GPCs. (J) ChIP-seq peak graphics around the astrocyte gene Fgfbp3. ChIP-seq peaks are derived from three different experiments; SOX3 ChIPs in NPCs, SOX3 ChIPs in GPCs, SOX9 ChIPs in GPCs. Both ChIP-seq reads and called peak regions (underlying black lines) are shown for all data sets. Bar graphs shows the distribution of differentially expressed genes that are bound by all three factors. P-values (phyper, R) were calculated from the total number of protein coding genes in mm10 assembly (23´389). List of tagged entities: multiple components, Fgfbp3 (ncbigene:72514), Sox3 (uniprot:P53784), Sox9 (uniprot:Q04887), , ChIP assay (obi:OBI_0001954),ChIP-seq assay (obi:OBI_0000716),gene expression assay (bao:BAO_0002785)

The H1B Sponsorship Trends linear chart shows the number of H1B cases filed by Pm Multi Services from 2020 to 2023, providing a clear view of filing trends over time. Alongside, the horizontal bar chart titled Distribution of Job Fields Receiving H1B Sponsorship breaks down which roles and industries are most commonly sponsored.

The H1B Sponsorship Trends linear chart shows the number of H1B cases filed by 180 Multi Family Management from 2020 to 2023, providing a clear view of filing trends over time. Alongside, the horizontal bar chart titled Distribution of Job Fields Receiving H1B Sponsorship breaks down which roles and industries are most commonly sponsored.

The PERM Sponsorship Trends linear chart visualizes the number of PERM cases filed by 180 Multi Family Management from 2020 to 2023, highlighting the company’s long-term sponsorship patterns. The horizontal bar chart titled Distribution of Job Fields Receiving PERM Sponsorship further categorizes sponsored roles by job type.

Data DescriptionThe layers on this map contain population, employed labour force counts, private dwelling counts, and employment counts at Census Subdivision and Census Tract geographies from the 2006, 2011, and 2016 Census. The definition of each variable is described next:Population counts: the total population aggregated from different ages in each census tract.Employment counts: the number of labour force aged 15 years and over having an usual work place or working at home at places of work in each census tract, excluding workers with a non-fixed place-of-work.Employed labour force counts: the number of employed labour force aged 15 years and over having a usual work place or working at home at places of residence in each census tract including workers with a non-fixed place-of-work.Private dwellings count: the number of households aggregated from different types of dwellings in each census tract.Note: Population counts are from long census survey forms, covering 25% of the population. The other three variables are from short census survey forms, covering 100% population.Note about the Legend: the Employment and Population values are normalized by Quantiles. Each colour has the same number of features and will not necessarily represent the same values in different layers.InstructionsZoom in and out of the map to update the bar charts. Use the Select Tool to select specific geographies to display on the bar chart.“Select by rectangle” allows you to draw a rectangle and select multiple geography to view in the chart.“Select by point” allows you select an area by clicking on its geography."Add Data" allows you add separate public data as need from ArcGIS Online, URL (an ArcGIS Server Web Service, a WMS OGC Web Service, a KML file, a GeoRSS file, a CSV file), and local files (shapefile, csv, kml, gpx, geojson)Project lead: A.MaruicioDevelopers: C.Riccardo, W.Huang, D.Robbin

The H1B Sponsorship Trends linear chart shows the number of H1B cases filed by Multi Max from 2020 to 2023, providing a clear view of filing trends over time. Alongside, the horizontal bar chart titled Distribution of Job Fields Receiving H1B Sponsorship breaks down which roles and industries are most commonly sponsored.

The PERM Sponsorship Trends linear chart visualizes the number of PERM cases filed by Pm Multi Services from 2020 to 2023, highlighting the company’s long-term sponsorship patterns. The horizontal bar chart titled Distribution of Job Fields Receiving PERM Sponsorship further categorizes sponsored roles by job type.

The PERM Sponsorship Trends linear chart visualizes the number of PERM cases filed by Multi Max from 2020 to 2023, highlighting the company’s long-term sponsorship patterns. The horizontal bar chart titled Distribution of Job Fields Receiving PERM Sponsorship further categorizes sponsored roles by job type.

The PERM Sponsorship Trends linear chart visualizes the number of PERM cases filed by Marian Goodman Gallery Multiples from 2020 to 2023, highlighting the company’s long-term sponsorship patterns. The horizontal bar chart titled Distribution of Job Fields Receiving PERM Sponsorship further categorizes sponsored roles by job type.

Data DescriptionThe layers on this map contain population, employed labour force counts, private dwelling counts, and employment counts at Census Subdivision and Census Tract geographies from the 2006, 2011, and 2016 Census. The definition of each variable is described next:Population counts: the total population aggregated from different ages in each census tract.Employment counts: the number of labour force aged 15 years and over having a usual workplace or working at home in each census tract, excluding workers with a non-fixed place-of-work.Employed labour force counts: the number of employed labour force aged 15 years and over having a usual workplace or working at home at places of residence in each census tract including workers with a non-fixed place-of-work.Private dwellings count: the number of households aggregated from different types of dwellings in each census tract.Note: Employment-related counts are from long census survey forms, covering 25% of the population. The other three variables are from short census survey forms, covering 100% population.Note about the Legend: The Employment and Population values are normalized by Quantiles. Each colour represents the same share of features but will not represent the same values in different layers.InstructionsZoom in and out of the map to update the bar charts. Use the Select Tool to select specific geographies to display on the bar chart.“Select by point” allows you select an area by clicking on its geography."Add Data" allows you add separate public data as need from ArcGIS Online, URL (an ArcGIS Server Web Service, a WMS OGC Web Service, a KML file, a GeoRSS file, a CSV file), and local files (shapefile, csv, kml, gpx, geojson“Select by rectangle” allows you to draw a rectangle and select multiple geography to view in the chart.

Data DescriptionThe layer on this map contains population, employed labour force counts, private dwelling counts, and employment counts at a Census Subdivision geography from the 2016 Census. The definition of each variable is described next:Population counts: the total population aggregated from different ages in each census tract.Employment counts: the number of labour force aged 15 years and over having an usual work place or working at home at places of work in each census tract, excluding workers with a non-fixed place-of-work.Employed labour force counts: the number of employed labour force aged 15 years and over having a usual work place or working at home at places of residence in each census tract including workers with a non-fixed place-of-work.Private dwellings count: the number of households aggregated from different types of dwellings in each census tract.Note: Population counts are from long census survey forms, covering 25% of the population. The other three variables are from short census survey forms, covering 100% population.Note about the Legend: the Employment and Population values are normalized by Quantiles. Each colour has the same number of features and will not necessarily represent the same values in different layers.InstructionsZoom in and out of the map to update the bar charts. Use the Select Tool to select specific geographies to display on the bar chart.“Select by rectangle” allows you to draw a rectangle and select multiple geography to view in the chart.“Select by point” allows you select an area by clicking on its geography."Add Data" allows you add separate public data as need from ArcGIS Online, URL (an ArcGIS Server Web Service, a WMS OGC Web Service, a KML file, a GeoRSS file, a CSV file), and local files (shapefile, csv, kml, gpx, geojson)