--- title: "archeoViz. Visualisation, Exploration, and Web Communication of Archaeological Spatial Data" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{archeoViz. Visualisation, Exploration, and Web Communication of Archaeological Spatial Data} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ``` `archeoViz` is a packaged R Shiny application for the *visualisation*, *exploration*, and web *communication* of archaeological spatial data. It includes interactive 3D and 2D *visualisations*, can generate *cross sections* and *maps* of the remains, and display an interactive *timeline* of the work made in a site. Simple *spatial statistics* can be performed (convex hull, regression surfaces, 2D kernel density estimation), as well as *exporting data* to other online applications for more complex methods. `archeoViz` can be used locally or deployed on a server, either by allowing the user to load data through the interface or by running the app with a specific data set. The app interface is available in English, French, German, Italian, Portuguese, Romanian, and Spanish. Website: https://archeoviz.hypotheses.org. - [**Installation**](#installation) - [Local Use](#local-use) - [Remote Use](#remote-use) - [Demonstration](#demonstration) - [**Community Guidelines**](#community-guidelines) - [Reporting Bugs](#reporting-bugs) - [Suggesting Changes](#suggesting-changes) - [Translation](#translation) - [**Use**](#use) - [Spatial Information in archeoViz](#spatial-information-in-archeoviz) - [Points, Exact Location: Plotted Objects](#points-exact-location-plotted-objects) - [Points, Vague Location: Spits, Buckets, Sieved Objects, and Recording Errors](#points-vague-location-spits-buckets-sieved-objects-and-recording-errors) - [Lines](#lines) - [Surfaces](#surfaces) - [Refittings and Fabric Measurements](#refittings-and-fabric-measurements) - [Refittings](#refittings) - [Fabric Measurements](#fabric-measurements) - [Data Format](#data-format) - [Formatting Data](#formatting-data) - [Objects Table](#objects-table) - [Refitting Table](#refitting-table) - [Timeline Table](#timeline-table) - [Background drawing](#background-drawing) - [Units](#units) - [Data Input](#data-input) - [Through the Application Interface](#through-the-application-interface) - [Through the R Function Parameters](#through-the-r-function-parameters) - [Through URL Parameters](#through-url-parameters) - [Generating Random Data](#generating-random-data) - [Rotating the points](#rotating-the-points) - [Data sub-setting](#data-sub-setting) - [By Location Mode](#by-location-mode) - [By Layer or Object Category](#by-objects-category) - [Interactive Visualisation](#interactive-visualisation) - [General Features](#general-features) - [Visualising Spatial Uncertainty](#visualising-spatial-uncertainty) - [Graphical Outputs](#graphical-outputs) - [Spatial Statistics](#spatial-statistics) - [Regression Surfaces](#regression-surfaces) - [Convex Hulls](#convex-hulls) - [2D Kernel Density](#2d-kernel-density) - [**Reproducibility**](#reproducibility) - [**Exports from and to Third-party Applications**](#exports-from-and-to-third-party-applications) - [Export from archeoViz](#export-from-archeoviz) - [Import to archeoViz](#import-to-archeoviz) - [**Advanced Parameters**](#advanced-parameters) - [Square Grid](#square-grid) - [Parameter Presetting](#parameter-presetting) - [Reactive Plot Display](#reactive-plot-display) - [Control Export Formats](#control-export-formats) - [URL parameters](#url-parameters) - [**Acknowledgments**](#acknowledgments) - [**References**](#references) - [Software](#Software) - [Papers](#papers) - [Presentations](#presentations) - [Websites](#websites) # Installation `archeoViz` can be used in two ways: * locally, on the user's machine * remotely, after deploying the app on a distant server ## Local use The package can be installed from CRAN with: ```r install.packages("archeoViz") ``` The development version is available on *GitHub* and can be installed with: ```r # install.packages("devtools") devtools::install_github("sebastien-plutniak/archeoviz") ``` Then, load the package and launch the app with: ```r library(archeoViz) archeoViz() ``` ## Remote use To deploy `archeoViz` on your Shiny server, first download and unzip the package: ```{r, eval=FALSE} # set the working directory on your shiny server: setwd(dir = "/some/path/") # download the package: download.file( url = "https://github.com/sebastien-plutniak/archeoviz/archive/master.zip", destfile = "archeoviz.zip") # unzip it: unzip(zipfile = "archeoviz.zip") ``` Then, go to `https:///archeoviz-main`. To set the app with your data and preferences, edit the app.R file, located at the root of the directory: ```{r, eval=FALSE} archeoViz(objects.df = NULL, # data.frame with data about the objects refits.df = NULL, # optional data.frame for refitting data timeline.df = NULL, # optional data.frame for the excavation timeline title = NULL, # title of the site / data set home.text = NULL, # HTML content to display on the home page lang = "en" # interface language ("de": German, "en": English, "fr": French, "it": Italian, "pt": Portuguese, "es": Spanish) set.theme = "cosmo") # graphic theme for the Shiny interface ``` The possible values for the `set.theme` parameter are illustrated on [this page](https://rstudio.github.io/shinythemes/). The language of the application can be set with the `lang` parameter. ## Demonstration Demonstration instances of the application are deployed on the *Huma Num* Shiny server: * [`archeoViz` in German](https://analytics.huma-num.fr/archeoviz/de). * [`archeoViz` in English](https://analytics.huma-num.fr/archeoviz/en). * [`archeoViz` in French](https://analytics.huma-num.fr/archeoviz/fr). * [`archeoViz` in Spanish](https://analytics.huma-num.fr/archeoviz/es). * [`archeoViz` in Italian](https://analytics.huma-num.fr/archeoviz/it). * [`archeoViz` in Portuguese](https://analytics.huma-num.fr/archeoviz/pt). * [`archeoViz` in Romanian](https://analytics.huma-num.fr/archeoviz/ro). Real use cases are presented on the [*archeoViz Portal*](https://analytics.huma-num.fr/archeoviz/home). # Community guidelines ## Reporting bugs If you encounter a bug, please fill an [issue](https://github.com/sebastien-plutniak/archeoviz/issues) with all the details needed to reproduce it. ## Suggesting changes Suggestions of changes to `archeoViz` are welcome. These requests may concern additional functions, changes to documentation, additional examples, new features, etc. They can be made by filling an [issue](https://github.com/sebastien-plutniak/archeoviz/issues) and, even better, using pull requests and the [GitHub Fork and Pull model](https://docs.github.com/articles/about-pull-requests). ## Translation In the development of `archeoViz`, particular attention is paid to multilingualism. The application interface is available in several languages and translations into additional languages are welcome. To do so, please edit this [file](https://github.com/sebastien-plutniak/archeoviz/blob/main/R/load_interface_terms_utf8.R) and submit a pull request. # Use Having archaeological remains from a given site, `archeoViz` is designed to lower the technical barriers to fulfill three objectives: * basic spatial exploration and generation of simple graphical reports; * fast pre-publication of archaeological data, intended for the scientific community; * fast deployment of a visualisation and communication tool intended for a broader audience. In addition, `archeoViz` is a suitable pedagogical resource for teaching spatial analysis in archaeology, data structuring, open science, and reproducible workflow. N.B.: consequently, `archeoViz` is not intended to replace more sophisticated analysis tools (e.g., GIS, statistical packages, etc.) ## Spatial Information in archeoViz Archaeologists record the location of archaeological objects at different scales and granularity. Accordingly, they use different geometrical concepts to represent location. ### Points, Exact Location: Plotted Objects Using grid coordinates or electronic “total station” enables recording the individual location of objects on the field. In that case, the location are represented as points in `archeoViz` (triplets of x, y and z coordinates). ### Points, Vague Location: Spits, Buckets, Sieved Objects, and Recording Errors However, it is also common that x, y, z, coordinates by object are not available, for different reasons due to: * recording errors, loss of information, resulting in the need to replace one of several coordinates values by ranges (e.g., a X value is missing for an object and is replaced by the minimal and maximal X values of the square where this object was found); * choice of method (e.g., excavation made and recorded using spits of arbitrary depth, sieved objects, etc.). In all these cases, we have to deal with vague location, when objects cannot be located as points but are somewhere between ranges of coordinates. Vague location can concern one, two, or the three spatial dimensions (the x, y, z coordinates, respectively). Note that this feature can also be used to deal with the imprecision of topographical instruments. ### Lines Lines are useful geometries for representing relationships. In archaeology, these can be [refitting](#reffitings) relationships between object fragments, orientation ([fabric measurements](#fabric-measurements), etc. Lines are generated from data loaded as refitting data, either from the “Data” tab, or with the `refits.df` parameter of the `archeoViz()` function. ### Surfaces Surfaces are useful geometries for representing ground levels, trenches, pits, etc. In `archeoViz`, this can be achieved by defining a subset of points summarising the desired surface, then displaying the [convex hull](#convex-hulls) of this subset. ## Refittings and Fabric Measurements ### Refittings Refittings are usually recorded by archaeologists in two ways: 1. by sets of refitting objects: using a two columns table, where a row corresponds to an **object**. The first column stores the object's unique id and the second column stores the id of the set of refitting objects this object belongs to. 2. by refitting relationships: using a two columns table, where a row corresponds to a **relationship**. The first column stores the first object's unique id and the second column stores the second object's unique id. Although the second data structure is more accurate, the first is more commonly used. `archeoViz` processes and represents the two data structures in two ways: * sets of refitting objects must be described using a specific column in the `objects.df` table (e.g. `object_refits`) and are represented by the color of points in the plots (like any other variable); * refitting relationships must be described using the `refits.df` table and are visualised as segments connecting the refitting objects in the plots. ### Fabric Measurements So far, `archeoViz` does not handle fabric measurements properly. However, the process used to represent refittings can also adapted and used to represent fabric measurements. This requires to distort the data structure as follows: * assuming that fabric measurements were recorded with two measurements on each object (and not with dip and plunge measurements), * different unique `id` values must be given to the two points, and * the two measures are processed as if they were two refitting objects. See an example of this method [here](https://analytics.huma-num.fr/archeoviz/shuidonggou2). ## Data Format Three types of data can be loaded in `archeoViz`: * an “objects” table (mandatory), with data about the objects; * a “refits” table (optional), with data about the refitting objects; * a “timeline” table (optional) giving the year when each square of the site was excavated or surveyed. ### Formatting Data The tables must be CSV files with the first row containing the column labels. Contents in HTML are allowed. This makes it possible, in particular, to add links to external resources (e.g., to objects permanent identifier in other databases, or to concepts identifiers in standard ontologies / thesauri, etc.). Formatting your data can be done: * either using a spreadsheet editor on your machine to generate CSV files; * or, for the `objects table,` using the [*SEAHORS*](https://aurelienroyer.shinyapps.io/Seahors/) application to load your data, define the variables (in the “Load data” tab), and export it to the `archeoViz` format (in the “Table” / “archeoViz exports” tab). It is also possible to directly send the data to an online `archeoViz` instance. ### Objects Table A row describes a single object with the following mandatory fields: * **id**: *alphanumerical value*, unique identifier of the object * **xmin**: *numerical value*, coordinate of the object on the X axis * **ymin**: *numerical value*, coordinate of the object on the Y axis * **zmin**: *numerical value*, coordinate of the object on the Z axis (positive depth value) * **layer**: *alphanumerical value*, identifier of the object's layer * **object_type**: *alphanumerical value*, category of the object In addition, optional fields are possible, including: * **square_x**: *alphanumerical value*, identifier of the square on the X axis * **square_y**: *alphanumerical value*, identifier of the square on the Y axis * **year** : *numerical value*, year when the object was excavated * **xmax**: *numerical value*, when the X location of the object is included in a range of X coordinates * **ymax**: *numerical value*, when the Y location of the object is included in a range of Y coordinates * **zmax**: *numerical value*, when the Z location of the object is included in a range of Z coordinates * **object_edit**: unlimited number of additional variables describing the object (field names must start with `object_` and have different suffixes) The labels of the squares of the grid: * are ordered alpha-numerically; * are not displayed to avoid erroneous displays, if the number of labels does not correspond exactly to the total number of 100 (cm, m, km) squares that can be defined in the range of minimum and maximum coordinates contained in the xmin and ymin variables; * can be completed with the `add.x.square.labels` and `add.y.square.labels` parameters of the `archeoViz()` function in order to add the missing labels (on the X and Y axes of the grid, respectively). ### Refitting Table A data table with two columns can be uploaded for refitting data (CSV format). Each row must contain the unique identifiers of two refitting objects (corresponding to the values of the `id` column in the objects table). ### Timeline Table A table (CSV format) can be uploaded about excavation history. Row gives the year when each grid square of the site was excavated or surveyed. This table must include the following variables: * **year**: numerical value, the year of excavation * **square_x**: alphanumerical value, identifier of the excavated square on the X axis * **square_y**: alphanumerical value, identifier of the excavated square on the Y axis ### Background Drawing A background drawing can be displayed in the 3D and Map plots. This feature makes it possible, for example, to show a site map behind a point cloud. It requires a data table in which each row gives the X and Y coordinates of the points to be used to draw. Note that the lines will be drawn following the order of the points in the table. The coordinates system used must be the same that the one used for the objects. To draw several lines, an additional column (named “group”) is required, containing for each point the unique identifier of the line to which this point belongs to. The data set is loaded using the `background.map` parameter. ### Units By default, all distances in `archeoViz` are in centimeter. However, it can be changed by giving the `unit` parameter one of the following value: “cm”, “m”, “km”. This parameter determines the contents of the legend of the square size. ## Data Input There are four ways to input data in `archeoViz`: 1. uploading data tables through the “Input data” tab, 2. loading data tables through the `archeoViz` function's parameters, in the R interface; 3. uploading data tables through URL parameters, when using an online instance of `archeoViz`. 4. generating random data in the “Input data” tab; ### Through the Application Interface The three types of tables can be loaded in the “Input data” tab. The CSV separator (one of: comma, semicolon, tabulation) and the character used for decimal points (period or comma). ### Through URL parameters The URL of an online instance of `archeoViz` can include the parameters: * `objects.df=` * `refits.df=` * `timeline.df=` whose values must be the URL of a CSV file observing the `archeoViz` format described above. For example: [https://analytics.huma-num.fr/archeoviz/en/?objects.df=https://zenodo.org/record/8003880/files/bilzingsleben.csv](https://analytics.huma-num.fr/archeoviz/en/?objects.df=https://zenodo.org/record/8003880/files/bilzingsleben.csv) ### Generating Random Data Using randomly generated data is made possible for demonstration purposes. To activate this feature, set the slider in “Input data” to a value higher than 0 (setting the value back to 0 deactivates the feature). An “objects” data set, a “refits” data set, and a “timeline” data set are generated, making it possible to test all the `archeoViz` functionalities. ### Through the R function parameters `archeoViz`'s launching function (`archeoViz()`) can be run without parameter ```{r, eval=FALSE} archeoViz() ``` or by using the `objects.df`, `refits.df`, or `timeline.df` parameters to input data.frames about the archaeological objects, refitting relationships between these objects, and the chronology of the excavation, respectively. ```{r, eval=FALSE} archeoViz(objects.df = NULL, # data.frame with data about the objects refits.df = NULL, # data.frame for refitting objects timeline.df = NULL) # optional data.frame for the excavation timeline ``` ### Rotating the points You can change the orientation of the points in the plan. In the “Data” tab, select a value (in degrees) and click on the “Validate selection” button to confirm. ## Data Sub-setting Once data are loaded, a sub-selection of the data can be done in the left side menu. Grouping can be done by crossing the following parameters: the mode of location, the layers, and the category of object. ### By Location Mode If all the objects have exact location or vague location, then no option is proposed. However, if the dataset includes both exact and vague location, then it is possible to select only one or both of these options. ### By Layer or Object Category The data can be grouped in two ways: either based on their layer or on the selected “object_” variable. This option determines the colours of the points in the 3D and 2D plots and how to group points when computing convex hulls and 3D regression surfaces. Sub-sets can be defined by object categories, using the “variable” and “values” fields. Once one of the “object_type” (or other possible “object_” variables) is selected, its values appear below and can be selected using the tick boxes. The selection must be validated by clicking on the “Validate” button. This selection determines the data to be displayed in the plots and tables. ## Interactive visualisation ### General features The plots in the “3D plot”, “Map”, “Section X”, and “Section Y” tabs are generated using the [`plotly`](https://CRAN.R-project.org/package=plotly) library. All the plots are dynamic and include a menu bar above the plot with several options (generating an image file, zooming, moving the view, etc). See details on the [`plotly` website](http://plotly.github.io/getting-to-know-the-plotly-modebar/). Clicking on a legend's item modifies the display: * a simple click on an item activates/deactivates its display; * a double click on an item displays this item only (another double click cancels it). This feature makes it possible to choose which layers are shown. In addition, the size of the points can be set and whether the refitting relationships must be represented or not. Finally, clicking on a point displays information about that point in the table below the plot. ### Visualising Spatial Uncertainty In `archeoViz`, a distinction is made between exact location (given as x, y, z coordinates) and vague locations (given as ranges of coordinates). Both types of locations can be displayed. The uncertainty of vague locations can be visualised by representing objects not as points but as lines, planes, and volumes (if ranges of coordinates are given for one, two, or three spatial dimensions, respectively). Note that this feature is resource intensive and using it with too much data can significantly slow down the application. ### Graphical outputs Several graphical outputs can be generated in `archeoViz`. * The plots in the “3D plot”, “Map”, “Section X”, and “Section Y” tabs can be exported: * in SVG format (by clicking on the “camera” icon in the menu bar above the plot), * as interactive plots in HTML format, by clicking on the “Export” button. * The small map in the “Section X” and “Section Y” tabs can be exported in SVG by clicking on the “Download Map” link. * The plan of the excavation chronology can be exported in SVG format by clicking on the “Download” button. ## Spatial statistics `archeoViz` includes some spatial analysis functionalities, intended for basic and exploratory use. ### Regression surfaces In the “3D plot” tab, clicking on “Compute surfaces” and “Validate” displays the regression surface associated with each layer (with at least 100 points). The surfaces are computed using the generalized additive model implemented in the [`mgcv`](https://CRAN.R-project.org/package=mgcv) package. ### Convex hulls In the “3D plot” tab, convex hulls can be displayed as follows: 1. tick the “Convex hulls” box, 2. select, from the menu that appears, the subsets of points for which convex hulls are to be calculated, 3. click on “Validate”. Convex hulls associated with each subsets with at least 20 points are displayed. The convex hulls are computed using the [`cxhull`](https://CRAN.R-project.org/package=cxhull) package. ### 2D kernel density In the “Map” tab, ticking the “Compute density” box and clicking on “Validate” generates a map with contour lines showing the points' density. Density can be computed for all the points together or by layer (with at least 30 points). The 2D kernel density is computed with the `kde2d` function of the [`MASS`](https://CRAN.R-project.org/package=MASS) package (through [`ggplot2`](https://CRAN.R-project.org/package=ggplot2)). ## Reproducibility `archeoViz` is, by definition, an interactive application. However, several features guarantee the reproducibility and communicability of the result of interactions with the application. * The 3D visualisation can be exported in an interactive HTML standalone format, considering the data selection made by the user. * In the “Reproducibility” tab, an R command is dynamically generated, considering the current application settings made by the user. * In a more advanced use, the URL parameters makes it possible to set an online instance of the application parameters of interest and to communicate it by sending the URL. ## Exports from and to Third-party Applications `archeoViz` was designed as one of the building blocks of a decentralised digital ecosystem for archaeological data and analysis. In this perspective, features and functions are distributed in multiple interconnected applications, rather than concentrated into few systems. Consequently, data can be exported and imported between `archeoViz` and other web-based applications. Note that, so far, the export functionalities are only available when using online `archeoViz` instances. ### Export from archeoViz Data can be exported to other online applications from `archeoViz` "Statistics" tab. Some exports are possible only for specific types of data or if a minimum number of values is satisfied. [*archeofrag*](https://analytics.huma-num.fr/Sebastien.Plutniak/archeofrag) is an R package and web application to assess and evaluate the distinctions betwen archaeological spatial units (e.g. layers) based on the analysis of refitting relationships between fragments of objects. The web version of the application includes methods to measure the cohesion and admixture of spatial units, and compare it to simulated data. If an instance of `archeoViz` is launched with [refitting data](#refittings), then this data can be analysed with `archeofrag`. See an example [here](https://analytics.huma-num.fr/archeoviz/grotte16). The [*Seriograph*](https://analytics.huma-num.fr/ModAthom/seriograph/) is a web application (part of the [SPARTAAS](https://spartaas.gitpages.huma-num.fr/r-package/) collection) to visualise changes in the quantitative distribution of artefacts types in ordered or unordered series of spatial units. Export to `Seriograph` is available from online `archeoViz` instance (only) for dataset with at least 2 different values for the `layer` variable and 2 different values for the selected variable (by default, `object_type`). See an example [here](https://analytics.huma-num.fr/archeoviz/poeymau). [*Amado online*](https://app.ptm.huma-num.fr/amado/) is an on-line application for analysing contingency tables. `Amado online` allows you to manually reorder rows and columns, and perform automatic seriation and classification. Export to `Amado online` is available from online `archeoViz` instance (only) for dataset with at least 2 different values for the `layer` variable and 2 different values for the selected variable (by default, `object_type`). See an example [here](https://analytics.huma-num.fr/archeoviz/tai). [*explor*](https://cran.r-project.org/package=explor) is an R Shiny / R package application for interactively exploring the results of multi-dimensional analyses. Export to `explor` is available from online `archeoViz` instance (only) for dataset with at least 2 different values for the `layer` variable and 2 different values for the selected variable (by default, `object_type`). The version of `explor` used from `archeoViz` is a fork of the original application, adapted to run correspondence analysis. See an example [here](https://analytics.huma-num.fr/archeoviz/tai). [*shinyHeatmaply*](https://cran.r-project.org/package=shinyHeatmaply) is an R Shiny / R package application to generate and interactively explore heatmaps. Multiple statistical distance and classification methods can be applied. Export to `shinyHeatmaply` is available from online `archeoViz` instance (only) for dataset with at least 2 different values for the `layer` variable and 2 different values for the selected variable (by default, `object_type`). The version of `shinyHeatmaply` used from `archeoViz` is a fork of the original application. See an example [here](https://analytics.huma-num.fr/archeoviz/grande-rivoire). ### Import to archeoViz [*SEAHORS*](https://aurelienroyer.shinyapps.io/Seahors/) is a web application and R package to visualise the spatial distribution of archaeological remains. As mentioned [above](#formatting-data), SEAHORS can be used to import, reshape, and send a dataset to an online instance of the `archeoViz` application. ## Advanced parameters The `archeoViz()` function can be set with multiple optional parameters, related to: * the input data (see [above](#through-function-parameters)), * the contents of the home page (see [above](#deployed-use)), * the [square grid](#square-grid), * the [presetting](#parameters-presetting) of the parameters that can be set through the application's graphical interface, * the [reactive behavior](#reactive-plot-display) of the application regarding the generation of plots, * the [HTML export](#html-export), * the [URL parameters](#url-parameters). ```{r, eval=FALSE} archeoViz(objects.df=NULL, refits.df=NULL, timeline.df=NULL, title=NULL, home.text=NULL, lang="en", set.theme="cosmo", square.size = 100, unit = "cm", rotation = 0, grid.orientation = NULL, background.map = NULL, reverse.axis.values = NULL, reverse.square.names = NULL, add.x.square.labels = NULL, add.y.square.labels = NULL, class.variable = NULL, class.values = NULL, default.group = "by.layer", location.mode = NULL, map.z.val = NULL, map.density = "no", map.refits = NULL, plot3d.ratio = 1, plot3d.hulls = FALSE, hulls.class.values = NULL, plot3d.surfaces = NULL, plot3d.refits = NULL, point.size = 2, sectionX.x.val = NULL, sectionX.y.val = NULL, sectionX.refits = NULL, sectionY.x.val = NULL, sectionY.y.val = NULL, sectionY.refits = NULL, camera.center = c(0, 0, 0), camera.eye = c(1.25, 1.25, 1.25), run.plots = FALSE, html.export = TRUE, table.export = TRUE ) ``` ### Square grid ```{r, eval=FALSE} archeoViz(square.size = 100, unit = "cm", rotation = 0, grid.orientation = NULL, background.map = NULL, reverse.axis.values = NULL, reverse.square.names = NULL, add.x.square.labels = NULL, add.y.square.labels = NULL ) ``` * **square.size**: numerical. Size (width and height) of the squares in the grid system. Default value is 100. * **unit**: character. Unit for spatial distances. One of “cm”, “m”, “km”. * **rotation**: integer. Value (degrees) for the in-plane rotation of the point cloud. * **grid.orientation**: numerical. Orientation (degrees, positive or negative) of the grid (0 corresponds to a north orientation). * **background.map**: data frame or matrix. Coordinates to draw background lines in 3D and Map plots. * **reverse.axis.values**: character. Name of the axis or axes to be reversed (any combination of “x”, “y”, “z”). * **reverse.square.names**: character. Name of the axis or axes for which to reverse the order of the square labels (any combination of “x”, “y”, “z”). * **add.x.square.labels**: character. Additional square labels for the “x” axis. * **add.y.square.labels**: character. Additional square labels for the “y” axis. ### Parameter presetting ```{r, eval=FALSE} archeoViz(class.variable = NULL, class.values = NULL, default.group = "by.layer", location.mode = NULL, map.z.val = NULL, map.density = "no", map.refits = NULL, plot3d.hulls = NULL, plot3d.surfaces = NULL, plot3d.refits = NULL, sectionX.x.val = NULL, sectionX.y.val = NULL, sectionX.refits = NULL, sectionY.x.val = NULL, sectionY.y.val = NULL, sectionY.refits = NULL, camera.center = NULL, camera.eye = NULL ) ``` * **class.variable**: character. At the launch of the app, name of the variable to preselect. * **class.values**: character vector. At the launch of the app, names of the values to preselect. * **default.group**: character. At the launch of the app, preset of the variable used to group data (one of “by.layer” or “by.variable”). * **location.mode**: character. At the launch of the app, preset of the location methods (any combination of “exact”, “fuzzy”, “show.uncertainty”). * **map.z.val**: numerical. Minimal and maximal Z coordinates values to display in the map plot. * **map.density**: character. At the launch of the app, whether to compute and show density contours in the map plot (one of “no”, “overall”, “by.variable”). * **map.refits**: TRUE or FALSE. Whether to show refits in the map plot. * **plot3d.hulls**: TRUE or FALSE. At the launch of the app, whether to compute and show convex hulls in the 3D plot. * **hulls.class.values**: character. At the launch of the app, names of the points subsets for which to compute convex hulls. * **plot3d.surfaces**: TRUE or FALSE. At the launch of the app, whether to compute and show regression in the 3D plot. * **plot3d.refits**: TRUE or FALSE. At the launch of the app, whether to show refits on the 3D section plot. * **point.size**: integer. At the launch of the app, size of the points in the plots. * **sectionX.x.val**: numerical. At the launch of the app, minimal and maximal X coordinates values to display in the X section plot. * **sectionX.y.val**: numerical. At the launch of the app, minimal and maximal Y coordinates values to display in the X section plot. * **sectionX.refits**: TRUE or FALSE. At the launch of the app, whether to show refits in the X section plot. * **sectionY.x.val**: numerical. At the launch of the app, minimal and maximal X coordinates values to display in the Y section plot. * **sectionY.y.val**: numerical. At the launch of the app, minimal and maximal Y coordinates values to display in the Y section plot. * **sectionY.refits**: TRUE or FALSE. At the launch of the app, whether to show refits in the Y section plot. * **camera.center**: numerical. In 3D plot, coordinates of the point to which the camera looks at (default values: x=0, y=0, z=0). * **camera.eye**: numerical. In 3D plot, coordinates of the camera's position (default values: x=1.25, y=1.25, z=1.25). ### Reactive plot display ```{r, eval=FALSE} archeoViz(run.plots = FALSE) ``` * **run.plots**: TRUE or FALSE. Whether to immediately compute and show plots (without requiring the user to click on the “Refresh” button). ### Control Export Formats * **html.export** : TRUE or FALSE. Whether or not to allow figures to be exported as interactive HTML widgets. * **table.export**: TRUE or FALSE. Allow or disallow data transfer to [third-party applications](#exports-from-and-to-third-party-applications) in the “Statistics” tab. ### URL parameters An instance of `archeoViz` deployed online on a server can be set with URL parameters. Supported parameters include: * `objects.df`, `refits.df`, `timeline.df` * `title`, `home.text` * `reverse.axis.values`, `reverse.square.names` * `square.size` * `add.x.square.labels`, `add.y.square.labels` * `class.variable`, `class.values` * `default.group` * `location.mode` * `map.density`, `map.refits` * `plot3d.hulls`, `plot3d.surfaces`, `plot3d.refits` * `sectionX.refits` * `sectionY.refits` * `run.plots` (The following parameters are not supported in the current version: `map.z.val`, `sectionX.x.val`, `point.size`, `sectionX.y.val`, `sectionY.x.val`, `sectionY.y.val`, `lang`, `set.theme`, `camera.center`, `camera.eye`, `html.export`, `table.export`.) The parameters must be written using the URL syntax (?param1=value¶m2=value2) and have the same type of values than when used in the R interface. For example, the following URL launches an `archeoViz` instance using the [Bilzingsleben](https://zenodo.org/record/8003880) dataset: [https://analytics.huma-num.fr/archeoviz/en/?objects.df=https://zenodo.org/record/8003880/files/bilzingsleben.csv](https://analytics.huma-num.fr/archeoviz/en/?objects.df=https://zenodo.org/record/8003880/files/bilzingsleben.csv) This URL does the same, but also includes the refitting table (parameter `&refits.df=`) and set the activate the display of the refitting relationships in the 3D and map plots: [https://analytics.huma-num.fr/archeoviz/en/?map.refits=TRUE&plot3d.refits=TRUE&objects.df=https://zenodo.org/record/8003880/files/bilzingsleben.csv&refits.df=https://zenodo.org/record/8003880/files/bilzingsleben-antlers-refits.csv](https://analytics.huma-num.fr/archeoviz/en/?map.refits=TRUE&plot3d.refits=TRUE&objects.df=https://zenodo.org/record/8003880/files/bilzingsleben.csv&refits.df=https://zenodo.org/record/8003880/files/bilzingsleben-antlers-refits.csv) The following URL launches the Bilzingsleben dataset, pre-setting the app to: 1. groups the points by variable (parameter `default.group`, with walue `by.variable` instead of `by.layer`) 2. selects only the "Antlers" (parameter `class.values`) 3. redefines the size of the square grid (parameter `square.size`, 500 instead of the 100 default value) 4. enable the immediate display of the plots (parameter `run.plots`) 5. modifies the title of the page (parameter `title`) 6. modifies the content of the home page with basic HTML contents (parameter `home.txt`) [https://analytics.huma-num.fr/archeoviz/en/?default.group=by.variable&class.values=Antler&square.size=500&run.plots=TRUE&title=Antlers%20at%20Bilzingsleben&home.text=Many%20antlers&objects.df=https://zenodo.org/record/8003880/files/bilzingsleben.csv](https://analytics.huma-num.fr/archeoviz/en/?default.group=by.variable&class.values=Antler&square.size=500&run.plots=TRUE&title=Anters%20at%20Bilzingsleben&home.text=Many%20antlers&objects.df=https://zenodo.org/record/8003880/files/bilzingsleben.csv) Note that the parameters `add.x.square.labels`, `add.y.square.labels`, `location.mode`, and `class.values`, which accept simple or multiple values in the R interface (e.g., c("value1", "value2")) only accept one value when set as URL parameters (this is a restriction due to the URL syntax). # Acknowledgments The `archeoViz` application and package is developed and maintained by Sébastien Plutniak. Arthur Coulon, Solène Denis, Olivier Marlet, and Thomas Perrin tested and supported the project in its early stage. Renata Araujo, Laura Coltofean, Sara Giardino, Julian Laabs, and Nicolas Delsol translated the application into Portuguese, Romanian, Italian, German, and Spanish respectively. # References ## Software * Plutniak, Sébastien, Renata Araujo, Laura Coltofean, Nicolas Delsol, Sara Giardino, Julian Laabs. 2024. “archeoViz. Visualisation, Exploration, and Web Communication of Archaeological Spatial Data”. v1.3.4, DOI: [10.5281/zenodo.7460193](https://doi.org/10.5281/zenodo.7460193). * Plutniak, Sébastien, Anaïs Vignoles. 2023. “[The archeoViz Portal: Dissemination of Spatial Archaeological Datasets](https://hal.science/hal-04156271)”, web portal, https://analytics.huma-num.fr/archeoviz/home. ## Papers * Plutniak, Sébastien. 2023. “archeoViz: an R package for the Visualisation, Exploration, and Web Communication of Archaeological Spatial Data”. *Journal of Open Source Software*, 92(8), 5811, DOI: [10.21105/joss.05811](https://doi.org/10.21105/joss.05811). * Plutniak, Sébastien. 2023. “[Visualiser et explorer la distribution spatiale du mobilier archéologique : l'application archeoViz et son portail web](https://www.prehistoire.org/offres/doc_inline_src/515/0-BSPF_2023_1_2e_partie_Correspondance_PLUTNIAK.pdf)”. *Bulletin de la Société préhistorique française*, 120(1), p. 70-74. ## Presentations * Plutniak, Sébastien. 2023. “[Fostering the Publication of Spatial Archaeological Data: a Decentralized Approach. The archeoViz Web Application and its Portal](https://hal.science/hal-04146410)”, slides of a presentation at the University of Florida, Gainesville. * Plutniak, Sébastien, Anaïs Vignoles. 2023. “[L’application web / package archeoViz et son portail web. Une solution décentralisée d’éditorialisation de données archéologiques spatialisées](https://hal.science/hal-04070444), slides of a presentation at the SITRADA workshop, Paris. ## Websites * The *archeoViz. Data visualization in archaeology. Re-use, visualization, dissemination of spatial data* blog: https://archeoviz.hypotheses.org