Merge pull request #114 from NNoemi1/main

Minor fixes and adding DE_External layers and DE_Sharing (chatgpt translation)

docs/data/data_basis.md

@@ -5,12 +5,12 @@ sidebar_position: 2
 # Inbuilt Datasets
 
 
-### Data as an important basis for analyses
+## Data as an important basis for analyses
 
 At Plan4Better, we recognize that data is the fuel that powers our analyses, making it our most valuable asset. To deliver accurate insights based on high-quality information, our WebGIS platform [GOAT](https://goat.plan4better.de/login) integrates a variety of diverse geospatial and non-geospatial datasets from various sources. However, processing inconsistent data from different sources with varying degrees of accuracy can pose a significant challenge. To address this issue, we leverage a range of techniques including efficient data integration, disaggregation, and fusion workflows.
 
 
-### Data collection and preparation
+## Data collection and preparation
 
 The data collection process involves identifying relevant data sources and collecting data - ideally from open data portals or publicly available initiatives. Depending on the data source, various formats such as shapefiles and GeoJSON may be used. It is therefore essential to prepare and convert the data into a common schema and format to ensure consistency and comparability.
 
@@ -20,7 +20,7 @@ At Plan4Better, we ensure that our data is up-to-date by updating it at least on
 
 ![GOAT data basis](/img/data/data_basis/original_files/data_en_blue.png "GOAT data basis")
 
-### Datasets in the Catalog
+## Datasets in the Catalog
 
 The following datasets are available via the Catalog. These are managed as *feature layers* containing geospatial features (points, lines, or polygons) or non-geospatial data (in a tabular format), and can be added to your projects for analysis and visualization. While not an exhaustive list of available layers, the following information provides an overview of the primary dataset types.
 
@@ -30,7 +30,7 @@ This section provides technical details about datasets available in the Catalog.
 
 ::::
 
-#### Points of Interest (POIs)
+### Points of Interest (POIs)
 Locations of common amenities, facilities, and trip-attractors that are necessary for accessibility planning.
 
 - *Features:*
@@ -44,7 +44,7 @@ Locations of common amenities, facilities, and trip-attractors that are necessar
 - *Sources:*
     [Overture Maps Foundation](https://overturemaps.org/), [Open Street Map (OSM)](https://wiki.openstreetmap.org/), government departments and agencies, health insurance companies, and retailer companies. Additional data collection may be carried out in the field by us if needed.
 
-#### Population and Buildings
+### Population and Buildings
 Population data is often provided at a micro level (e.g. the number of people residing in a building) and is disaggregated from district, municipality, or census population data. This disaggregation process also takes into account land-use information to improve the accuracy of results.
 
 - *Features:*
@@ -55,7 +55,7 @@ Population data is often provided at a micro level (e.g. the number of people re
 - *Sources:*
     Population data is fetched from various sources including the [German Zensus 2022](https://ergebnisse.zensus2022.de/datenbank/online/), and individual municipalities and districts, while building data is fetched in the form of 3D City Models from German federal states.
 
-#### Administrative Boundaries
+### Administrative Boundaries
 Areas under the jurisdiction of governmental or administrative entities.
 
 - *Features:*
@@ -67,7 +67,7 @@ Areas under the jurisdiction of governmental or administrative entities.
 - *Sources:*
     The [Federal Agency for Cartography and Geodesy (BKG)](https://www.bkg.bund.de/) and [Open Street Map (OSM)](https://wiki.openstreetmap.org/).
 
-### Network Datasets for Routing
+## Network Datasets for Routing
 
 These are the networks used by GOAT's accessibility indicators for performing routing-based analyses.
 
@@ -77,7 +77,7 @@ While in-built networks are currently used for public transport and street routi
 
 ::::
 
-#### Public Transport Network
+### Public Transport Network
 Extensive public transport network data for various modes such as buses, trams, subways, trains, ferries, and more. This is used by GOAT for [Public Transport](../routing/public_transport) routing.
 
 ![Public Transport Network](/img/data/data_basis/pt_network_banner.png "Public Transport Network")
@@ -100,7 +100,7 @@ Extensive public transport network data for various modes such as buses, trams,
     - The network is optimized to only include the modal pattern of service for each route (the most prevalent sequence of trips).
     - GOAT allows public transport analysis for three day-of-week types (**Weekday**, **Saturday**, and **Sunday**) with a **Tuesday** typically used as a reference day for the *Weekday* type.
 
-#### Street Network and Topography
+### Street Network and Topography
 Extensive street network data that represents real-world transport networks and their components: roads, motorways, interchanges, dedicated paths, and more. This is used by GOAT for [Walk](../routing/walking), [Bicycle](../routing/bicycle), [Pedelec](../routing/bicycle), and [Car](../routing/car) routing.
 
 ![Street Network](/img/data/data_basis/street_network_banner.png "Street Network")

docs/data/dataset_types.md

@@ -13,7 +13,10 @@ Users can access datasets in the **Catalog Explorer** and through the **Dataset
 
 :::info External Datasets
 
-Unlike other datasets, external datasets are sourced from **third-party services** via the link you provide. They will be fetched into GOAT and stored there. These datasets can either be [Features](#1-features) or [Rasters](#2-rasters), each serving distinct purposes. The following external datasets are supported in GOAT: Web Map Service (WMS), Web Map Tile Service (WMTS), Web Feature Service (WFS), XYZ Tiles.
+Unlike other datasets, external datasets are sourced from **third-party services** via the link you provide. These datasets can either be [Features](#1-features) or [Rasters](#2-rasters), each serving distinct purposes. *External feature layers* will be fetched into GOAT and stored there, meanwhile *external raster layers* will be fetched live (to overlay on the map) but not stored.
+<p>
+</p>
+The following external datasets are supported in GOAT: Web Map Service (WMS), Web Map Tile Service (WMTS), Web Feature Service (WFS), XYZ Tiles.
 
 :::
 
@@ -24,16 +27,26 @@ Unlike other datasets, external datasets are sourced from **third-party services
 #### 1.1 Spatial Features
 Feature datasets serve as a dynamic repository of **spatial features**, such as points, lines, or polygons - they contaian spatially referenced geogrpahic features. Users can upload and utilize data from **Shapefiles**, **Geopackages**, **GeoJSON**, and **KML** files or add **WFS** link from an external URL. Feature datasets can be visualized on the map, [styled](../category/layer-styling), and used for analyses with any tools from the [toolbox](../category/toolbox). Furthermore, feature datasets can serve as a data basis for the [scenario creation](../category/scenarios).
 
+<p> </p>
+<div style={{ display: 'flex', flexDirection: 'column', alignItems: 'center' }}>
+  <img src={require('/img/data/spatial.png').default} alt="Home Interface Overview in GOAT" style={{ maxHeight: "750px", maxWidth: "750px", objectFit: "cover"}}/>
+</div>
+<p> </p>
+
 Within the GOAT framework, there are two different types of feature datasets, to address different aspects of geospatial functionality:
 
 - **Feature Dataset Standard:** This is the primary feature type that is automatically selected when a user uploads a file. It supports a range of formats including GeoJSON, GPKG, KML, and ZIP files. This dataset serves as the foundation for basic geospatial operations within GOAT.
 
-- **Feature Dataset Tool:** This dataset includes all datasets that have been produced using the tools available in GOAT. 
+- **Feature Dataset Tool:** This dataset includes all datasets that have been produced using the tools available in GOAT.
 
 
 #### 1.2. Non-spatial datasets
 **Tables** are **non-spatial datasets**, which differ from the geospatial datasets due to their lack of geographic reference points, therefore they cannot be visualized on the map. These datasets can be used for selected analysis and data management processes. Users can import table datasets in widely used formats such as **CSV** (Comma-Separated Values) and **XLSX** (Microsoft Excel Open XML Spreadsheet). 
 
+<div style={{ display: 'flex', flexDirection: 'column', alignItems: 'center' }}>
+  <img src={require('/img/data/table.png').default} alt="Home Interface Overview in GOAT" style={{ maxHeight: "750px", maxWidth: "750px", objectFit: "cover"}}/>
+</div>
+<p> </p>
 
 ### 2. Rasters
 
@@ -43,8 +56,7 @@ You cannot edit or run analyses on raster layers.
 
 :::
 
-#### 2.1. Imageries
-Imagery datasets are datasets that are provided by external sources such as **WMS** (Web Map Service) or **WMTS** (Web Map Tile Service). Therewith, a wide range of georeferenced map images, such as topographic maps, can be obtained from external servers and integrated into GOAT. While these images can be incorporated as static maps, it is important to note that they do not support analytical functions.
+Raster datasets are provided by external sources such as **WMS** (Web Map Service) or **WMTS** (Web Map Tile Service). Therewith, a wide range of georeferenced map images, such as topographic maps, can be obtained from external servers and integrated into GOAT. While these images can be incorporated as static maps, it is important to note that they do not support analytical functions.
 
 
 :::tip Note
@@ -53,16 +65,18 @@ The styling of these external image datasets is dependent on the external servic
 Consequently, the visual presentation of the map imagery, including elements such as color schemes and representation of geographic features, cannot be changed within the GOAT framework.
 
 :::
-
+<p> </p>
+<div style={{ display: 'flex', flexDirection: 'column', alignItems: 'center' }}>
+  <img src={require('/img/data/raster.png').default} alt="Home Interface Overview in GOAT" style={{ maxHeight: "750px", maxWidth: "750px", objectFit: "cover"}}/>
+</div>
+<p> </p>
 
 **WMS (Web Map Service)**
 This type of layer supports zooming and panning and it is ideal for basemaps, but the output is always a static image and gets loaded slower.
 
 **WMTS (Web Map Tile Service)**
 WMTS layers have pre-rendered, fixed sized tiles therefore it loads quickly, and you can zoom in and pan them quickly and smoothly. It is ideal for basemaps on big areas and best to use when you want to have consistent map-style.
 
-#### 2.2. Vector Tiles
-**Vector Tile Datasets** allow the integration of **MVT** (Mapbox Vector Tile) (e.g. mapbox://mapbox.mapbox-terrain-v2) into GOAT, allowing these efficient vector tiles to be used as static maps.
 
 **XYZ Tiles**
 This type of layer offers fast and efficient map zooming and panning because the tile is defined by their longitude (X), latitude (Y) and zoom level (Z) coordinates. It’s most often used when you need a fast-loading map that has the same performance on different zoom levels.
@@ -77,6 +91,9 @@ This type of layer offers fast and efficient map zooming and panning because the
 | **Scalability** |Less scalable | Highly scalable |
 |**Zoom level** | Variable, set by request parameters | Fixed zoom level, predetermined by the server |
 
+
+
+
 :::info INFO
-You can find out which data types are supported by GOAT under [**Data Types**](../data/data_types).
+You can find out which data types are supported by GOAT under [**Attribute Types**](../data/data_types).
 :::

docs/sharing/sharing.md

@@ -13,7 +13,7 @@ Sharing **does not duplicate** your data, only grants access to it.
 
 ## **Managing teams and members**
 
-In the [Settings](../workspace/settings.md) you can find the Teams you are part of, and you can see the members and their role. Teams are little departments of Organizations.
+In the [Settings](../workspace/settings.md) you can find the Teams you are part of, and you can see the members and their role. Teams can represent departments within an organization and allow you to group members in a way that suits your workflow.
 
 <div style={{ display: 'flex', flexDirection: 'column', alignItems: 'center' }}>
   <img src={require('/img/sharing/sharing_teams.png').default} alt="Home Interface Overview in GOAT" style={{ maxHeight: "750px", maxWidth: "750px", objectFit: "cover"}}/>
@@ -64,6 +64,18 @@ Click on the three-dot menu <img src={require('/img/map/filter/3dots.png').defau
 
 ## **Roles**
 
-:::info
-coming soon
+See the table to learn what each user can do within an Organization/Team and in a shared Dataset/Project.
+
+<p> </p>
+<div style={{ display: 'flex', flexDirection: 'column', alignItems: 'center' }}>
+  <img src={require('/img/sharing/sharing_roles_table.png').default} alt="Home Interface Overview in GOAT" style={{ maxHeight: "Auto", maxWidth: "Auto", objectFit: "cover"}}/>
+</div>
+<p> </p>
+
+:::info Important
+
+Deleting a dataset from a shared project **that you own** will cause it to be *deleted for other users as well*.
+
+**As an editor** if you delete a dataset or (layer from the) project, the *owner will still have it in their personal dataset*.
+
 :::

i18n/de/docusaurus-plugin-content-docs/current/data/data_basis.md

@@ -1,8 +1,8 @@
 ---
-sidebar_position: 1
+sidebar_position: 2
 ---
 
-# Unsere Datensätze
+# Eingebaute Datensätze
 
 
 ### Daten als elementare Grundlage für Analysen

i18n/de/docusaurus-plugin-content-docs/current/data/data_types.md

@@ -1,8 +1,8 @@
 ---
-sidebar_position: 2
+sidebar_position: 3
 ---
 
-# Datentypen
+# Attributetypen
 
 GOAT verarbeitet eine Vielzahl von Geometrietypen für räumliche Daten. Dies wird durch die Verwendung einer [PostgreSQL](https://www.postgresql.org/docs/) Datenbank mit der [PostGIS](https://postgis.net/documentation/) Erweiterung erreicht. GOAT speichert alle Geometrien im **PostGIS-Geometrietyp** (Der PostGIS-Geometrietyp ist eine Möglichkeit, verschiedene Formen und Standorte auf einer Karte innerhalb einer PostgreSQL-Datenbank zu speichern und zu bearbeiten. Er ermöglicht es, Details über Punkte (wie Wahrzeichen), Linien (wie Straßen) und Flächen (wie Bezirke) direkt in der Datenbank zu speichern. Alle Daten werden in der Datenbank Koordinatenreferenzsystem **EPSG:4326** gespeichert. Für Operationen, die Längen- oder Flächenmessungen beinhalten, wird jedoch der PostGIS-Geographietyp verwendet. Dieser Typ ermöglicht Berechnungen in Metern und bietet eine höhere Genauigkeit.