dataesr/scientific-paragraphs-categorization huggingface dataset:
One commonly used data model to store and model building and other relevant objects (terrain surfaces, infrastructure, etc. ) in the context of Smart Cities applications is the 3D city model. An explicit XML-based exchange format for 3D city models is CityGML. It supports geometric description of 3D city model components, specifies semantics and topology information as well as stores multi-level of detail (LOD) information at different spatial and temporal scales  [8]. Furthermore, object modelling specifications can be shown at different LODs-ranging from simple building block models with flat roofs (LOD1) to detailed building models that include building interiors (LOD4) (Figure  1 ). ISPRS Int. J. Geo-Inf. 2018, 7, x FOR PEER REVIEW 2 of 18 example, in the case of the modelling of solar energy or PV potential, results could be aggregated at different temporal (hourly, daily, monthly, annual) resolutions.
Lately, static visualizations have been deemed tedious against the new technologies that support dynamic and interactive platforms, allowing users to navigate, zoom and even query data in real-time on a web-based application. The advancement of newer technologies such as WebGL  [4]  different proprietary and open-source software, tools and libraries enable the design and development of such interactive interfaces (Cesium. js [5], Glob3m  [6] ). On the other hand, although 3D web-based visualization has been a topic of increasing popularity in recent years, the cartographic principles that can be applied to such representations has not been fully investigated and standards have not been established  [3, 7]. One commonly used data model to store and model building and other relevant objects (terrain surfaces, infrastructure, etc.
) in the context of Smart Cities applications is the 3D city model. An explicit XML-based exchange format for 3D city models is CityGML. It supports geometric description of 3D city model components, specifies semantics and topology information as well as stores multi-level of detail (LOD) information at different spatial and temporal scales  [8]. Furthermore, object modelling specifications can be shown at different LODs-ranging from simple building block models with flat roofs (LOD1) to detailed building models that include building interiors (LOD4) (Figure  1 ). Multiple application domain extensions (ADE) covering various smart city research applications (energy, utility networks, sensor data) have been developed or are currently under development  [10, 11]. Thereby, the 3D city models act as a container for storing ICT relevant smart city data and multiple software architectures (both open-source and proprietary) have been developed to store and access all this relevant information.
Furthermore, the capabilities and limitations of using different data formats such as JSON, GeoJSON, Cesium Markup Language (CZML) and 3D Tiles in 4D web applications are evaluated. In the following section, an overview of the current trend of 3D and 4D web services, their implementation and applications are explained. Section 3 describes the system architecture of the proposed 4D application as well as the required data formats, software and technologies. Section 4 demonstrates the visualization and functional capabilities of the web interface with some energy simulation related case studies. The discussion of results and testing of performance of the application are summarized in Section 5. Finally, a conclusion is drawn by highlighting the limitation and future research issues in Section 6.
g. , CityGML format) are a key in urban energy modelling and several interfaces have been developed. For example, the Energy Atlas Berlin [27], discussed by  Kaden et al. ([28, 29] ), aims to visualize information such as heating energy needs, energy rehabilitation and geothermal energy in the city of Berlin in Germany. Their interface enables the visualization of LOD2 CityGML building data at multiple aggregation scales. Wendel et al. [7]  developed an interactive, plug-in free, web-based application that allows the visualization and interaction with semantical 3D geospatial data in the city of Karlsruhe in Germany with no dependencies on proprietary software or tools. It was based on a custom-made three. js JavaScript but was not capable of visualizing spatiotemporal data. The Sunshine project, an early adopter of Cesium implemented a cartographic display for urban services and energy consumption at the urban scale  [30].
For the purpose of direct visualization capabilities for semantic 3D city models, Chatuverdi et al. [31]  developed a web client based on KML/COLLADA exports from CityGML in an interactive interface for the 3DCityDB [32], a simplified database schema for CityGML in PostgreSQL  [33]. Based on that methodology, Kolbe et al. [34]  published the whole city model of New York (over 1 million buildings) in CityGML on a Cesium web-based interface that was further enriched by additional 3D city objects. On the topic of 4D web visualization, Resch et al. [3]  implemented a WebGL-based prototype to incorporate marine spatiotemporal data in a native 3D web-based interface. They also discussed the challenges in 4D visualization concept and discussed the lack of standards with temporal geo-data. Evangelidis et al.
[37] , where the user could interact with energy model outputs in an immersive manner  [38]. In contrast to the research-oriented developments presented in the sections above, there are also several propriety and commercial 3D interfaces that were developed in recent years. Most of these interfaces deal with the topic of smart cities, architectures, urban design, and urban planning. Three main WebGL-based commercial software frameworks are ESRI City Engine web viewer, Unity 3D  [17] , and Google Earth/Maps 3D  [39]. They provide comprehensive Application Programming Interfaces (API) for customized project development. For example, the Smart Dubai project  [40]  was develop on an ESRI platform that streams real-time 3D data to the public to help them understand places, projects and events around the city.
Proposed Architecture Among the available WebGL-based visualization frameworks and libraries, Cesium is most suitable to create virtual globes with time dynamic 3D visualization of geospatial data as it allows native discrete temporal data support. In addition, it includes various geospatial functionalities such as terrain visualization and imagery layers by using geospatial web services and standards. Cesium is an open-source JavaScript package supporting the presentation of 3D contents within the web browser where users can dynamically switch between 3D globe visualization and 2D map projection. It utilizes WebGL to provide hardware acceleration and plugin independence and provides cross-platform and cross-browser functionalities  [31]. The architecture of the proposed 4D visualization interface is designed on Cesium's existing layers  [47]  (widgets, DataSources, Scene, Renderer and Core) and features (Figure  2 ).
It consists of three main parts: data preparation, implementation and visualization. Data preparation: The proposed dynamic visualization interface supports different data formats such as CityGML, JSON, GeoJSON, Cesium Markup Language (CZML) and Cesium 3D Tiles. Each of these formats have specific capabilities and therefore the choice of the data format depends on the functionalities/use and the level of details of the original CityGML data. CityGML data (LOD1 and LOD2) is imported into the PostgreSQL databases as tables via 3DCityDatabase Import/Exporter to run energy simulations on them. The energy simulation results are saved in the same database as separate tables  [2, 48]. To visualize the results in the proposed interface, several Python scripts are written in Eclipse environment in order to convert the database tables into the desired format.
Implementation: Cesium. js (version 1. 45) is deployed on a local server to customize and visualize the energy simulation results. Cesium depends on a web server to host maps and files. It does not have any server requirements but Node. js is used for this interface. After setting up the local host connection, a programming development environment is created using Brackets, where the Cesium Viewer is initially added to the JavaScript code to initiate the development of 4D CANVAS. Afterwards, further analytical functionalities and time-dependent visualization are implemented using scripting languages (see Section 3). Visualization: The proposed interface is then deployed in both personal computers (desktops, laptops) and in multi-touch tablets. A summary of the functionalities of the different scripting languages (e.
g. , python, HTML5 [49], CSS, JavaScript), libraries/API (AMCharts, JQuery UI, Geostats), software (3D City Database, pgAdmin, Eclipse, FME), and data formats (CZML, JSON, etc. ) are explained in Table  1. ISPRS Int. J. Geo-Inf. 2018, 7, x FOR PEER REVIEW 5 of 18 Cesium Viewer is initially added to the JavaScript code to initiate the development of 4D CANVAS. Afterwards, further analytical functionalities and time-dependent visualization are implemented using scripting languages (see Section 3). Visualization: The proposed interface is then deployed in both personal computers (desktops, laptops) and in multi-touch tablets. A summary of the functionalities of the different scripting languages (e. g. , python, HTML5 [49], CSS, JavaScript), libraries/API (AMCharts, JQuery UI, Geostats), software (3D City Database, pgAdmin, Eclipse, FME), and data formats (CZML, JSON, etc.
Software 3D City Database Importer/Exporter A Java-based front-end that allows importing CityGML data to the database. pgAdmin III Used for viewing the database tables. Eclipse Oxygen. 2 A programming environment used for Python coding with PyDev extension. Brackets 1. 12 A programming environment used for HTML, CSS, and JavaScript coding. FME Used to facilitate the conversion from GeoJSON to Cesium 3D Tiles.
Both are based on a JSON syntax and are easily understood. CZML is similar to KML format but is adapted to Cesium products. 3D Tiles is an open specification for streaming massive heterogeneous 3D geospatial datasets such as imagery, 3D contents including buildings, trees, point clouds, and vector data  [50]. CZML is the only format for visualizing dynamic (i. e. , hourly or monthly temporal) data but it has many limitations, especially regarding coarser level of details and the increased data volume. The format is rather complex and raises multiple problems (discussed in Section 5. 1). A detailed use of CZML properties to describe time-varying characteristics of geospatial objects, and the use of CZML to support streaming data are explained in Zhu et al. [51] , while the relevant applications, academic influences, and future developments of CZML are explored in Zhu et al.
The model produces monthly heating and cooling energy needs and uses. Both models are implemented in an open-source software architecture. In 4D CANVAS, these outputs are visualized as time-static (e. g. , annual) and time-dynamic (e. g. , hourly, daily or monthly) manners. Hourly solar irradiance or energy production produces 8760 values (each hour throughout the year) for each surface of the building, which makes it difficult to display such data (explained in Section 5) in an interactive way. Therefore, hourly results are aggregated to monthly and annual level or are visualized for limited number of surface objects. For annual data, GeoJSON is used when total number of building surfaces is less than thirty thousand, otherwise, 3D Tiles is used for its faster rendering service. They are shown in a static manner with thematic mapping/color schemes on the building surfaces.
Discussion of Results Free and open-source Cesium software: This study tested the capability of utilizing the open-source Cesium. js library in visualizing 4D data of higher spatiotemporal resolutions. The capability of identifying individual building-surfaces of different LODs (as in the CityGML data) and providing their corresponding attributes from tables, was very beneficial to display detailed information about each building object. The use of the CZML format facilitated the dynamic visualization of temporal attributes in the monthly and daily data. Furthermore, the main advantage of Cesium was the easy integrating of different libraries and API, such as AmCharts and Geostats, which allowed further analytical functions to be implemented into the interface. Data format evaluation: This research has tested and evaluated different data formats relevant to the energy simulation application (Figure  8 ).
GeoJSON and 3D Tiles showed similar capabilities when static geospatial visualization is chosen and the data is not large in volume. Both can visualize the LOD1 and LOD2 datasets. However, GeoJSON does not support tiling, and therefore attempts to load the complete set of data into the viewer at a time. A function was developed to loop through the whole data to perform statistical calculations such as maximum, minimum, variance, mean and standard deviation, which are used for data classifications. Nevertheless, for larger volume of LOD2 datasets, such effort often caused to crush the browser. In contrast, 3D Tiles is a suitable alternative to efficiently visualize large volume of data due to its tiling property but it restricts the display of detailed statistical information of the individual building surfaces, mainly due to its frequent re-rending.
Discussion of Results Free and open-source Cesium software: This study tested the capability of utilizing the opensource Cesium. js library in visualizing 4D data of higher spatiotemporal resolutions. The capability of identifying individual building-surfaces of different LODs (as in the CityGML data) and providing their corresponding attributes from tables, was very beneficial to display detailed information about each building object. The use of the CZML format facilitated the dynamic visualization of temporal attributes in the monthly and daily data. Furthermore, the main advantage of Cesium was the easy integrating of different libraries and API, such as AmCharts and Geostats, which allowed further analytical functions to be implemented into the interface. Data format evaluation: This research has tested and evaluated different data formats relevant to the energy simulation application (Figure  8 ).
Every time the camera position is changed, the data is reloaded into the viewer and different statistical values are obtained only for the current view. CZML is the only suitable format used to visualize temporal variations in data. It does not support tiling and it can visualize LOD1 buildings only. This format is adequate to represent monthly and daily data. Due to the structure of the file, the hourly representation of data throughout a year (8760 values) for a large number of buildings (as in this application) resulted a massive file size and therefore, found unsuitable to visualize at hourly time step. However, hourly data for a few days could be easily visualized on some buildings. Integration of popular geodatabase and data formats: Three main types of geodatabases (GDB) supported by both ArcGIS and QGIS are File Geodatabases, Personal Geodatabases and ArcSDE Geodatabases.
These popular GDBs cannot be directly integrated into the Cesium application and need to be converted to Cesium 3D Tiles. Besides the proprietary data formats of Cesium (CZML, quantized-mesh, 3DTiles), it also supports some external formats such as gITF, GeoJSON, TopoJSON, Collada, ArcGIS ImageLayer, and google's KML, etc. [55]. Other popular data formats need to be Integration of popular geodatabase and data formats: Three main types of geodatabases (GDB) supported by both ArcGIS and QGIS are File Geodatabases, Personal Geodatabases and ArcSDE Geodatabases. These popular GDBs cannot be directly integrated into the Cesium application and need to be converted to Cesium 3D Tiles. Besides the proprietary data formats of Cesium (CZML, quantized-mesh, 3DTiles), it also supports some external formats such as gITF, GeoJSON, TopoJSON, Collada, ArcGIS ImageLayer, and google's KML, etc.
It is also helpful to know the exact number of features and hourly data points that can be visualized without risking the browser to crash. Moreover, as some energy models produce results at building surface level (e. g. , PV energy), the CZML format can be adapted to cope with it. Automatize data conversion and integration into application: The energy simulation results are saved in the PostgreSQL databases as tables. They are, at first, manually converted using python scripts into required data formats and then integrated/loaded into the web application (see Figure  2 ). This process can be automatized through on-the-fly data conversion within the web application and thus avoid the data conversion steps (Figure  10 ). The complexities associated with the visualization of hourly dynamic data can be resolved by modifying the JavaScripts and Html files to smoothly animate the hourly results.
It is also helpful to know the exact number of features and hourly data points that can be visualized without risking the browser to crash. Moreover, as some energy models produce results at building surface level (e. g. , PV energy), the CZML format can be adapted to cope with it. Automatize data conversion and integration into application: The energy simulation results are saved in the PostgreSQL databases as tables. They are, at first, manually converted using python scripts into required data formats and then integrated/loaded into the web application (see Figure  2 ). This process can be automatized through on-the-fly data conversion within the web application and thus avoid the data conversion steps (Figure  10 ). From a technical point of view, it was investigated whether such process improves the application performance.
Performance Testing The performance of the 4D CANVAS web application and the GUI were tested both desktop screens and a touchscreen tablet. In this regard, some popular web-browsers such as Mozilla Firefox (v60. 0. 1), Google Chrome (v66. 0. 3359. 181), Microsoft Internet Explorer (v11. 1088. 15063. 0) were considered to observe possible configuration changes in the user interface in terms of UI content scroll performance, UI latency/response time, Finger tracking and UI functionality. In many cases, Chrome From a technical point of view, it was investigated whether such process improves the application performance. The primary advantage of processing on-the-fly data conversion within the 4D CANVAS application is the need of less software and python scripts, but this approach has some limitations in terms of long loading-time of the data and thus delayed visualization.
Performance Testing The performance of the 4D CANVAS web application and the GUI were tested both desktop screens and a touchscreen tablet. In this regard, some popular web-browsers such as Mozilla Firefox (v60. 0. 1), Google Chrome (v66. 0. 3359. 181), Microsoft Internet Explorer (v11. 1088. 15063. 0) were considered to observe possible configuration changes in the user interface in terms of UI content scroll performance, UI latency/response time, Finger tracking and UI functionality. In many cases, Chrome had shown faster and smoother response during navigation with the Cesium globe, in comparison to Firefox. Firefox had displayed a more robust performance in loading large volume of data. However, JQuery functionality required some code adjustment to make use of it in the Firefox browsers.
Summary In this research, the 4D CANVAS web application was developed based on the open-source Cesium virtual globe. Multiple energy simulation results such as techno-economic PV potential or energy needs of the 3D buildings are dynamically visualized in the context of different Asian and European cities. Several analytical functionalities are also integrated and a GUI is built to allow user explorative analyses of results. This study demonstrates that with widely available 3D datasets and technological advancements in virtual globe software frameworks, many different smart city applications can be integrated into the application.
Tileset refers to all the object/geometry (e. g. , surfaces) that are visible at a particular view in the globe. Once the particular tileset is visible on the globe, it fetches the required values from the corresponding b3dm file to be visualized. This way it reduces the loading and displaying large amount of data at a time. CZML is able to visualize 4D data, but it (a) cannot display tilted roofs of the buildings and degrades them into flat roofs. Moreover; (b) the file size also becomes too large. In case of hourly irradiance of the Karlsruhe Buildings, the size is 3. 4 GB, which disabled the browser to respond once the data was added to the Cesium Viewer. Immutable terrain exaggeration is a problem in Cesium. In cases where original CityGML data had terrain information, the terrain provider is utilized with an exaggeration parameter.
CZML is able to visualize 4D data, but it (a) cannot display tilted roofs of the buildings and degrades them into flat roofs. Moreover; (b) the file size also becomes too large. In case of hourly irradiance of the Karlsruhe Buildings, the size is 3. 4 GB, which disabled the browser to respond once the data was added to the Cesium Viewer. Immutable terrain exaggeration is a problem in Cesium. In cases where original CityGML data had terrain information, the terrain provider is utilized with an exaggeration parameter. However this function is still under development and is currently immutable. It can only be initially set with the first constructor options of the Cesium Viewer. As a result, terrain exaggeration cannot be modified in real-time. It imposes multiple problems when different exaggeration settings need to be set in the viewer.
Future Research In the future, additional statistical analysis tools can be developed. For example, in this current application, the energy simulation results are visualized on 3D buildings and their surfaces. A tool can be developed to help users to aggregate/add/summarize results of particular surface type (e. g. , roofs facing south only) and visualize in 4D. A JavaScript function can loop through the data set and highlight all such geometries and returns their statistical information. 3D Tiles can be directly extracted from the PostgreSQL database using the FME translator. In this regard, the feasibility of conversion of 3D Tiles can be investigated by writing a python script, which can connect to PostgreSQL database to get it converted. The hourly visualization of 3D dataset for a small number of objects is already demonstrated in this paper.
Acknowledgments: We are grateful to EDF R&D and EIFER for funding this research. Some of the Energy Simulation results were performed in the  Modélisation Urbaine Gerland (MUG)  and  Resource Urbanisms Project. We are grateful to the respective funding agencies and project members. Our heartiest gratitude to the  City of Lyon and Laboratoire LIRIS  for providing the 3D city model of Lyon. We would like to thank  City of Karlsruhe  for the permission of using the CityGML data. We also acknowledge  Wanji Zhu ,  Mario Ammann ,  Francisco Marzabal ,  Alexander Simons  and  Monica Feis  for their support in application development. Finally, our sincere gratitude extends to the editors and two anonymous referees for their insightful comments, which helped us to improve the manuscript.