You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: CityGML Application Domain Extension (ADE): overview of developments 
Chapter Title:  Generics: the alternative to ADEs 
1. Abstract of Cited Paper (BIB001):  Abstract CityGML is the international standard of the Open Geospatial Consortium (OGC) for the representation and exchange of 3D city models. It defines the three-dimensional geometry, topology, semantics and appearance of the most relevant topographic objects in urban or regional contexts. These definitions are provided in different, well-defined Levels-of-Detail (multiresolution model). The focus of CityGML is on the semantical aspects of 3D city models, its structures, taxonomies and aggregations, allowing users to employ virtual 3D city models for advanced analysis and visualization tasks in a variety of application domains such as urban planning, indoor/outdoor pedestrian navigation, environmental simulations, cultural heritage, or facility management. This is in contrast to purely geometrical/graphical models such as KML, VRML, or X3D, which do not provide sufficient semantics. CityGML is based on the Geography Markup Language (GML), which provides a standardized geometry model. Due to this model and its well-defined semantics and structures, CityGML facilitates interoperable data exchange in the context of geo web services and spatial data infrastructures. Since its standardization in 2008, CityGML has become used on a worldwide scale: tools from notable companies in the geospatial field provide CityGML interfaces. Many applications and projects use this standard. CityGML is also having a strong impact on science: numerous approaches use CityGML, particularly its semantics, for disaster management, emergency responses, or energy-related applications as well as for visualizations, or they contribute to CityGML, improving its consistency and validity, or use CityGML, particularly its different Levels-of-Detail, as a source or target for generalizations. This paper gives an overview of CityGML, its underlying concepts, its Levels-of-Detail, how to extend it, its applications, its likely future development, and the role it plays in scientific research. Furthermore, its relationship to other standards from the fields of computer graphics and computer-aided architectural design and to the prospective INSPIRE model are discussed, as well as the impact CityGML has and is having on the software industry, on applications of 3D city models, and on science generally. 
2. Abstract of Cited Paper (BIB002):  Abstract Climate protection concepts for cities and regions are designed to establish CO2 emission baselines and develop measures for climate change mitigation. Up to now such concepts were based on aggregated consumption and emission data and only qualitative estimations of the effect of measures were possible. To better quantify the impact of mitigation measures, a large amount of data on the building stock is needed. Very powerful analysis possibilities for an energetic and economic evaluation of scenarios arise, if continuously growing data stock organized in geographical information systems are combined with simulation models of buildings and energy systems. In this work, 3D data models in CityGML format of the entire building stock of Ludwigsburg, a German county with 34 municipalities, were used and enriched with building’s year of construction and its function to allow an automatized quantifying the climate protection indicators. In this regard, the heating demand of each individual building in the region in the current state and after two refurbishment scenarios are calculated. In addition, the local solar photovoltaic potential is determined, as the exact size and orientation of each building surface is in the 3D model available. Besides, some new methodologies are described to better quantify the costs and benefits of CO2 mitigation strategies on a local or regional level and to support decision making.

Literature Review:
As mentioned in the introduction of this paper, the other official way of supporting the extension of the data model is through generic attributes (_genericAttribute) and generic objects (GenericCityObject). While this approach is not in focus of this paper, it is discussed here briefly for the sake of completeness and overview. The advantage of using generics is that it does not change the CityGML XML schema. An example from practice is the 3D city model of the Hague in the Netherlands BIB003 . Each building contains the attribute of the height of its eaves, expressed as a generic attribute, for example: <gen:doubleAttribute name="RelativeEavesHeight"> <gen:value>5.162</gen:value> </gen:doubleAttribute> The CityGML 2.0 Generics also has a Generic AttributeSet element which supports grouping of related generic attributes (_genericAttribute) under a common name BIB002 . This is akin to the concept of "PropertySets" (IfcPropertySets) in IFC to dynamically add properties to the objects (IfcObject). A GenericAttributeSet can contain any number of arbitrary generic attributes (_genericAttribute) and its name serves as an identifier for the entire set. It also has an optional codeSpace attribute to specify the authority, e.g. the organisation or community that defined a generic attribute set and its contained attributes. <gen:genericAttributeSet name="BaseHeights" codeSpace="https://www.example_authority.com"> <gen:doubleAttribute name="RelativeEavesHeight"> <gen:value>6.609</gen:value> </gen:doubleAttribute> <gen:doubleAttribute name="AbsoluteEavesHeight"> <gen:value>13.189</gen:value> </gen:doubleAttribute> <gen:doubleAttribute name="RelativeRidgeHeight"> <gen:value>9.587</gen:value> </gen:doubleAttribute> <gen:doubleAttribute name="AbsoluteRidgeHeight"> <gen:value>16.167</gen:value> </gen:doubleAttribute> </gen:genericAttributeSet> However, most of other aspects go in favour of ADEs. One of the key differences of ADE over Generics is that the former must be defined in an additional XML schema with a dedicated namespace. The CityGML standard denotes that this is an advantage for ADE because the extension is formally specified, and realisations can be validated against the schemas, which is not possible with generic objects and attributes. Further advantages of ADE over Generics is that the chance of naming conflicts is diminished, multiple ADEs can be used in the same dataset, and the fact that Generics might not be suitable for all situations given that there is a limited number of predefined data types that can be used BIB001 .