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Semantic Hierarchical Data Modeling
1980 - 1986
Conscious emphasis on semantic grounding and temporal integrity emerges as the core of data modeling, aiming to preserve meaning and timing across evolving datasets. Object-oriented approaches begin to influence modeling for engineering and CAD data, with early DBMS facilities supporting structured yet extensible representations. Extended non-first normal form hierarchies, dataflow architectures, and time-series methods drive scalable, distributed modeling and enable early forecasting and temporal analytics.
• Semantic grounding and temporal integrity drive early data modeling, emphasizing semantic data models, abstract data types, and time-preserving approaches across foundational works. [17] [8] [9] [10]
• Object-oriented (OO) data modeling emerges with OO approaches and database management system (DBMS) facilities for handling structured engineering entities and CAD (Computer-Aided Design) data architectures. [5] [12] [6]
• Non-first normal form (NF2) hierarchical data representations evolve with extended NF2 relations and integrated views across flat and hierarchical structures. [3] [2] [12]
• Dataflow (dataflow architectures) and parallel processing across distributed systems shape data modeling and scalable computation. [7] [20] [11]
• Time series analysis and forecasting anchor early data modeling with rainfall modeling and time-series methods. [15] [14] [18]
Semantic Object Modeling
1987 - 1994
Unified Object-Oriented Spatiotemporal Modeling
1995 - 2001
Unified Multimodal Data Modeling
2002 - 2008
Data-Intensive Spatial Modeling
2009 - 2015
Physics-Informed Data-Driven Modeling
2016 - 2023