Background: Data models are crucial for clinical research as they enable researchers to fully use the vast amount of clinical data stored in medical systems. Standardized data and well-defined relationships between data points are necessary to guarantee semantic interoperability. Using the Fast Healthcare Interoperability Resources (FHIR) standard for clinical data representation would be a practical methodology to enhance and accelerate interoperability and data availability for research. Objective: This research aims to provide a comprehensive overview of the state-of-the-art and current landscape in FHIR-based data models and structures. In addition, we intend to identify and discuss the tools, resources, limitations, and other critical aspects mentioned in the selected research papers. Methods: To ensure the extraction of reliable results, we followed the instructions of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. We analyzed the indexed articles in PubMed, Scopus, Web of Science, IEEE Xplore, the ACM Digital Library, and Google Scholar. After identifying, extracting, and assessing the quality and relevance of the articles, we synthesized the extracted data to identify common patterns, themes, and variations in the use of FHIR-based data models and structures across different studies. Results: On the basis of the reviewed articles, we could identify 2 main themes: dynamic (pipeline-based) and static data models. The articles were also categorized into health care use cases, including chronic diseases, COVID-19 and infectious diseases, cancer research, acute or intensive care, random and general medical notes, and other conditions. Furthermore, we summarized the important or common tools and approaches of the selected papers. These items included FHIR-based tools and frameworks, machine learning approaches, and data storage and security. The most common resource was “Observation” followed by “Condition” and “Patient.” The limitations and challenges of developing data models were categorized based on the issues of data integration, interoperability, standardization, performance, and scalability or generalizability. Conclusions: FHIR serves as a highly promising interoperability standard for developing real-world health care apps. The implementation of FHIR modeling for electronic health record data facilitates the integration, transmission, and analysis of data while also advancing translational research and phenotyping. Generally, FHIR-based exports of local data repositories improve data interoperability for systems and data warehouses across different settings. However, ongoing efforts to address existing limitations and challenges are essential for the successful implementation and integration of FHIR data models.

In this paper, we present an FP-like approach, named class point, which was conceived to estimate the size of object-oriented products. In particular, two measures are proposed, which are theoretically validated showing that they satisfy well-known properties necessary for size measures. An initial, empirical validation is also performed, meant to assess the usefulness and effectiveness of the proposed measures to predict the development effort of object-oriented systems. Moreover, a comparative analysis is carried out, taking into account several other size measures.

We have developed the visual language compiler-compiler (VLCC) system to automatically generate visual programming environments. VLCC is a grammar based system that can support implementation of any visual language by assisting the language designer in defining the language's graphical objects, syntax, and semantics. The final result of the generation process includes an integrated environment with a visual editor and a compiler for the defined visual language. In VLCC, graphical tools define visual languages to create both graphical objects and composition rules. Visual editors enable language designers to directly and visually manipulate the syntax of these languages. To capture the widest range of visual languages, the VLCC system can be configured for a specific language class. Different language classes can be characterized depending on their graphical objects' structure and on the way they can be composed. Also, box and arrow diagrams are defined for primitive objects with attaching points and for composition rules to join boxes and arrows at those attaching points. After choosing the visual language type to create, the designer can concentrate on language definition details. VLCC uses the positional grammar model as its underlying grammar formalism.<>

We present a framework for modeling visual notations and for generating the corresponding visual programming environments. The framework can be used for modeling the diagrammatic notations of software development methodologies, and to generate visual programming environments with CASE tools functionalities. This is accomplished through an underlying modeling process based on the visual notation syntactic model of eXtended Positional Grammars (XPG, for short), and the associated parsing methodology, XpLR. In particular, the process requires the modeling of the basic elements (visual symbols) of a visual notation, their syntactic properties, the relations between them, the syntactic rules to formally define the set of feasible visual sentences, and a set of semantic routines performing additional checks and translation tasks. Such a process is completely supported by the VLDesk system, which enables the automatic generation of an editor for drawing visual sentences, as well as a processor for their recognition, parsing, and translation into other notations.The proposed framework also provides the basis for the definition of a meta-CASE technology. In fact, we can customize the generated visual programming environment in terms of the supported visual notation, its syntactic properties, and the translation rules. We have used this framework to model several diagrammatic notations used in software development methodologies, including those of the Unified Modeling Language.