What Is Informatics?

Informatics is the study of information: how it is represented, processed, communicated, and used by both natural systems and engineered artifacts. The field is concerned with the methods for acquiring, storing, retrieving, transforming, and reasoning about information, and with the role that computational systems play in each of these activities. Informatics draws on computer science, cognitive science, mathematics, and artificial intelligence, and applies its methods to virtually every domain in which information processing is central, from genomics and healthcare to materials science and manufacturing. The University of Edinburgh's School of Informatics, one of the leading programs in the field, defines informatics as the study of "the transformation of information, whether by computation or communication, whether by organisms or artefacts," capturing its dual focus on natural and artificial information systems.

Unlike computer science, which is primarily concerned with the design and analysis of computing systems, informatics foregrounds the information artifact itself: the structure of data, the semantics of representations, and the context in which information is created, shared, and interpreted. This broader scope means that informatics regularly engages with social, biological, and organizational systems in addition to technical ones.

Computational and Cognitive Foundations

Informatics rests on two disciplinary pillars. The computational pillar, drawn from computer science and mathematics, provides the formal tools for information representation, algorithm design, data modeling, and system architecture. Database theory, information retrieval, formal languages, and knowledge representation all contribute to this foundation. The cognitive pillar, drawn from cognitive science and psychology, provides models of how humans and other cognitive agents process, store, and retrieve information, which in turn informs the design of interfaces, recommendation systems, and collaborative platforms. Artificial intelligence connects the two by building systems that replicate or extend cognitive functions computationally. The ACM Europe Council and Informatics Europe have formally described informatics as synonymous with computer science in the context of the discipline's academic and professional organization, reflecting the field's roots in formal computational methods.

Bioinformatics and Health Informatics

Two of the most established sub-disciplines within informatics are bioinformatics and health informatics. Bioinformatics applies computational methods to biological data, particularly the large-scale sequence, structure, and expression datasets generated by genomic and proteomic technologies. Sequence alignment algorithms, protein structure prediction methods, and phylogenetic inference tools are representative examples. Health informatics focuses on the management and use of patient and population health data within clinical and public health systems, encompassing electronic health records, clinical decision support, and disease surveillance platforms. The NCBI PubMed database is a major institutional resource for health and biomedical informatics research, indexing over 37 million citations and providing structured metadata used in bibliometric and text-mining studies.

Computational Materials Science and Domain Informatics

Informatics methods have been extended to materials science through a field called computational materials science informatics, or materials informatics, which applies machine learning and data management techniques to materials discovery and characterization. Rather than relying solely on physics-based simulation, materials informatics extracts property-structure relationships from large experimental and computational datasets, accelerating the identification of candidates for specific applications. The Materials Project at Lawrence Berkeley National Laboratory, for instance, provides an open database of computed properties for tens of thousands of inorganic compounds, enabling data-driven materials discovery through computational informatics. This domain exemplifies a broader pattern: informatics as an enabling layer that any field can adopt when its data becomes too large and complex for manual analysis.

Applications

Informatics has applications in a range of fields, including:

• Clinical decision support and electronic health record management
• Genomic sequence analysis and precision medicine
• Materials discovery through data-driven property prediction
• Digital library systems and information retrieval at scale
• Educational technology and learning analytics platforms