Conceptualization of Methods and Experiments in Data Intensive Research Domains

• Published in: Data Analytics and Management in Data Intensive Domains Vol. 706; pp. 3 - 17
• Main Authors: Skvortsov, Nikolay A., Kalinichenko, Leonid A., Kovalev, Dmitry Yu
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2017; Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: Conceptual modeling; Conceptual schema; FAIR data principles; Ontology; Research experiment; Research infrastructure
• ISBN: 3319571346; 9783319571348
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-319-57135-5_1

Nowadays research of various scopes especially in natural sciences requires manipulation of big volumes of data generated by observation, experiments and modeling. Organization of data-intensive research assumes definition of domain specifications including concepts (specified by ontologies) and formal representation of data describing domain objects and their behavior (using conceptual schemes), shared and maintained by communities working in the respective domains. Research infrastructures are based on domain specifications and provide methods applied to such specifications, collected and developed by research communities. Tools for organizing experiments in research infrastructures are also supported by conceptual specifications of measuring and investigating object properties, applying the research methods, describing and testing the hypotheses. Astronomy as a sample data intensive domain is chosen to demonstrate building of conceptual specifications and usage of them for data analysis.