The core characteristics of information systems are defined by information and mathematical models; these are the plenitude of data and data analysis, and the intellectuality of a system. The article discusses different approaches to describing the information model, the types of implementation, and the practice methods of data integration. The definition and analysis are presented from a set of viewpoints, including business architecture, organization as communication, organization as document-flows, services and processes. The implementation is represented by the ER and RDF models. The data integration methods have been divided into three categories according to control type. In a controlled environment the integration can be implemented by creating an integrated data model, standardizing the data, assigning unified identifiers to basic model objects, as well as by tracking the data integrity for the systems included in the model. Three models are possible in a semi-controlled environment: the service model, data formats standardization and semantic integration. In an uncontrolled environment, integration methods involve linked open data and context based models. With the growing number of users and the transition to an open world, semantic principles are becoming more significant. Given the shift from systems integration to the semantic method, the role experts in various areas is growing substantially; these act as suppliers of context, interpreters of data, and the key participants in designing architectural solutions. Using the architectural principles of system implementation during the specification stage and subsequently following these principles through implementation and integration may result in a substantial reduction of the costs of modeling and implementing the system as a whole.