A Framework for Maritime Domain Interoperability with Formal Concept Analysis

Interoperability of information systems is the main goal of engineers in 21 st century. Maritime domain interoperability is the main requirement of civilian and military agencies for common understanding of the activities in maritime environment. For achieving maritime domain awareness, interoperability between heterogeneous information systems is required, which in turn requires these systems to be connected physically, syntactically and semantically. Alliance forces and law enforcement agencies depend heavily on maritime information systems in their operational activities for decision support and anomaly detection. In our work, formal concept analysis (FCA) is proposed as the core of decision support and anomaly detection in maritime domain. Concept lattices are generated and concept exploration methods are utilized for maritime domain awareness requirements of the alliance. Finally; in this paper, a new framework for maritime domain interoperability is proposed, which properly maps to phases of Semantic Interoperability Framework (SILF) by generation of maritime data model, mapping of the maritime context, utilization of FCA for anomaly detection and upgrade to the national/alliance data model. The proposed framework aims to achieve maritime domain interoperability in a sense of an electronic library approach that can also form the basis for Common Information Sharing Environment (CISE) of European Union (EU). This work is accomplished in the context of Coastal Surveillance Radar System project requirements for the Turkish maritime information system. 1.0 INTRODUCTION The development of communication technologies has led to the requirement of semantic information exchange between computer systems. This has given rise to a new question: “What is semantic information for a computer system? ” For two or more systems to be interoperable, the language of the shared information has to be compromised by all parties and all systems need to fully understand each other. Situational awareness, which is the perception, comprehension and projection [1] of the real world from information systems’ point of view, can only be achieved by the semantic interoperability of the systems. Among the research areas for bringing situational awareness to reality, Maritime Situational Awareness (MSA) steps forward as a promising concept for member nations’ information sharing requirements for maritime interoperability issues. In this paper, we focus on the importance of interoperability by giving examples from maritime situational awareness with semantic information exchange, and introduce the concept of anomaly detection in maritime domain. Then we propose a theoretical approach for maritime situational awareness concept analysis by defining maritime ontologies as context, utilizing concept exploration as a tool for dynamically aligning the maritime situational awareness concept lattice. Maritime concept exploration browses through the concepts, which give the maritime situational awareness operator the ability to locate required vessels, RTO-MP-IST-101 10 1 A Framework for Maritime Domain Interoperability with Formal Concept Analysis reach the related information and analyze the maritime situation. Afterwards we introduce the framework for maritime domain interoperability and identify the sub domains with different operational picture requirements. Lastly, we finalize the paper by mapping the phases of Semantic Interoperability Framework (SILF) [2] to the phases of our Framework for Maritime Domain Interoperability with Formal Concept Analysis and conclude with our suggestions and requirements for establishing a maritime information system. 2.0 MSA & SEMANTIC INFORMATION EXCHANGE According to NATO, “MSA is an enabling capability which seeks to deliver the required information superiority in the maritime environment to achieve a common understanding of the maritime situation in order to increase effectiveness in the planning and conduct of operations. " where "The maritime environment comprises the oceans, seas, bays, estuaries, waterways, coastal regions and ports. " Generation of the maritime situational awareness requires the semantic communication between member nations’ maritime information systems which leads to a full semantic integration of systems’, which is referred as interoperability of systems. NATO definition of interoperability is “The ability to act together coherently, effectively and efficiently to achieve Allied tactical, operational and strategic objectives” and the NATO Architecture Framework (NAF) defines interoperability as “The ability to operate in synergy in the execution of assigned tasks” [3]. Consequently, to enable the member nations’ information systems to act together and operate in synergy, information systems need to have a shared communication medium and a fully understood context, in which the systems share information semantically for maritime situational awareness [4]. The shared medium requires a “common language” between the systems, which needs to have a well defined form, meaning and language in context where linguistics is defined as “The study of language in general and of particular languages, their structure, grammar, and history”. From the information sharing perspective, grammar of the language has an important role. Grammar defines the semantics of information sharing, where shared datagrams are understood as they are intended to. Words in a language, both in a natural language or a computer language, gain different meanings as they are used. For instance, words are used as attributes to real world objects, such as an adjective in front of a noun; and, as new phrases are created, the phrases gain different meanings. We need to find a formal way of creating phrases from words by defining their relations, and build semantic sentences from these phrases. Building the sentences requires the logical selection of the words and phrases, adjectives and nouns in natural languages, similar to objects and attributes in computer languages, by a formal methodology. For situational awareness, we will model this methodology in information systems by generation of formal context and performing formal concept analysis on this context. Formal concept analysis is proposed in this paper as the main tool for anomaly detection in maritime domain. 3.0 ANOMALY DETECTION IN MARITIME DOMAIN Maritime domain consists of several and multi-disciplinary branches, each of which deals with completely different data sets. To achieve Maritime Situational Awareness, each data set needs to be thoroughly analyzed by a formal way. The results of the formal analysis are to be used in not only improving the daily operations such as optimization of maritime commercial vessel routes against piracy operations but also for maritime anomaly detection. Anomaly detection refers to detecting patterns in a given data set that do not conform to an established normal behavior. The patterns thus detected are called anomalies and often translate to critical and actionable information in several application domains. In maritime domain, a vessel coming from Country A, with a load of Substance 1, may be referred to as a normal behavior, while the same vessel coming A Framework for Maritime Domain Interoperability with Formal Concept Analysis 10 2 RTO-MP-IST-101 from Country B with a load of Substance 1 may be referred to as an anomaly. Our main effort in this paper is to automate the detection of anomalies in maritime domain, through the analyses of the knowledge base generated by domain experts. The knowledge base shall include the experiences of the domain experts and shall be temporally updated according to new maritime incidents, such as the same vessel coming from Country A with a load of Substance 1 may be referred to as an anomaly by time, if the ship gains a criminal record. Supposedly, a cargo vessel V1, coming from country U1 with a load of white chalk S1 is a normal behavior. But later on, the coast guard receives a notice stating that the load is not white chalk, but illicit cargo. After this event, all cargo vessels coming from country U1 with a load of white chalk becomes an anomaly for a predefined time frame, keeping in mind that the suspicion includes all known related commercial routes, vessel personal lists and ship owners. This suspicious behavior of all related vessels need to be analyzed and all vessels of interest shall be classified into a set of suspicious vessels, each set containing a different property of vessels such as vessels from Country U1, ships with crew C1, ships with load of white chalk S1. We need to find a formal way of creating data sets and a formal way of navigation through these sets so that we can focus on the suspicious vessels and semi-automate the anomaly detection process. For the arrestment of the offenders in maritime domain, the maritime governmental authorities need to gather all maritime related data into a database, and the information in the database shall be automatically analyzed 24/7 for suspicious behavior, leading to law enforcement operations. One procedure for behavioral analysis by the usage of the time varying knowledge base is called Formal Concept Analysis. 4.0 FORMAL CONCEPT ANALYSIS FOR ANOMALY DETECTION Formal concept analysis is a theory of data analysis which identifies conceptual structures among data sets, by usage of contexts and concept lattices [5]. This method intends to make ontology building more efficient and allows for discovering necessity for new concepts and relations in an ontology, which leads to an ontology that has these entities described in a way suitable for knowledge exchange. Member nations’ semantic information sharing objectives and interoperability goals will be achieved by forming the maritime ontology from the formal context and analysis of the concept lattice [6]. 4.1 FORMAL CONTEXT Before analyzing and sharing the maritime information, all the v