EFFECTIVE METHODS FOR ORGANIZATION AND PRESENTATION OF DIGITIZED CULTURAL HERITAGE

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1 International Journal of Mechanical Engineering and Technology (IJMET) Volume 9, Issue 4, April 2018, pp , Article ID: IJMET_09_04_113 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed EFFECTIVE METHODS FOR ORGANIZATION AND PRESENTATION OF DIGITIZED CULTURAL HERITAGE Galina Bogdanova, Todor Todorov and Nikolay Noev Institute of mathematics and informatics, BAS, 8 G.Bonchev str., Sofia, 1113, Bulgaria Todor Todorov "St. Cyril and St. Methodius" University of Veliko Tarnovo, 3, arh. G. Kozarev str., Veliko Tarnovo, 5000, Bulgaria ABSTRACT This paper presents the approaches and methods for creating, storing and presentation of digital resources in the field of cultural and historical heritage. Digital knowledge is described including context-based annotations of objects at particular subject area. Some major problems and solutions of digitalization of items, their processing and organization in a repository are highlighted. In the paper is also shown building of an OntoWiki structure that represents the developed semantic model. Finally we show how graph databases could be used as data management platform. Key words: semantic web; ontology; graph databases; OntoWiki structure; data management platform Cite this Article: Galina Bogdanova, Todor Todorov and Nikolay Noev, Effective Methods for Organization and Presentation of Digitized Cultural Heritage, International Journal of Mechanical Engineering and Technology, 9(4), 2018, pp INTRODUCTION The creation of new digital content of objects in the field of cultural heritage is an important task for the future progress of society. The subject area of this research is bell objects. They are artifacts of great artistic value in the field of cultural heritage. This research is a result of years of investigations and analyzes of approaches and methods of creating and presenting digital content in the field of cultural heritage, performed by many scientists of different areas and different on various applied-research projects [1], [2], [3] editor@iaeme.com

2 Galina Bogdanova, Todor Todorov and Nikolay Noev In this paper are presented modern approaches and methods of creating a digital content of objects in the field of cultural heritage. At first is shown building of semantic-based knowledge of specific area. At second are presented effective methods and platforms for storage and presentation of that knowledge. The aim of the OntoWiki Bell Ontology is to enrich the knowledge of church bell objects with describing places where they are. We develop semantic-based ontology using web-based platform. 2. SEMANTIC MODEL TO REPRESENT BELL KNOWLEDGE The Technologies used in the construction of a semantic network is designed to provide a formal description of concepts, terms and relationships within a given knowledge domain. To describe the data and their relationships using technology RDF, whose basic structure is called RDF-Count. RDF-count consists of the trio (or triplets) [4], [5]: 1) subject predicate object; The main content of RDF technology are resources, properties and statements. The resource is an object that has a unique identifier URI (Uniform Resource Identifier). The properties are a special kind of resources that describe the relations between other resources, such as made of, is cast, is set to and so on. Claims declare resource properties and represent the trio: 2) Resource attribute value; Figure 1 Scheme of relations of bells objects Ontology of bell objects is subject ontology and represents the knowledge about these objects. It aims to semantically describe bells with their characteristics, to define different specifications for them and make relations with other specialized semantic structures. An OWL ontology consists of individuals, properties, and classes, which roughly correspond to framework objects: 1) Individuals represent objects in the domain that we are interested in. For example an individual is each different bell. 2) Classes OWL classes are sets that contain individuals. For example, the class Bell would contain all the individuals that are bells in our domain of interest. Classes may be editor@iaeme.com

3 Effective Methods for Organization and Presentation of Digitized Cultural Heritage organized into a superclass-subclass hierarchy. In OWL classes are built up of descriptions that specify the conditions that must be satisfied by an individual for it to be a member of the class. 3) Properties Properties are binary relations between individuals. For example, the property has location might link the individual bell 1 AN to the individual St Aleksander Nevski cathedral, or the property has bell might link the individual St Aleksander Nevski cathedral to the individual bell 1 AN. Properties can have inverses. For example, the inverse of has location is is location of. Properties can be limited to having a single value i.e. to being functional. They can also be either transitive or symmetric. There are three main types of properties: Object properties, Datatype properties and Annotation properties. Figure 2 Object property Object properties are relationships between two individuals. On the Fig. 2: An Object property linking the individual bell 1 AN to the individual bell 1 AN beat. Figure 3 Annotation property Annotation properties can be used to add metadata to classes, individuals and properties. On the Fig. 3: An Annotation property, linking the class bell to the data literal (string) Geogri Ivanov. Figure 4 Datatype property Using the Datatype property, can add a restriction to the class states that all individuals of the class must meet specific restrictions. On the Fig. 4: A Datatype property linking the individual bell 1 AN to the data literal 140, which has a type of an xsd:float. Part of the content of knowledge of bell objects is supplemented by information from other areas. Relations of that content are mainly in the subject area between semantic substructures or outside this area with foreign ontological structures (as saints, metal molding or other). Next schema shows example of relations for St Ivan Rilski resource editor@iaeme.com

4 Galina Bogdanova, Todor Todorov and Nikolay Noev Figure 5 Example of relations between bell object and St Ivan Rilski resource In this example: individual bell has relation has art design. At property of class art design of that individual has value St Ivan Rilski. This value is related to other ontology structure at this subject area and has linked with Internet resource St Ivan Rilski, outside the bell subject area. Next code is show example of rule of relation between two individuals at different ontology structures. First is bell object (A) from bell ontology and its relations between properties bell type (T) and church bell (Ch) at same structure. Then there is relations between properties storyline (S), storyline type (St) and religious storyline (Rs) at substructure Ontology of religious and social themes depicted on bell objects. And if conditions are fulfilled then the rule is valid and enforced. IF bell object (A) has a relation has art design story-line (R1: A S), storyline (S) AND IF ( bell object (A) has relation has bell type (RA1: A T), bell type (T) AND bell type (T) has relation is bell type (RA2: T Ch), church bell (Ch) ) THEN storyline (S) has relations: ( storyline (S), has storyline type (RS1: S St), storyline type (St) AND storyline type (St), is storyline type (RS2: St Rs), religious storyline (Rs) ) 3. Building ontowiki bell ontology OntoWiki is a tool providing support for agile, distributed knowledge engineering scenarios. It enables intuitive authoring of semantic content, with an inline editing mode for editor@iaeme.com

5 Effective Methods for Organization and Presentation of Digitized Cultural Heritage editing RDF content, similar to WYSIWYG for text documents. Ontowiki enhances the browsing and retrieval by offering semantic enhanced search strategies [6]. First we create basic ontology classes according to the scheme described before in the paper. Next is an RDF code with example church, bell and person objects description. Figure 6 Temple object Figure 7 Bell object Figure 8 Person object Next we describe super-subclass relations of classes and object and data properties using OWL language. In this we also use some popular predefined ontology terms and relations. These are FOAF, Dublin Core, OntoWiki System Ontology, SKOS etc. On the next pictures are shown OntoWiki screens of imported ontology editor@iaeme.com

6 Galina Bogdanova, Todor Todorov and Nikolay Noev Figure 9 Temple object in OntoWiki Figure 10 Person object in OntoWiki editor@iaeme.com

7 Effective Methods for Organization and Presentation of Digitized Cultural Heritage Figure 11 Bell object in OntoWiki 4. USAGE OF NEO4J TO REPRESENT BELL ONTOLOGY NoSQL graph databases is a database that uses graph structures for semantic queries with nodes, edges and properties to represent and store data. Neo4j is a highly scalable, native graph database purpose-built to leverage not only data but also its relationships [7]. Graph database performance stays constant even as the data grows year over year. While most relational databases use a form of SQL as their query language, the graph database world is more varied so we'll look specifically at a single graph database query language Cypher. The system can execute direct queries written in Cypher. Cypher supports queries with parameters which are submitted as JSON [8]. Cypher query: MATCH (x { name: { startname }})-[r]-(friend) WHERE friend.name = { name } RETURN TYPE(r) Request: { query : MATCH (x { name: { startname }})-[r]-(friend) WHERE friend. name = { name } RETURN TYPE(r), params : { startname" : "I", editor@iaeme.com

8 Galina Bogdanova, Todor Todorov and Nikolay Noev "name" : "you" } } Response: { columns : [ "TYPE(r) ], "data" : [ [ "know" ]] } To import data from OWL file to Neo4j DB we use OWL API [9], [10]. Next is shown a pseudo code with explanation notes about basic steps. Step 1 Create an OWLOntologyManager object. The manager will load and save ontologies: m = OWLManager.createOWLOntologyManager() Load ontology from file into OWLOntology object: f = new File("bell.owl") o = m.loadontologyfromontologydocument(f) Next we create an instance of HermiT Reasoner and start import operations: reasoner = new Reasoner(o); Step 2 Create a starting node in Neo4j representing the owl:thing node. This is the root node of the graph we re going to create: thingnode = getorcreatenodewithuniquefactory("owl:thing") Step 3 Get all the classes defined in the ontology and add them to the graph: for (OWLClass c :o.getclassesinsignature(true)) { classnode =getorcreatenodewithuniquefactory(classstring)} Step 4 Create relations. If no super class exists then we link back to owl:thing. The relationship type used to express the rdf:type property is a custom one named isa : sc = reasoner.getsuperclasses(c, true) if (sc.isempty()) classnode.createrelationshipto(thingnode, DynamicRelationshipType.withName("isA")); else for ( parentowlnode: sc ) { parent = parentowlnode.getrepresentativeelement() parentnode = getorcreatenodewithuniquefactory(ps); classnode.createrelationshipto(parentnode, DynamicRelationshipType.withName("isA"));} editor@iaeme.com

9 Effective Methods for Organization and Presentation of Digitized Cultural Heritage Step 5 Now for each class we create nodes and link them back to their parent class: for ( in: reasoner.getinstances(c, true)) { individualnode = getorcreatenodewithuniquefactory(indstring) individualnode.createrelationshipto(classnode, DynamicRelationshipType.withName("isA")); } Step 6 Add object properties to the graph as node properties or relationships.: for (objectproperty: o.getobjectpropertiesinsignature()){ for(object:reasoner.getobjectpropertyvalues(i,objprop)) { objectnode = getorcreatenodewithuniquefactory(indnode.createrelationshipto(objectnode, DynamicRelationshipType.withName(reltype)) }} for (dataproperty: o.getdatapropertiesinsignature()) { for (object: reasoner.getdatapropertyvalues( i, dataprop){ indnode.setproperty(reltype, s); }} In our experiments we also used Neo4jphp (PHP library wrapping the Neo4j graph database) that supports executing both Cypher and Gremlin queries via REST. 5. CONCLUSION In the paper are investigated tools for ontological model representation. We use one such tool OntoWiki to build and use ontology of unique Bulgarian bells. We present an ontological model of knowledge in specific subject area in a field of cultural and historical heritage and describing bell objects. In detail is described the semantics of the subject area, by defining many features, characteristics, metadata, rules, classes of knowledge and relationships between them. We propose a graph database approach for storing and managing data in the ontological model. ACKNOWLEDGEMENTS This work has been partially supported by the National Science Fund of Bulgaria within the "Models and concepts of serious educational games through related multimedia resources of military and historical heritage" project, contract No. DM02/ REFERENCES [1] Bogdanova, G., Todorov, T. and Noev, N. Digitalization and security of Bulgarian folklore heritage archive. Proc. 11th International Conference on Computer Systems and Technology, 2010 [2] Bogdanova, G., Todorov, T. and Todorov, V. QPlus - computer package for coding theory research and education, International Journal of Computer Mathematics, 88(3) Taylor and Francis, 2001, editor@iaeme.com

10 Galina Bogdanova, Todor Todorov and Nikolay Noev [3] Bogdanova, G., Todorov, T. and Noev, N. Creating and Representing Semantic Knowledge of Bell Objects, International Journal of Applied Engineering Research, Vol.12(19), Research India Publications, 2017, [4] Paneva-Marinova, D., Pavlov, R. and Kotuzov, N. Approach for Analysis and Improved Usage of Digital Cultural Assets for Learning Purposes, Int. Journal Cybernetics and Information Technologies, 17(3), 2017, pp [5] Gruber, T. Towards Principles of the Design of Ontologies Used for Knowledge Sharing, International Journal of Human Computer Studies, 43, 1995, pp [6] Auer, S., Dietzold, S. and Riechert, T. OntoWiki a tool for social, semantic collaboration, The Semantic Web-ISWC, 2006 [7] Bruggen, R. Learning Neo4j, Packt Publishing, 2014 [8] Neo4j REST API documentation v3.0, [Online]. Available: [9] Neo4j and OWL, [Online]. Available: [10] OWL API, [Online]. Available: [11] Lata Gadhavi, Vishakha Modi and Madhuri Bhavsar. Proposed Ontology Framework for Dynamic Resource Provisioning on Public Cloud. International Journal of Advanced Research in Engineering and Technology, 7(2), 2016, pp [12] P. Kiran Kumar and Dr. V. Khanna, Software Data Graphs Using Ontology-Driven Software Evolution and Its Application. International Journal of Civil Engineering and Technology, 8(2), 2017, pp [13] Houda El Bouhissi, Mimoun Malki and Djamila Berramdane, Applying Semantic Web Services, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 2, March April (2013), pp [14] Sinan Adnan Diwan Alwan, Dr. Enas Hadi Salih, Ammar J.Fatah, Ontology Based Java Platform Personalization to Host Environment, International Journal of Computer Engineering & Technology (IJCET), Volume 5, Issue 7, July (2014), pp [15] Anitha, Prof. M.Padmavathamma, Toward a New Ontology of Nodelock Licensing Mechanism Patterns and Applicability Cuddapah, International Journal of Computer Engineering & Technology (IJCET), Volume 5, Issue 3, March (2014), pp editor@iaeme.com