An introduction to Graph Data Management

A graph database is a database where the data structures for the schema and/or instances are modeled as a (labeled)(directed) graph or generalizations of it, and where querying is expressed by graph-oriented operations and type constructors. In this article we present the basic notions of graph databases, give an historical overview of its main development, and study the main current systems that implement them

The PSN tribe

AbstractThe paper reviews the history, premises, research results and applications of the Procedural Semantic Network (hereafter PSN) formalism and two of its descendants, Taxis and Telos. The primary goal for the PSN project was to develop a knowledge representation formalism which combined gracefully semantic networks and procedural representations. After an initial proposal which set out a framework for the integration of these two types of representations [1], a number of features were investigated, including the treatment of contexts, the declarative representation of slots and procedures and several others. In parallel, attempts were made to apply some of the representation ideas embodied in PSN to the task of developing suitable languages for the early stages of information system design. During these stages, the designer is concerned with understanding the problem at hand and then proceeding with the specification of an initial conceptual design of an information system that meets stated requirements. Taxis and Telos were the result of this effort. Their features are outlined, along with a rationale for the differences between the three formalisms

Comparative analysis of PropertyFirst vs. EntityFirst modeling approaches in graph databases

While relational databases still hold the primary position in the database technology domain, and have been for the longest time of any Computer Science technology has since its inception, for the first time the relational databases now have valid and worthy opponent in the NoSQL database movement. NoSQL databases, even though not many people have heard of them, with a significant number of Computer Science people included, have spread rapidly in many shapes and forms and have done so in quite a chaotic fashion. Similarly to the way they appeared and spread, design and modeling for them have been undertaken in an unstructured manner. Currently they are subcategorized in 4 main groups as: Key-value stores, Column Family stores, Document stores and Graph databases. In this thesis, different modeling approaches for graph databases, applied to the same domain are analyzed and compared, especially from a design perspective. The database selected here as the implemented technology is Neo4J by Neo Technologies and is a directed property graph database, which means that relationships between its data entities must have a starting and ending (or source and destination) node. This research provides an overview of two competing modeling approaches and evaluates them in a context of a real world example. The work done here shows that both of these modeling approaches are valid and that it is possible to fully develop a data model based on the same domain data with both approaches and that both can be used later to support application access in a similar fashion. One of the models provides for faster access to data, but at a cost of higher maintenance and increased complexity

Entity Relationship Approach to Knowledge Base Systems.

A unified framework for knowledge base systems is proposed based on Entity-Relationship (ER) approach. Following the analysis and the specification of the real-world using Entity-Relationship approach, the knowledge base is implemented as a first-order logic system, a production system, or a frame-based system by mapping the appropriate symbolic data structures. An approach for analyzing and specifying real-world perceptions must provide appropriate semantic primitives. Therefore, a justification is provided for the semantic primitives proposed in Entity-Relationship approach by considering the fundamental issues in perception. A notation that allows Entity-Relationship approach to be used as a holistic representation is presented. Translation rules are provided for the conversion of ER-diagrams into symbolic data structures of first-order logic systems, production systems, and frame-based systems. The feasibility of using Entity-Relationship approach to support a natural language front-end of a knowledge base system is examined by analyzing the representation of surface and deep structures of a sentence in Entity-Relationship approach

Semantic Database Model Language (SDML): grammar specification and parser

Call number: LD2668 .T4 1986 L364Master of ScienceComputing and Information Science

Evaluation of Functional Data Models for Database Design and Use

The problems of design, operation, and maintenance of databases using the three most popular database management systems (Hierarchical, CQDASYL/DBTG, and Relational) are well known. Users wishing to use these systems have to make conscious and often complex mappings between the real-world structures and the data structuring options (data models) provided by these systems. In addition, much of the semantics associated with the data either does not get expressed at all or gets embedded procedurally in application programs in an ad-hoc way. In recent years, a large number of data models (called semantic data models) have been proposed with the aim of simplifying database design and use. However, the lack of usable implementations of these proposals has so far inhibited the widespread use of these concepts. The present work reports on an effort to evaluate and extend one such semantic model by means of an implementation. It is based on the functional data model proposed earlier by Shipman[SHIP81). We call this 'Extended Functional Data Model' (EFDM). EFDM, like Shipman's proposals, is a marriage of three of the advanced modelling concepts found in both database and artificial intelligence research: the concept of entity to represent an object in the real world, the concept of type hierarchy among entity types, and the concept of derived data for modelling procedural knowledge. The functional notation of the model lends itself to high level data manipulation languages. The data selection in these languages is expressed simply as function application. Further, the functional approach makes it possible to incorporate general purpose computation facilities in the data languages without having to embed them in procedural languages. In addition to providing the usual database facilities, the implementation also provides a mechanism to specify multiple user views of the database