Semistructured Data Model Research Articles

Towards a Generalised Semistructured Data Model and Query Language

Although current efforts are all aimed at re-defining new ways to harness old data representations, possibly with new schema features, the challenges still open provide evidence of the need for a "diametrically opposite" approach: in fact, all information generated in real contexts is to be understood lacking of any form of schema, where the schema associated with such data is only determined a posteriori based on either a specific application context, or from some data's facets of interest. This solution should still enable recommendation systems to manipulate the aforementioned data semantically. After providing evidence of these limitations from current literature, we propose a new Generalized Semistructured data Model that makes possible queries expressible in any data representation through a Generalised Semistructured Query Language, both relying upon script v2.0 as a MetaModel language manipulating types as terms as well as allowing structural aggregation functions.

A repository for the publication and sharing of heterogeneous materials data

National Materials Data Management and Service platform (NMDMS) is a materials data repository for the publication and sharing of heterogeneous materials scientific data and follows the FAIR principles: Findable, Accessible, Interoperable, and Reusable. To ensure data are ‘Interoperable, NMDMS uses a user-friendly semi-structured scientific data model, named dynamic container’, to define, exchange, and store heterogeneous scientific data. Then, a personalized yet standardized data submission subsystem, a rigorous project data review and publication subsystem, and a multi-granularity data query and retrieval subsystem collaboratively make data ‘Reusable’, ‘Findable’, and ‘Accessible’. Finally, China’s “National Key R&D Program: Material Genetic Engineering Key Special Project” has adopted NMDMS to publish and share its project data. There are 12,251,040 pieces of data published in NMDMS since 2018, under 87 categories and 1,912 user-defined schemas from 45 projects. The platform has been accessed 908875 times, and 2403,208 pieces of data have been downloaded. In short, NMDMS effectively accelerates the publication and sharing of material project data in China.

Polytopic Matrix Factorization: Determinant Maximization Based Criterion and Identifiability

We introduce Polytopic Matrix Factorization (PMF) as a novel data decomposition approach. In this new framework, we model input data as unknown linear transformations of some latent vectors drawn from a polytope. In this sense, the article considers a semi-structured data model, in which the input matrix is modeled as the product of a full column rank matrix and a matrix containing samples from a polytope as its column vectors. The choice of polytope reflects the presumed features of the latent components and their mutual relationships. As the factorization criterion, we propose the determinant maximization (Det-Max) for the sample autocorrelation matrix of the latent vectors. We introduce a sufficient condition for identifiability, which requires that the convex hull of the latent vectors contains the maximum volume inscribed ellipsoid of the polytope with a particular tightness constraint. Based on the Det-Max criterion and the proposed identifiability condition, we show that all polytopes that satisfy a particular symmetry restriction qualify for the PMF framework. Having infinitely many polytope choices provides a form of flexibility in characterizing latent vectors. In particular, it is possible to define latent vectors with heterogeneous features, enabling the assignment of attributes such as nonnegativity and sparsity at the subvector level. The article offers examples illustrating the connection between polytope choices and the corresponding feature representations.

Research Directions on GIS Database Design and Management

Objective: Geospatial Information System (GIS) is predominantly used in urban planning, and improves quality of people living in an area in many ways. Even though so many hardware and software systems are employed in GIS, the database gains the greatest significance. The intension is to progress a spatial database that should be used as a representation or model of the world, particularly to design for a very specific application. Analysis: The GIS data framework is the methodology proposed to promote an application specific spatial database. It comprises of integrating heterogeneous type of data, followed by constructing a semi-structured multi dimensional data model which directs to design a spatial database. Findings: The novelty in this GIS data framework is Building Information Model (BIM) integrated with the traditional data in support of answering indoor spatial queries. Moreover, this framework worked with BigData to support heterogeneous type of data and to automate decision support system. Enhancements: The views focused on the case studies in this paper help to travel in a new direction of GIS specification, utilization and research from the routine methodologies. This paper widens the scope of research directions in order to establish new techniques in each diverse field.

Towards a Normal Form and a Query Language for Extended Relations Defined by Regular Expressions

This paper introduces a generalized data base concept that unites relational and semi structured data models. As an important theoretical result we could find a quadratic decision algorithm for the implication problem of functional and join dependencies defined on the united data model. As practical contribution we presented a normal form for the new data model as a tool for data base design. With our novel representations of regular expressions, a more effective searching method could be developed. XML elements are described by XML schema languages such as a DTD or an XML Schema definition. The instances of these elements are semi-structured tuples. A semi-structured tuple is an ordered list of (attribute: value) pairs. We may think of a semi-structured tuple as a sentence of a formal language, where the values are the terminal symbols and the attribute names are the non-terminal symbols. In the authors' former work (Szabó and Benczúr, 2015) they introduced the notion of the extended tuple as a sentence from a regular language generated by a grammar where the non-terminal symbols of the grammar are the attribute names of the tuple. Sets of extended tuples are the extended relations. The authors then introduced the dual language, which generates the tuple types allowed to occur in extended relations. They defined functional dependencies (regular FD - RFD) over extended relations. In this paper they rephrase the RFD concept by directly using regular expressions over attribute names to define extended tuples. By the help of a special vertex labeled graph associated to regular expressions the specification of substring selection for the projection operation can be defined. The normalization for regular schemas is more complex than it is in the relational model, because the schema of an extended relation can contain an infinite number of tuple types. However, the authors can define selection, projection and join operations on extended relations too, so a lossless-join decomposition can be performed. They extended their previous model to deal with XML schema indicators too, e.g., with numerical constraints. They added line and set constructors too, in order to extend their model with more general projection and selection operators. This model establishes a query language with table join functionality for collected XML element data.

Research on the Data Model and the Approaches to Data Mining in the Semi-Structured Data

As an important form of Internet data, semi-structured data in data mining is an important fist conditions. And the data mining was designed to find and extract large database in the implied information of value. This paper first introduced the half structured data concept characteristic, based on the data from each of the half structural said, the data model two half-and-half structured data model are introduced, finally summarizes semi-structured data model and the relationship between the data model before difference [1].

Evaluations of Conceptual Models for Semi-structured Database System

In the latest years many different models for semi structured data have been proposed; most of them, however, are too specific to allow immediate comparison with other models, and do not easily support incremental model design. A number of features which can be considered interesting for a semi structured data model are listed. E.g. we review the more widely used models in Conceptual Modeling for Information Systems (Entity-Relationship and UML), and argue that they do not support effectively modeling of semi structured data. As a consequence, structured and semi structured data cannot be treated in an integrated, holistic way during requirements specification. Research about similarity between semi structured documents (particularly for XML documents) has produced many works in the areas of Database Systems, Artificial Intelligence and Data Mining. In this work introducing a brief survey about it. At first introducing some basic properties. After that, some works are reviewed, highlighting their particularities and general approach. Concluding with a comparison of these works, analyzing their benefits and problems.

3SEPIAS: A Semi-Structured Search Engine for Personal Information in dAtaspace System

Nowadays, personal information is being distributed into more and more heterogeneous sources, which presents a huge obstacle to management and retrieval of personal information. To address this problem, this paper presents the blueprint of a novel Personal Information Management (PIM) system named 3SEPIAS (short for Semi-Structured Search Engine for Personal Information in dAtaspace System).3SEPIAS has three main features, data integration without upfront semantic reconciliation, flexible query model for data having sparse and evolving schema, and efficient best-effort proximity search approach on graphs. For that, we first propose a semi-structured graph data model called Interpreted Object Model (IOM) to uniformly represents a user’s heterogeneous personal information and loosely integrates it into a dataspace in a schema-later way. Then, a Semi-Structured Search Engine (3SE) can be used to search over the personal dataspaces. We propose an intuitive 3SE Query Language (3SQL) that enables users to query in a varying degree of structural constraint according to their knowledge of underlying schemas. Moreover, a best-effort top-k proximity search optimization strategy and corresponding graph index structures are proposed to improve the efficiency of query processing.We perform comprehensive experiments to test both effectiveness and efficiency of our proximity search approach. The results reveal that 3SE can beat the previous proximity search systems by a large margin with only a little or even no loss of result quality, especially for large graphs.

Enhancing Data Security in ERP Projects Using XML

Enterprise resource planning (ERP) is integrated packaged software, which addresses most fundamental business processing functionality across different functional areas and business units, in a single software system, with single database and accessible through a unified interface and channel of communication. Meeting security requirements for privacy, confidentiality and integrity is essential in order to move business online ERP System requires an accurate, precise and Data security in business concepts of the enterprise. The authors introduce basic features and security of ERP System using Extensible Mark-up Language (XML) technology. Traditionally, XML security has developed along two distinct though related lines of research, corresponding to two facts of the XML security notion. The first fact defines XML security as a set of security techniques (encryption, digital signature) tightly coupled with XML to maintain the main features of the XML semi-structured data model while adding to it all necessary security capabilities. In this paper we will explore XML Signature specification from W3C and its implementation in .NET.

Concept-based query language approach to enterprise information systems

In enterprise information systems (EISs) it is necessary to model, integrate and compute very diverse data. In advanced EISs the stored data often are based both on structured (e.g. relational) and semi-structured (e.g. XML) data models. In addition, the ad hoc information needs of end-users may require the manipulation of data-oriented (structural), behavioural and deductive aspects of data. Contemporary languages capable of treating this kind of diversity suit only persons with good programming skills. In this paper we present a concept-oriented query language approach to manipulate this diversity so that the programming skill requirements are considerably reduced. In our query language, the features which need technical knowledge are hidden in application-specific concepts and structures. Therefore, users need not be aware of the underlying technology. Application-specific concepts and structures are represented by the modelling primitives of the extended RDOOM (relational deductive object-oriented modelling) which contains primitives for all crucial real world relationships (is-a relationship, part-of relationship, association), XML documents and views. Our query language also supports intensional and extensional–intensional queries, in addition to conventional extensional queries. In its query formulation, the end-user combines available application-specific concepts and structures through shared variables.

Theorem prover approach to semistructured data design

The wide adoption of semistructured data has created a growing need for effective ways to ensure the correctness of its organization. One effective way to achieve this goal is through formal specification and automated verification. This paper presents a theorem proving approach towards verifying that a particular design or organization of semistructured data is correct. We formally specify the semantics of the Object Relationship Attribute data model for Semistructured Data (ORA-SS) modeling notation and its correctness criteria for semistructured data normalization using the Prototype Verification System (PVS). The result is that effective verification on semistructured data models and their normalization can be carried out using the PVS theorem prover.

Formal Verification of Semistructured Data Models in PVS

Formal Verification of Semistructured Data Models in PVS

Evolving a “Wise” integration system for e-commerce transactions

The Web facilitates a global marketplace that provides an economic platform for application developers, merchants and customers to exchange goods and services from a wide range of domains. As a result, large volume of data now resides on the Web. Access to data distributed over the Web is becoming increasingly difficult because of information overload. A system that transcends the amalgamation of data, and provides easy access to data distributed over the Web is necessary. We present WISE, a correctness preserving approach to integration of Web data sources. We describe components of WISE, including a flexible semistructured data model, a common-term vocabulary, and an efficient integration algorithm that automates the integration process. We formally specify these components and show that the global integrated schema is correct, complete, minimal, and understandable.

A Z Approach in Validating ORA-SS Data Models

The rapid growth of the World Wide Web has resulted in more data being accessed over the Internet. In turn there is an increase in the use of semistructured data, which plays a crucial role in many web applications particularly with the introduction of XML and its related technologies. This increase in use makes the design of good semistructured data structures essential. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. In this paper, we demonstrate an approach to formally validate the ORA-SS data models in order to enhance the correctness of semistructured data design. A mathematical semantics for the ORA-SS notation is defined using the Z formal language, and further validation processes are carried out to check the correctness of the semistructured data models at both the schema and instance levels.

Unauthorized inferences in semistructured databases

In this paper we study the problem of providing controlled access to confidential data stored in semistructured databases. More specifically, we focus on privacy violations via data inferences that occur when domain knowledge is combined with non-private data. We propose a formal model, called Privacy Information Flow Model, to represent the information flow and the privacy requirements. These privacy requirements are enforced by the Privacy Mediator. Privacy Mediator guarantees that users are not be able to logically entail information that violates the privacy requirements. We present an inference algorithm that is sound and complete. The inference algorithm is developed for a tree-like, semistructured data model, selection–projection queries, and domain knowledge, represented as Horn-clause constraints.

Efficient processing of XPath queries using indexes

A number of indexing techniques have been proposed in recent times for optimizing the queries on XML and other semi-structured data models. Most of the semi-structured models use tree-like structures and query languages (XPath, XQuery, etc.) which make use of regular path expressions to optimize the query processing. In this paper, we propose two algorithms called Entry-point algorithm (EPA) and Two-point Entry algorithms that exploit different types of indices to efficiently process XPath queries. We discuss and compare two approaches namely, Root-first and Bottom-first in implementing the EPA. We present the experimental results of the algorithms using XML benchmark queries and data and compare the results with that of traditional methods of query processing with and without the use of indexes, and ToXin indexing approach. Our algorithms show improved performance results than the traditional methods and Toxin indexing approach.

Electronic Clinical Path System Based on Semistructured Data Model Using Personal Digital Assistant for Onsite Access

Clinical Paths (Paths) have been introduced by different hospitals for patient care management. An Electronic Clinical Path (ECP) with onsite access provision seems to improve the efficiency of medical staffs because they can share vast medical information about patients at a time and also can reuse accumulated data easily, which is impossible with paper-based Path. Data model is the basis for implementing ECP. However, there is no established model for ECP. The purpose of this study is to introduce a model for ECP and implement an ECP with onsite access system. We introduced a Semistructured Data Model (SSDM) for ECP, and implemented a Web application system based on this model using Personal Digital Assistant (PDA) as inputting device. Our system functioned as expected with wireless LAN, and users handled the data on bedside using PDA. By introducing SSDM, we showed the correspondence between schema of Paths and implementation of ECP.

Decidable containment of recursive queries

One of the most important reasoning tasks on queries is checking containment, i.e., verifying whether one query yields necessarily a subset of the result of another one. Query containment is crucial in several contexts, such as query optimization, query reformulation, knowledge-base verification, information integration, integrity checking, and cooperative answering. Containment is undecidable in general for Datalog, the fundamental language for expressing recursive queries. On the other hand, it is known that containment between monadic Datalog queries and between Datalog queries and unions of conjunctive queries are decidable. It is also known that containment between unions of conjunctive two-way regular path queries, which are queries used in the context of semistructured data models containing a limited form of recursion in the form of transitive closure, is decidable. In this paper, we combine the automata-theoretic techniques at the base of these two decidability results to show that containment of Datalog in union of conjunctive two-way regular path queries is decidable in 2EXPTIME. By sharpening a known lower bound result for containment of Datalog in union of conjunctive queries we show also a matching lower bound.

Reasoning on regular path queries

Current information systems are required to deal with more complex data with respect to traditional relational data. The database community has already proposed abstractions for these kinds of data, in particular in terms of semistructured data models. A semistructured model conceives a database essentially as a finite directed labeled graph whose nodes represent objects, and whose edges represent relationships between objects. In the same way as conjunctive queries form the core of any query language for the relational model, regular path queries (RPQs) and their variants are considered the basic querying mechanisms for semistructured data.Besides the basic task of query answering, i.e., evaluating a query over a database, databases should support other reasoning services related to querying. One of the most important is query containment, i.e., verifying whether for all databases the answer to a query is a subset of the answer to a second query. Another important reasoning service that has received considerable attention in the recent years is view-based query processing, which amounts to processing queries based on a set of materialized views, rather than on the raw data in the database.The goal of this paper is to describe basic results and techniques concerning query containment and view based query processing for the class of two-way regular-path queries (which extend RPQs with the inverse operator). We will demonstrate that the basic services for reasoning about two way regular path queries are decidable, thus showing that the limited form of recursion expressible by these queries does not endanger the decidability of reasoning. Besides the specific results, our methods show the power of two-way automata in reasoning on complex queries.

Modelling the history of semi-structured geographical entities

Geographical entities are characterized by rather complex structures. They involve space and thematic information, which is subject to change in time, while history should be maintained. On the other hand, these structures may be irregular (i.e. they do not necessarily conform to a fixed schema), because associated data is usually collected based on different specifications and multiple resolutions. Hence, the representation of geographical entities in traditional data models, such as the relational or object-oriented, is not always feasible. In this respect, this paper investigates the use of semi-structured data (SSD) models—an innovative approach recently developed in Information Technology—for modelling dynamic geographical entities. A framework for the representation of geographic entities in Object Exchange Model (OEM), a popular model for semi-structured data, is introduced. Additionally, it is shown how useful information can be extracted from such a representation using the LOREL query language for SSD. A simplified case study in the application domain of cadastre involving SSD is examined closely.