Existing Data Models Research Articles

실시간 대중교통 경로안내를 위한 Space Time Point 모델의 설계와 구현

최근 환경문제로 인해 보행, 자전거, 대중교통과 같은 친 환경 교통수단에 대한 관심이 높아지고 있다. 하지만 보행과 자전거는 경우에 따라 장거리 이동이 불가능하기 때문에 이용범위가 제한적이라는 단점이 있다. 반면에 대중교통은 교통체증이라는 사회적 문제점까지 해결할 수 있는 교통수단이다. 이러한 대중교통은 시간에 따라 운행여부가 달라진다는 특징을 갖고 있다. 하지만 현재 웹상에서 서비스중인 대중교통정보 안내 서비스는 이러한 특징을 반영하지 못하기 때문에 경우에 따라 사용자에게 잘못된 정보를 제공할 수 있다. 이러한 한계점을 해결하고 대중교통의 운행정보를 고려한 정보제공을 위해 본 연구에서는 STP(Space Time Point)데이터 모델을 제안하였다. STP데이터 모델은 객체의 최하위 개념을 포인트 단위로 인식하고 이들을 계층적으로 구성하여 객체를 표현할 수 있으며, 기존의 시공간 데이터 모델과는 달리 시간에 따라 객체정보가 변하는 다양한 동적 공간객체의 구현이 가능하다. 대전지역을 대상으로 대중교통 운행정보로 버스 및 지하철에 대한 STP모델을 설계 및 구축하고 이를 이용하여 동적 경로 안내 기능을 구현하였다. 구현한 경로안내 기능을 통해 대전국립현충원에서 한남대학교로 가는 경로를 시간대별로 탐색해 본 결과 대중교통의 운행에 제한이 발생하는 심야시간에는 운행이 제한되는 노선을 우회하는 경로를 안내함으로써 시간에 따라 서로 다른 경로를 나타내었다. 이는 기존 데이터 모델에서는 제공할 수 없는 결과로 실시간 운행정보를 고려한 경로안내가 가능함을 확인하였다. 이러한 기능은 실시간 교통정보나 통행이력정보등과 같은 다양한 데이터 모델의 적용을 통해 추가적인 기능 확장이 가능할 것으로 기대한다. Recent environmental concerns have made interest in environment-friendly transportation means such as walking, biking, and public transportation. However, since it is difficult to move long distance by walking or biking, their scope of application is rather limited. On the other hand, public transportation can solve traffic congestion, a recent social issue, though its usability may depend on its time schedule. Currently available information services on public transportation in the Web do not reflect well such traits of the public transportation; thus, in some cases, they may provide wrong information to end users. To solve such problems and provide information based on timetable of public transportations, this paper proposes a STP(Space Time Point) data model. Unlike existing space-time data models, this model recognizes the bottommost element of an object as a point and structures these points in hierarchical way to define an object. In particular, It can make it possible to implement a variety of dynamic spatial objects changing object information according to time. An objective of this study is to design a STP model for bus and subway based on timetables of public transportation in Daejeon area and builds a system to provide path navigation. With the designed navigation function, a path from the Daejeon National Cemetery to Hannam University was searched by time slot. The result showed that the system provided different paths by time, as the system guided different paths when bus operation was limited in midnight. As existing data model could not provide such results, it is confirmed that the system can provide path navigation based on real-time traffic information. It is expected that based on such functionality, it is possible to provide additional functionalities by applying diverse data models such as real-time transport information or traffic history information.

Integrated management of facility, process, and output: data model perspective

As the manufacturing industry matures, vast amounts of data related to products are created by many kinds of engineering systems during the manufacturing phase. These include data for a variety of facilities, manufacturing processes, and the input and output of each process (input material, by-products, and intermediate and final products). Effective operation and maintenance of manufacturing facilities and eco-friendly products are gradually becoming important issues due to increased environmental regulations and changes in the enterprise business model. For this reason, increased efficiency in data management is necessary in the manufacturing industry. In this paper, existing data models for the integration of lifecycle data are analyzed according to their application domains. After the analysis, information requirements for the integrated management of facility, process, and output data are developed. According to these requirements, a data model appropriate for this integration is proposed. As an application case study, the use of the proposed data model for the effective operation and maintenance of manufacturing facilities is presented. Finally, benefit, limitation, and improvement of the proposed data model are discussed.

Is it still "Big Data" if it fits in my pocket?

"Big Data" is a hot topic but, in many ways, we are still trying to define what the phrase "Big Data" means. For many, there are more questions than answers at this point. Is it about size alone? Complexity? Variability? Data shape? Price/performance? New workloads? New types of users? Are existing data models, data management systems, data languages, and BI/ETL tools relevant in this space? Is MapReduce really a "major step backwards"? I have spent time over the last several years trying to answer many of these questions to my own satisfaction. As part of the journey I have witnessed a number of natural patterns that emerge in big data processing. In this talk I will present a catalog of these patterns and illustrate them across a scale spectrum from megabytes to 100s of petabytes. Finally, I will offer some thoughts around a systems and research agenda for this new world.

Spatial data modeling for coalfield geological environment

Presented a study on the design and implementation of spatial data modeling and application in the spatial data organization and management of a coalfield geological environment database. Based on analysis of a number of existing data models and taking into account the unique data structure and characteristic, methodology and key techniques in the object-oriented spatial data modeling were proposed for the coalfield geological environment. The model building process was developed using object-oriented technology and the Unified Modeling Language (UML) on the platform of ESRI geodatabase data models. A case study of spatial data modeling in UML was presented with successful implementation in the spatial database of the coalfield geological environment. The model building and implementation provided an effective way of representing the complexity and specificity of coalfield geological environment spatial data and an integrated management of spatial and property data.

Geoscience explanations: Identifying what is needed for generating scientific narratives from data models

As models of geoscience systems grow in number and size, so grows the need for tools to help express the output of those models in usable forms. In this paper the utility of the output of a model is defined as its ability to support scientific explanation. Commonly the output of a model might include statistics, graphs, maps, images and animations, which require expert interpretation and evaluation in the context of the model setup or implementation. Here the narrative is presented as a type of output from a model that can present the results of a model in a form that is more useful for the non-expert. Narratives provide a rich medium for expressing causal chains of events that form the basis for explanation and its future use in policy and decision making. This paper reviews research on narratives and their role in scientific explanation. The principles of narrative construction for the Geosciences are identified, which forms the basis for determining the key components needed in explanatory statements for communicating the output of geoscience models. The potential of existing data models used in model output for generating narratives are explored, followed by the conceptual presentation of an extended data model, which supports the narrative unit and has the potential to automate aspects of the generation of scientific explanation in narrative form.

Design and implementation of a domain-aware data model for pervasive context information

We introduce a data model for a context-management middleware that enables context-aware and pervasive computing applications to transparently access available data providers and that effectively combines their data. Our approach supports new data fusion concepts for overlapping and heterogeneous data sets and thus maximizes the information presented to the application. The main part of our data model is a flexible concept for meta data that is able to represent important aspects like quality, data derivation, or temporal characteristics of data. Attributes having multiple values are utilized to represent sensor measurements histories like locations of mobile objects at different points in time. In our paper, we characterize the requirements for our data model and show that existing data models, including the (object-) relational data model and standard XML data models, do not offer the required flexibility. Therefore basic XML technology is extended to support the necessary meta data concept and multiply typed objects.

Unifying Process Design with Automation and Control Application Development - An Approach Based on Information Integration and Model-driven Methods

The transfer of design information from process design to automation design requires attention as requirements on process control are increasing resulting in more complex systems to be designed. This paper presents current process and automation design practices and highlights related problems and information exchange challenges. A development method based on a common consistent information model, utilizing standards and existing data models, is discussed and model-driven methods for improved quality and productivity are introduced to the development of industrial process control applications.

Management of interval probabilistic data

In this paper we present a data model for uncertain data, where uncertainty is represented using interval probabilities. The theory introduced in the paper can be applied to different specific data models, because the entire approach has been developed independently of the kind of manipulated objects, like XML documents, relational tuples, or other data types. As a consequence, our theory can be used to extend existing data models with the management of uncertainty. In particular, the data model we obtain as an application to XML data is the first proposal that combines XML, interval probabilities and a powerful query algebra with selection, projection, and cross product. The cross product operator is not based on assumptions of independence between XML trees from different collections. Being defined with a possible worlds semantics, our operators are proper extensions of their traditional counterparts, and reduce to them when there is no uncertainty. The main practical result of the paper is a set of equivalences that can be used to compare or rewrite algebraic queries on interval probabilistic data, in particular XML and relational.

Mapping Local Solar Data Types

Solar physics and heliospheric study have arrived at the era of the Virtual Solar Observatory (VSO). The VSO gathers data from observation stations and data centers geographically distributed throughout the world, providing data from multiple spectral bands. In this paper, the author briefly analyzes the existing data model and presents a description of our local data ( that is produced at the Huairou Solar Observation Station ) in a well-defined way. The work lays the foundation for querying our data in VSO. It forms the beginning for adding additional search elements and categories to the VSO, therefore providing an infrastructure for a web site of the solar physics domain in China.

Personalized DVB-H Service Discovery Beyond 3G

In converged mobile broadcast and cellular services, the ability to choose among hundreds of digital broadcast streams and browsing a multitude of IP based content, will necessitate integration of advanced user interfaces capable of personalized service discovery. Next generation mobile terminals should be capable of not only displaying available services in the ESG electronic service guide but dynamically filter the content according to user preferences. This article explores possibilities for personalizing service discovery by matching semantic descriptions of media according to user-centric preferences submitted through the 3G return channel. Architectural design components are identified to filter content based on XML transformation of TV-Anytime metadata and additional elements are proposed to extend the existing data models with rich semantics based on RDF syntax and OWL ontology description logics.

A model for uncertain lines

The paper introduces a geometric model for uncertain lines that is capable of describing all the sources of uncertainty in spatial objects of linear type. We define uncertain lines as lines that incorporate uncertainties description both in the boundary and interior. These objects can model all the uncertainty by which spatial data are commonly affected and allow computations in presence of uncertainty without rough simplifications of the reality. The proposed model is an extension of the model for regions with a broad boundary and can be easily integrated into existing data models for spatial databases. We use the model as a basis for the study of topological relations between uncertain lines.

Iterative multi-tier management information modeling

The management information models currently used in the Internet have several limitations. Some of them contain errors, are missing important features, or are difficult to understand. Second, standards bodies keep reinventing the wheel, which confuses the terminology (hence customers) and wastes precious time. Third, finding a good balance between too abstract, and overly detailed models is a tough challenge, rarely achieved in practice. Last, the learning curve of existing data models is too steep. We propose to alleviate these problems by adopting a new process for designing and standardizing management information models. It is inspired by two techniques form software engineering: the iterative and incremental software development process, which addresses the shortcomings of the waterfall process usually adhered to by the IETF and DMTF; and multi-tier models, which capture different perspectives (e.g., analysis, design, and implementation) of the information model. Our main innovations are management-architecture-neutral universal information models (UIMs), sharing of conceptual models by different standard bodies, and specialization of the people involved in designing the different layers of the models. Our new process takes into account a number of constraints identified in real-life environments.

Towards integrated information models for data and documents

Numerous approaches to information modeling exist within chemical engineering representing product data, work processes, or other information. These models have a limited scope and were developed independently from each other. Thus, extended and general information models for chemical engineering are still missing as they are needed for the efficient support of work processes and for the development of domain-specific software tools. In this paper, open issues of information modeling are discussed. These are the integrated representation of information and work processes, the description of documents as carriers of data, and the integration of existing data models. The conceptual model framework CLiP is presented, which holds solution approaches for these three issues. Further, it can serve as an integration basis for existing information models. The paper further presents an overall architecture of a tool supporting the development and integration of information models.

이동 객체의 과거 및 미래 위치 연산을 위한 데이터 모델

무선 환경에서 시공간 이동 객체들의 위치 정보를 획득할 수 있는 기술들의 발달로 인해, 차량 추적 시스템, 산불 관리 시스템, 디지털 전장 시스템 등과 같은 다양한 응용 시스템들이 개발되고 있다. 이와 같은 응용에서는 이동 객체의 연속적인 변화 과정을 표현하고, 처리할 수 있는 데이터 모델이 필요하다. 그러나 관계형 모델을 이용하여 이동 객체를 표현할 경우 매 시간 마다 변경된 모든 정보를 저장할 수 없는 문제점이 발생된다. 또한 기존의 이동 객체 데이터 모델에서는 질의 시점을 데이터베이스로 관리되는 과거 시간이나 현재로부터 가까운 미래 시간으로 제한하는 단점이 있다. 따라서 이 논문에서는 모양 변화 처리 기법과 과거와 미래의 위치 추정 함수를 사용함으로써 이동 점 및 이동 영역 객체의 연속적인 움직임을 표현하고 모든 질의 시점에서의 연산을 저리 할 수 있는 이동 객체 데이터 모델을 제안한다 아울러 제안 모델을 산불관리 시스템에 적용 및 구현한 결과를 통해 타당성을 평가한다. In the wireless environment, according to the development of technology, which is able to obtain location information of spatiotemporal moving object, the various application systems are developed such as vehicle tracking system, forest fire management system and digital battle field system. These application systems need the data model, which is able to represent and process the continuous change of moving object. However, if moving objects are expressed by a relational model, there is a problem which is not able to store all location information that changed per every time. Also, existing data models of moving object have a week point, which constrain the query time to the time that is managed in the database such as past or current and near future. Therefore, in this paper, we propose a data model, which is able to not only express the continuous movement of moving point and moving region but also process the operation at all query time by using shape-change process and location determination functions for past and future. In addition, we apply the proposed model to forest fire management system and evaluate the validity through the implementation result.

A spatial model for complex objects with a broad boundary supporting queries on uncertain data

This paper proposes a new data model for spatial databases that supports spatial entities with a broad boundary. The model is proposed as a solution to the problem of handling uncertainty in spatial data. Broad boundaries absorb all the uncertainty by which spatial data are commonly affected and allow computations in presence of uncertainty without rough simplifications of the reality. A specific model for topological relations between regions with a broad boundary is then developed and hierarchically structured topological operators are proposed. Such operators allow users to progressively refine their queries and constitute the basis for a spatial extension to SQL. The model proposed in the paper can be easily integrated into existing data models for spatial databases.

A Conceptual Model and Rule-Based Query Language for HTML

Most documents available over the Web conform to the HTML specification. Such documents are hierarchically structured in nature. The existing data models for the Web either fail to capture the hierarchical structure within the documents or can only provide a very low level representation of such hierarchical structure. How to represent and query HTML documents at a higher level is an important issue. In this paper, we first propose a novel conceptual model for HTML. This conceptual model has only a few simple constructs but is able to represent the complex hierarchical structure within HTML documents at a level that is close to human conceptualization/visualization of the documents. We also describe how to convert HTML documents based on this conceptual model. Using the conceptual model and conversion method, one can capture the essence (i.e., semistructure) of HTML documents in a natural and simple way. Based on this conceptual model, we then present a rule-based language to query HTML documents over the Internet. This language provides a simple but very powerful way to query both intra-document structures and inter-document structures and allows the query results to be restructured. Being rule-based, it naturally supports negation and recursion and therefore is more expressive than SQL-based languages. A logical semantics is also provided.

Integration of data models for process design — first steps and experiences

In recent years numerous approaches have been presented to support the activities in chemical process design by means of software tools, but significant improvements of the design process can only be achieved if it is supported in its entirety. Therefore, the integration of the existing software tools is of prime importance. All these tools are based on data models that capture the information handled during the design process. In this study, a conceptual data model is presented that has been designed for the integration of existing data models as a first step towards the integration of the software tools using these models. This conceptual lifecycle process model CLiP is based on the ideas of general systems theory. This universal approach renders the model very flexible and guarantees a well-defined structure for data model integration. Some integration mechanisms are presented and discussed. Finally, a conceptual model is proposed based on the architecture tool integration.

Logical data modelling for geographical applications

Abstract. A formal, yet practical, GeoRelational Data Model (GRDM) is presented for the logical database design phase of the development of spatial information systems. Geographic applications are viewed in the context of information systems development. The generic needs of modelling spatial data are analyzed; it is concluded that they are not served satisfactorily by existing data models, so specifications of modelling tools for spatial application design are given. GRDM provides a set of representational constructs (relations and layers for the logical schema; virtual layers, object classes and spatial constraints for the user views) on top of well-established models. It constitutes part of a full, easily automated application design methodology. Extensive examples demonstrate the relevance, and ease-of-use of the platform-independent GRDM.

Indexing temporal data using existing B + -trees

Research in temporal databases has largely focused on extensions of existing data models for the proper handling of temporal information. One approach is to store temporal data on existing DBMS and build some new indexes to provide support for the efficient retrieval of temporal data. This paper describes mapping strategies to linearize the data such that existing B +-trees can be used directly. With such an implementation, a temporal relation is mapped to points in a multi-dimensional space, with each time interval being translated to a two-dimensional coordinate, and a temporal selection operation is constructed as a spatial search operation. The proposed approach has two advantages. First, mapping a temporal relation to a multi-dimensional space provides a uniform framework for dealing with temporal queries involving transaction and valid time, as well as other non-temporal attributes. Second, linearization of the multi-dimensional search space allows classical indexing methods (such as the B +-tree) to be used; this means that index support for temporal selection can be accomplished without modification to the underlying storage components of the DBMS. Both analytical and simulation study show that the proposed indexing scheme is more efficient than the time index in both its disk utilization and access time.

A Hypergraph-based Framework for Visual Interaction with Databases

The advent of graphical workstations has led to a new generation of interaction tools in database systems, where the use of graphics greatly enhances the quality of the interaction. Yet, Visual Query Languages present some limitations, deriving partly from their own paradigm and partly from the available technology. One of the basic drawbacks is the lack of formalization, in contrast to the well-established traditional languages. In this paper we propose a theoretical framework for visual interaction with databases, having a particular kind of hypergraph, the Structure Modeling Hypergraph (SMH), as a representation tool, able to capture the features of existing data models. SMHs profit from the basic property of diagrams while overcoming their limitations. Notable characteristics of SMHs are: uniform and unified representation of intensional and extensional aspects of databases, direct representation of containment relationships, and immediate applicability of direct manipulation primitives. SMHs are not a new data model but a new representation language that provides the syntactic rules for describing the structuring mechanisms of data models. SMHs can be queried by formal systems closed under queries.