Comprehensive Data Model Research Articles

Query intent inference via search engine log

Mining the latent intents behind search queries is critical for contemporary search engines. Therefore, there has been lots of effort on studying how to infer the intents of search queries via search engine query log. However, the task of query log-based intent inference is not trivial, since it involves cross-disciplinary knowledge of data modeling and data mining. In this paper, we tackle the problem of query intent inference by integrating multiple information sources in a seamless manner. We first propose a comprehensive data model called Search Query Log Structure (SQLS) that represents the relation between search queries via the User dimension, the URL dimension, the Session dimension and the Term dimension. In order to explore the effective ways of using such multidimensional information modeled by SQLS, we survey and compare three frameworks, namely Result-Oriented Framework, Laplacian-Oriented Framework and Topic-Oriented Framework, to infer the intents of search queries. Experimental results show that the three frameworks significantly outperform the state-of-the-art approach and meet the diverse requirements arising from different application scenarios.

A comprehensive and generic machine tools data model

The data model of machine tools plays a key role to share and manage machine tools information among modern manufacturing systems and has been considered as a fundamental basis for achieving various manufacturing activities such as process planning, machining simulation and production scheduling. Although research into modelling machine tools has been done, these modelling approaches are either machine vendor specific, or limited and incomplete in their scope to represent machine tools. Therefore, a comprehensive and generic machine tools data model (CGMTDM) is proposed in this paper. The proposed data model is constructed based on the oriented-object EXPRESS language, which not only includes the information of mechanical elements, but the information of the electro-mechanical and electronic elements. The case study is used to demonstrate the proposed data model at the end. It has been concluded that CGMTDM can consistently, completely and flexibly represent the information of machine tools. [Received 14 April 2016; Revised 4 September 2016; Accepted 8 September 2016]

BUILDING INFORMATION MODELING AND OPERATING of RFID TECHNOLOGY TO IMPROVE OCCUPATIONAL SAFETY IN CONSTRUCTION INDUSTRY

Despite a slight decrease of the number of accidents at work on German construction sites in recent years, prevention activities should be strengthened and started explicitly in addition. In particular, a large number of accidents on construction sites are carried out by the collision of different trades and the absence or not wearing appropriate PPE for workers of adjacent trades. An important potential is seen in the optimization of the safety and health by making available pre-defined information about safety and health throughout the life cycle of buildings. Using this information, preventive measures can be taken faster, more effective, safer and preventive. The method of Building Information Modelling (BIM) forms the basis for a comprehensive building information model or building data model. From the perspective of the applicant the method of BIM in conjunction with the Auto-ID-based tracking of actual process data, however, provides additional data to planning data among other OSH-related processes. This data can be used for the further phases of the life cycle of buildings, which are in the building phase, the use phase and rebuilding phase and the decommissioning phase considerable potential, especially for the optimization of occupational safety and health. The primary objective of this research project is to identify, define and standardize health and safety information and provide them for preventive measures with the BIM method.

Ontology-based facility data model for energy management

Context: Definition of a comprehensive facility data model is a prerequisite for providing more advanced energy management systems capable of tackling the underlying heterogeneity of complex infrastructures, thus providing more flexible data interpretation and event management, advanced communication and control system capabilities. Objective: This paper proposes one of the possible implementations of a facility data model utilizing the concept of ontology as part of the contemporary Semantic Web paradigm. Method: The proposed facility ontology model was defined and developed to model all the static knowledge (such as technical vendor data, proprietary data types, and communication protocols) related to the significant energy consumers of the target infrastructure. Furthermore, this paper describes the overall methodology and how the common semantics offered by the ontology were utilized to improve the interoperability and energy management of complex infrastructures. Initially, a core facility ontology, which represents the generic facility model providing the general concepts behind the modelling, was defined. Results: In order to develop a full-blown model of the specific facility infrastructure, Malpensa and Fiumicino airports in Italy were taken as a test-bed platform in order to develop the airport ontology owing to the variety of the technical systems installed at the site. For the development of the airport ontology, the core facility ontology was first extended and then populated to reflect the actual state of the target airport facility. Conclusion: The developed ontology was tested in the environment of the two pilots, and the proposed solution proved to be a valuable link between separate ICT systems involving equipment from various vendors, both on syntax and semantic level, thus offering the facility managers the ability to retrieve high-level information regarding the performance of significant energy consumers.

Information Structure of STEP Convertor of STEP-CNC Mapping System

ISO 14649 standard, commonly recognized as STEP-NC is a data model interface for computer numerical controllers. STEP-NC goes much further that G codes and has a more comprehensive data model that overcomes the lack of process information in ISO 6983 files (G codes programming). The STEP compliant approach brings the possibility to integrate the machine controller to the overall enterprise information network, with the intention of having bi-directional data flow. This will provide the novel capability for upstream feedback of information from the numerical controller to the design and process areas in the process planning and manufacturing. This paper presents the key concepts of the proposed STEP Convertor of the STEP-CNC Mapping System. The objective of the main system is to take a generic STEP file as the input to drive a CNC machine tool. The main system is broken down into two main sub-systems, STEP Convertor and STEP-NC Translator. This paper will focus solely on the information structure and conceptualization of the STEP Convertor.

Business intelligence for cross-process knowledge extraction at tourism destinations

Decision-relevant data stemming from various business processes within tourism destinations (e.g. booking or customer feedback) are usually extensively available in electronic form. However, these data are not typically utilized for product optimization and decision support by tourism managers. Although methods of business intelligence and knowledge extraction are employed in many travel and tourism domains, current applications usually deal with different business processes separately, which lacks a cross-process analysis approach. This study proposes a novel approach for business intelligence-based cross-process knowledge extraction and decision support for tourism destinations. The approach consists of (a) a homogeneous and comprehensive data model that serves as the basis of a central data warehouse, (b) mechanisms for extracting data from heterogeneous sources and integrating these data into the homogeneous data structures of the data warehouse, and (c) analysis methods for identifying important relationships and patterns across different business processes, thereby bringing to light new knowledge. A prototype of the proposed concepts was implemented for the leading Swedish mountain destination Are, which demonstrates the effectiveness of the proposed business intelligence architecture and the gained business benefits for a tourism destination.

Data modelling and the audit

The development of a corporate-wide data model is a tool to integrate firm's data. The lack of staff is an impediment to data management efforts. Creation of a comprehensive data-model includes collecting and verifying extensive meta-data information. Meta-data includes provenance (both processes and code), structure, relationships among data, data transformation, and units responsible for data items. Inclusion of meta-data will enhance data quality and provide support for users' data understanding and use. The more complete and detailed the corporate data model, the better information can be communicated across the organisation. This meta-data can be an explicit representation of management policies. For instance, employee type with rights to enter or manipulate data elements and the skill and knowledge requirements. These policies can also represent internal controls. This paper examines management policies within data-models and use of this information to test audit assertions on the effectiveness, design, and operation of internal controls.

SEMERGY.net: automatically identifying and optimizing energy-efficient building designs

A central goal of European and national climate and energy programs is to reduce the greenhouse gas emission of buildings. SEMERGY is a web-based optimization environment, which supports users in decision-making regarding energy-efficient building designs. Taking the user-specified criteria investment costs, final energy demand of the building, and environmental impact of used building products into account, the system identifies efficient building designs and retrofit options. The following steps were taken: (i) development of a comprehensive building data model, (ii) creation of an ontology of linked building product data, (iii) development of a rule-based system to automatically identify valid construction alternatives for building components, (iv) development of a multi-objective optimization procedure, and (v) creation of a web-based Graphical User Interface to enable data entry and user interaction. The present contribution provides an overview of the progress made in the above mentioned domains.

Building a geospatial data model for humanitarian response.

An effectual emergency response effort is contingent upon the quality and timeliness of information provided to both the decision making and coordinating functions; conditions that are hard to guarantee in the urgent climate of the response effort. The purpose of this paper is to present a validated Humanitarian Data Model (HDM) that can assist in the rapid assessment of disaster needs and subsequent decision making. Substandard, inconsistent information can lead to poorly informed decisions, and subsequently, inappropriate response activities. Here we present a novel, organized, and fluid information management workflow to be applied during the rapid assessment phase of an emergency response. A comprehensive, peer-reviewed geospatial data model not only directs the design of data collection tools but also allows for more systematic data collection and management, leading to improved analysis and response outcomes. This research involved the development of a comprehensive geospatial data model to guide the collection, management and analysis of geographically referenced assessment information, for implementation at the rapid response phase of a disaster using a mobile data collection app based on key outcome parameters. A systematic review of literature and best practices was used to identify and prioritize the minimum essential data variables. The data model was critiqued for variable content, structure, and usability by a group of subject matter experts in the fields of humanitarian information management and geographical information systems. Consensus found that the adoption of a standardized system of data collection, management, and processing, such as the data model presented here, could facilitate the collection and sharing of information between agencies with similar goals, facilitate the better coordination of efforts by unleashing the power of geographic information for humanitarian decision support.

Formal model of time point-based sequential data for OLAP-like analysis

Abstract Numerous nowadays applications generate huge sets of data, whose natural feature is order, e.g,. sensor installations, RFID devices, workflow systems, Website monitors, health care applications. By analyzing the data and their order dependencies one can acquire new knowledge. However, nowadays commercial BI technologies and research prototypes allow to analyze mostly set oriented data, neglecting their order (sequential) dependencies. Few approaches to analyzing data of sequential nature have been proposed so far and all of them lack a comprehensive data model being able to represent and analyze sequential dependencies. In this paper, we propose a formal model for time point-based sequential data. The main elements of this model include an event and a sequence of events. Measures are associated with events and sequences. Measures are analyzed in the context set up by dimensions in an OLAP-like manner by means of the set of operations. The operations in our model are categorized as: operations on sequences, on dimensions, general operations, and analytical functions.

A data model for algorithmic multiple criteria decision analysis

Various software tools implementing multiple criteria decision analysis (MCDA) methods have appeared over the last decades. Although MCDA methods share common features, most of the implementing software have been developed independently from scratch. Majority of the tools have a proprietary storage format and exchanging data among software is cumbersome. Common data exchange standard would be useful for an analyst wanting to apply different methods on the same problem. The Decision Deck project has proposed to build components implementing MCDA methods in a reusable and interchangeable manner. A key element in this scheme is the XMCDA standard, a proposal that aims to standardize an XML encoding of common structures appearing in MCDA models, such as criteria and performance evaluations. Although XMCDA allows to present most data structures for MCDA models, it almost completely lacks data integrity checks. In this paper we present a new comprehensive data model for MCDA problems, implemented as an XML schema. The data model includes types that are sufficient to represent multi-attribute value/utility models, ELECTRE III/TRI models, and their stochastic extensions, and AHP. We also discuss use of the data model in algorithmic MCDA.

SEMERGY: Performance-Guided Building Design and Refurbishment within a Semantically Augmented Optimization Environment

This contribution illustrates recent efforts in the research project SEMERGY, a computational environment, which incorporates semantic web technologies to support building design and refurbishment optimization. A major part of the necessary information for energy efficient building planning is implicitly available in the World Wide Web. However, this theoretically valuable repository of information cannot be practically used, given its ill-structured nature. SEMERGY addresses this very problem through a number of developments. Specifically, SEMERGY: 1) embeds a comprehensive building data model, 2) incorporates an Ontology for building product data, 3) deploys a rule-based logic for identification of valid building construction alternatives, 4) provides an easy-to-use optimization procedure evaluating energy demand, environmental impact, and investment costs of alternatives, and 5) offers a web-based Graphical User Interface. The present contribution provides a general overview of the whole project and documents the state of its development.

Processing Uncertain RFID Data in Traceability Supply Chains

Radio Frequency Identification (RFID) is widely used to track and trace objects in traceability supply chains. However, massive uncertain data produced by RFID readers are not effective and efficient to be used in RFID application systems. Following the analysis of key features of RFID objects, this paper proposes a new framework for effectively and efficiently processing uncertain RFID data, and supporting a variety of queries for tracking and tracing RFID objects. We adjust different smoothing windows according to different rates of uncertain data, employ different strategies to process uncertain readings, and distinguish ghost, missing, and incomplete data according to their apparent positions. We propose a comprehensive data model which is suitable for different application scenarios. In addition, a path coding scheme is proposed to significantly compress massive data by aggregating the path sequence, the position, and the time intervals. The scheme is suitable for cyclic or long paths. Moreover, we further propose a processing algorithm for group and independent objects. Experimental evaluations show that our approach is effective and efficient in terms of the compression and traceability queries.

Review of semantic modelling technologies in support of virtual factory design

Comprehensive data models and standardised terminologies are required across tools and their developers to rapidly design and prototype digitised virtual factories. Also, various types of software are required to be integrated for cost-effective modelling exercises. To meet this requirement, semantic modelling technologies involving ontologies have featured prominently in many manufacturing applications. This paper considers, extensively, the current semantic requirements for digitised virtual factory design and prototyping and compares them with the capabilities of existing semantic technologies. As a result, a review of methodologies, tools and languages for creating ontologies has been reported. The review concludes with the next generation requirements for methodologies, tools and languages for creating ontologies suitable for the virtual factory design process, and further explains ongoing work associated with the creation of ontologies and reasoning mechanisms through the integrated use of ObjectLogic, OntoStudio and OntoBroker.

VarioML framework for comprehensive variation data representation and exchange

BackgroundSharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement.ResultsThe GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs) e.g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components.ConclusionsVarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.

The development of a comprehensive machine-readable lexicon for Zulu

A comprehensive machine-readable (MR) lexicon is a strategic resource in the development of language technology. Two essential aspects are the development of a comprehensive data model and its accurate and efficient implementation. This study focuses on the development of MR lexicons for the South African Bantu languages and more specifically Zulu.

Joint Item-Tag Recommendation Framework for Collaborative Filtering in Social Tagging Systems

Tapping into the wisdom of the crowd, social tagging is becoming an increasingly important mechanism for organizing and discovering information on the Web. Effective tag-based recommendation of information items is one of the key technologies contributing to the success of this social information discovery mechanism. A precise understanding of the information structure of social tagging systems lies at the core of an effective tag-based item recommendation method. While most existing methods either implicitly or explicitly assume a simple tripartite graph structure, in this paper, we propose a comprehensive data model to capture all types of co-occurrence information in the social tagging context. Based on this data model, we further propose a unified user profiling scheme to make full use of all available information. Finally, supported by this user profile, we propose a framework for collaborative filtering in social tagging systems. In this framework, we first generate joint item-tag recommendations, with tags indicating topical interests of users in target items. These joint recommendations are then refined by the wisdom from the crowd and projected to the item (or tag) space for final item (or tag) recommendations. Empirical evaluation using real-world data demonstrates the utility of our proposed approach.

What Is A Well?

Guest editorial Over the past decade, well technology has advanced exponentially. Horizontal wells, multiple completions, and wells that cycle between steam injection and heavy oil production have superseded the traditional vertical well with one completion zone. Advances in the way the oil and gas sector describes and identifies well data elements have not matched the growth in well technology, however. Even the way the sector defines basic well concepts, such as wellbores, completions, and depths, can vary between companies and regulatory jurisdictions. Several factors have contributed to that inconsistency. The foundation for regulations and well technology dates back more than a century: many terminologies arose when the petroleum sector was in its infancy. Drilling technology has changed dramatically in the past 10 years, yet the regulatory descriptions have remained relatively static. Part of the reason is the lack of international standards; for many years, guidance was offered by the American Petroleum Institute in the US, but lapsed in the 1980s. The myriad of modern drilling techniques also add to the confusion. Start with a simple producing well, which is wellbore WB1 (Fig. 1). Later, when the operator deepens the well (WB2) and completes new formations (WB2-C1 and WB2-C2), there is some disagreement about whether the deepened segment is part of the same wellbore, or a new wellbore. Of those who think it is a new wellbore, some measure the new wellbore from the surface to the new bottom hole, and some think the new wellbore is only the newly drilled portion. Many modern wells have far more complex production histories. In Fig. 2, the operator has drilled a pilot well, WB1, with two lateral segments, WB2 and WB3, which are then completed in separate reservoirs. Knowing which production exists in which wellbores becomes far more important; an engineering decision made on incorrect or incomplete information has the potential to create significant repercussions. In Search of a Solution The Professional Petroleum Data Management Association (PPDM), based in Calgary, has been working to resolve the issue. PPDM was formed in 1989 and incorporated in 1991. It is a not-for-profit organization that provides data management expertise for the petroleum exploration and production industry. The membership is made up of more than 150 petroleum companies, government agencies, software application providers, data vendors, and service companies. The petroleum industry generates a large amount of data, including exploration seismic, well drilling, and oil and gas production information. PPDM originally set out to develop an open data model that would allow the industry to reduce costs and allow companies to become more productive, efficient, and competitive. Over the past two decades, industry professionals working as volunteers with PPDM have created a comprehensive data model that benefits a wide array of functions within an oil company, such as well information, surface and mineral rights management, well activities and operations, equipment and facilities management, seismic information, and production and reserves data.

TMA-TAB: A spreadsheet-based document for exchange of tissue microarray data based on the tissue microarray-object model

The importance of tissue microarrays (TMA) as clinical validation tools for cDNA microarray results is increasing, whereas researchers are still suffering from TMA data management issues. After we developed a comprehensive data model for TMA data storage, exchange and analysis, TMA-OM, we focused our attention on the development of a user-friendly exchange format with high expressivity in order to promote data communication of TMA results and TMA-OM supportive database applications. We developed TMA-TAB, a spreadsheet-based data format for TMA data submission to the TMA-OM supportive TMA database system. TMA-TAB was developed by simplifying, modifying and reorganizing classes, attributes and templates of TMA-OM into five entities: experiment, block, slide, core_in_block, and core_in_slide. Five tab-delimited formats (investigation design format, block description format, slide description format, core clinicohistopathological data format, and core result data format) were made, each representing the entities of experiment, block, slide, core_in_block, and core_in_slide. We implemented TMA-TAB import and export modules on Xperanto-TMA, a TMA-OM supportive database application, to facilitate data submission. Development and implementation of TMA-TAB and TMA-OM provide a strong infrastructure for powerful and user-friendly TMA data management.

Design and Implementation of a Data Processing and Visualization System for STEP-NC Programs

Over the last decade a new data interface for CAM/CNC integration has been established to replace ISO 6983. The new standard, ISO 14649 (STEP-NC), provides a comprehensive data model that describes both geometrical and technological information in an object-oriented way. In order to bridge the gap between such rich-information programs and the legacy CNC systems, this paper presents a framework for manipulating the manufacturing data in STEP-NC part programs. The proposed system provides a basic platform for STEP-NC program interpretation, geometry visualization, micro-process planning and program re-generation. Major issues relating to the realization of manufacturing information extraction and shop-floor-level process planning are addressed in particular, and a prototype for STEP-NC turning process is implemented to demonstrate the feasibility of the approach.