Representing Ecological Niches in a Conceptual Model

The Human Genome Project (HGP) plans to sequence the human genome by the beginning of the next century. It will generate DNA sequences of more than 10 billion bases and complex marker sequences (maps) of more than 100 million markers. All of these information will be stored in database management systems (DBMSs). However, existing data models do not have the abstraction mechanism for modelling sequences and existing DBMS`s do not have operations for complex sequences. This work addresses the problem of sequence modelling in the context of the HGP and the more general problem of an extensible object data model that can incorporate the sequence model as well as existing and future data constructs and operators. First, we proposed a general sequence model that is application and implementation independent. This model is used to capture the sequence information found in the HGP at the conceptual level. In addition, abstract and biological sequence operators are defined for manipulating the modelled sequences. Second, we combined many features of semantic and object oriented data models into an extensible framework, which we called the ``Extensible Object Model``, to address the need of a modelling framework for incorporating the sequence data model with other types of data constructs and operators. This framework is based on the conceptual separation between constructors and constraints. We then used this modelling framework to integrate the constructs for the conceptual sequence model. The Extensible Object Model is also defined with a graphical representation, which is useful as a tool for database designers. Finally, we defined a query language to support this model and implement the query processor to demonstrate the feasibility of the extensible framework and the usefulness of the conceptual sequence model.

In the field of environmental management, inefficient piecemeal sectorial approaches are still widespread, particularly in water resources management, where concerns and decisions are usually split among a set of rather weakly linked stakeholders. Planning and management problems to be addressed are in most cases complex and need to be tackled in a global, integrated and holistic way, including from the different areas of science and knowledge from the various stakeholders. Therefore, the sharing and integration of data, knowledge and models has become a major issue. A lot of effort has been made in recent years to develop such integrative tools, including systems (IS), decision support systems (DSS) or integrated modelling frameworks (IMF). Although these tools achieved great progress in terms of linkages, there is currently no environment providing a full integration of the various kinds of data, models, and their visualisation. This is the general issue tackled by the present thesis, with developments based on a semantic, systemic formalism, and applications focusing on water management issues. The first development step taken was the creation of a systemic description of water management. Albeit the various aspects of water management are abundantly documented and well-known, an integrated description including interconnections was lacking. Therefore, a graphic representation of interconnected elements annotated with definitions was created. This innovative result constitutes an ontology (a formal representation of a knowledge domain) providing a robust reference and a fairly exhaustive reminder of the complexity of the water management field, including transdisciplinary aspects. In the second step, a data model was created, based on the new SYSMOD language. The latter proposes a new graphical language uniting the ontological and systemic approaches, with a strong emphasis on interactions. Whereas existing data models are generally specific to a field or designed for a target application, this new data model is generic and transdisciplinary. It can handle any kind of systemically organised data, which potentially includes any sort of environmental data. To visualise and manage the systems-based, generic data stored within the database (created on the basis of the generic data model) a new kind of visualisation was developed, proposing diagrams of interconnected nodes. Whereas existing systems are often data warehouses without a user-friendly graphical user interface, or geographic systems focussing on spatial data, this new diagram visualisation proposes views including spatial and non-spatial elements (such as lakes, power plants, stakeholders or laws) interconnected by interactions (such as fluxes or influences). Bound to the database, the tool was called an information on the system (ISS). It provides a way of graphically managing and integrating the systemically organised, generic, transdisciplinary data. Furthermore, the systems approach fosters the apprehension and communication of complex situations in a holistic way (involving many different elements, influences and interactions from various fields), through their representation into thematic views. In complement to the diagram visualisation, a reporting tool was developed to display the data linked to elements (numeric values, comments, files, etc.) in a web-browser fashion. To interoperate with external models, another module was developed on the top of the ISS. Finally, a fully-fledged general user interface was created to integrate all the previous developments into a single environment. To visualise the different facets of elements, a geographic and a chart view were added, in complement to the reporting view. This final tool was called the generic decision support (GenDSS), as its application to given situations can give rise to a series of views and linkages to models, thereby providing specific DSS functionalities for these situations. The successive developments were tested in Birmingham (United Kingdom). Test results indicated that the GenDSS is currently limited to managing a few hundred elements; beyond this quantity, the loading times and the user interface reactivity can become long and unresponsive. On the other hand, the application also demonstrated the strengths of the GenDSS which provides an innovative integrated solution to centralise transdisciplinary data in various formats (e.g. numeric values, texts, geometries, files), to holistically describe situations using complementary visualisations, and to test scenarios using externally-linked models. Thus, the GenDSS may prove an adequately versatile solution for large institutions or enterprises dealing with complex situations, heterogeneous and transdisciplinary data, and where requirements are continuously evolving, such as: a car manufacturing corporation (which would involve several different production and research sites in different countries with different regulations), a hospital, or a strategic environmental planning network (where the tool could help to break the transdisciplinary, sectorial barriers). In the case of water, the GenDSS could prove very useful to achieve a truly integrated water management approach.

Activity-centric data gather feedback on students' learning to enhance learning effectiveness. The heterogeneity and multigranularity of such data require existing data models to perform complex on-the-fly computation when responding to queries of specific granularity. This, in turn, results in latency. In addition, existing data models are inefficient in storing computed results, which are often required for follow-up analysis. These follow-up analyses depend largely on stakeholder objectives, which often impose constraints to the analysis process. In this article, we propose a context-based data model that addresses two challenges associated with learning analytics: the increased processing time due to multiple data granularities required from various stakeholder objectives, and the lack of support for archiving and updating of new information that exist during iterative analysis. We demonstrate how the proposed model can help support analysis and visualization via the XuetangX and ASSISTments datasets. Results show that although our proposed data model requires preprocessing, it requires less time to process queries associated with learning-activity attributes of various granularities compared to existing data models.

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.

The use of a proper data model is a way to introduce rigour in requirements analysis, traditionally considered the most informal stage of software development, and responsible for the more costly errors. Several data models have emerged, but their comparative value is unclear. We think that an appraisal is only possible if the nature — and not only the goal — of requirements analysis is clearly perceived. We investigate this point and emphasise that requirements analysis is an activity of acquiring real-world knowledge, thereby forming a theory in which objectives can be stated and a solution specified. A suited language should thus restrict as little as possible the freedom of expression when describing some part of the world. A number of requirements are derived from this statement, such as the possibility to describe individual objects, as well as groups of objects, to explicitly refer to a global continuous time, to handle undefinedness, to allow simultaneous events, etc. When assessing the various existing data models with respect to these requirements, the entity-relationship model is found a suitable basis, but still lacking essential features. We extend it in a model called ERAE (entity, relationship, attribute, event), which is presented informally and illustrated on examples.

One of the goals in the design of database machines of the future is their generality. In addition to being capable of carrying out the common database management functions with high reliability and performance, some of these machines are intended to support more than one data model. A specific database machine, known as the DBC, is intended to support several existing data models. Although the DBC supports many data models, we single out the relational data model for this discussion. In particular, we have tried to concentrate mainly on the subject of database representation and query translation of System R-like database management systems. Some estimates of the storage requirements and performance gains are given in this paper. However, due to limited space, the detailed analysis is shown elsewhere in [22].

The development of an Electronic Health Record (EHR) system requires a well-defined data set and a robust data model to support complex clinical workflows, interoperability, and data quality. Many existing EHR implementations lack standardized and integrated data models, resulting in redundancy, semantic inconsistency, and limited support for secondary data use. This study aims to develop a comprehensive EHR data model based on a Minimum Data Set (MDS) that systematically represents medical service processes across emergency, outpatient, inpatient, and surgical care. The proposed approach involves the design of a conceptual, logical, and physical data model. Business processes were first analysed to identify relationships among clinical and administrative data classes, which were then transformed into a conceptual data model. The logical data model was developed through database normalization and schema definition, while the physical data model was constructed to represent the actual database structure for implementation. The results demonstrate a structured EHR data model comprising 21 interrelated data classes that reflect real-world medical service workflows. The conceptual data model establishes clear entity relationships, supporting data consistency and interoperability. The logical data model provides a normalized SQL-based schema that minimizes redundancy and enhances data integrity, while the physical data model enables efficient data storage and access. A prototype EHR system was implemented to evaluate the feasibility of the proposed data model, showing stable performance, usability, and alignment with functional requirements. This study concludes that a standardized EHR data model derived from an MDS can effectively support comprehensive clinical documentation, interoperability, and future scalability. The proposed model provides a strong foundation for developing national or institutional EHR systems and can serve as a reference for further EHR data standardization efforts.

On the basis of analyzing of the marine environment spatio-temporal data characteristics and the existing data model, proposes a conceptual model for marine environment data based on the feature and field to achieve integration of description and expression of feature, field, time, space and semantic domains. Designs and implements the service-oriented marine environment data organization and storage using Geography Markup Language (GML). Efficient data organization and management is crucial to marine environment visual services.

Conceptual modeling is a learning task essential to students of computer science, software engineering and related programs. Construed as a complex task, surprisingly little is known about the actual act of conceptual modeling, and about modeling difficulties learners experience. Combining complementary modes of observation of learners’ modeling processes, we study modeling difficulties encountered while performing a data modeling task. Using the concept of cognitive breakdown, we analyze audiovisual protocols of the individual modelers’ modeling processes, recordings of their interactions with the employed modeling software tool and survey data of modelers about their perception of encountered modeling difficulties. In an exploratory study and a follow-up study, we identify eight types of modeling difficulties related to modeling entity types, generalization hierarchies, relationship types, attributes and cardinalities. The identified types of modeling difficulties contribute to a better and more complete understanding of data modeling processes intended to inform design science research on modeling assistance for data modelers at different stages of their learning and mastering of conceptual data modeling.

With new aviation market entrants such as Urban Air Mobility (UAM) vehicles, the role aviation will take in seamless, end-to-end multimodal transportation is evolving. Travelers will likely be able to request on-demand, point-to-point transportation through air taxis in the not-to-distant future. Previous multimodal research efforts have focused on surface urban mobility, where multiple modes of ground transportation compete with and complement each other, ignoring the growing role that aviation will play going forward. Existing public transportation data exchange models, tailored for their respective systems, likewise, have not yet accounted for this looming transportation transformation nor for widespread multimodal end-to-end, seamless transporting. To date, the FAA has succeeded in establishing a robust data exchange architecture to support traditional air transportation, but to facilitate this evolution of the public airspace system with respect to UAM and other emerging air vehicle systems, new and revised data exchange models are necessary. Existing data exchange models in need of revision include the International Civil Aviation Organization's (ICAO) Flight Information Exchange Model (FIXM) and the General Transit Feed Specification (GTFS) [2], [3]. New data exchange models in need of creation include the Passenger Information Exchange Model (PIXM), the Operation Information Exchange Model (OIXM), and Vehicle Information Exchange Model (VIXM) [1]. The research here explored these data models, identifying and defining preliminary conceptual data elements necessary to support seamless, end-to-end mobility. The conceptual model herein proposed is holistic and considers all modes of transportation – walk, car, bus, rail, boat, air, etc. - and looks to incorporate the most promising transportation data exchange models from among these transportation systems.A realistic multimodal travel scenario subject to disruptive events (such as severe weather) was developed for the purpose of identifying the necessary exchange of data to reduce the impact of the disruptive events on the traveler. This work helped inform the next steps in the project, the definition of multimodal data exchange models and the development of a corresponding multimodal transportation conceptual data model. The scenario includes Urban Air Mobility (UAM) vehicles that are intended to serve as short haul providers operating in a congested urban metro environment to bypass surface traffic congestion. New aviation market entrants, such as UAM, will likely not operate entirely within a traditional gate to gate model and are eventually likely to use a model similar to on-demand surface transportation such as ride share. Uber Elevate has already been proposing this type of application for their future air taxis [4]. Accommodating these new aviation market entrants will require further extensions to the FIXM (a second package for Unmanned Aircraft System (UAS) is already planned by the FIXM committee), adoption and enhancement of existing industry data exchange models, and entirely new data models. GTFS is the industry-leading and international de facto public transportation data exchange standard and has an extension called "flex" for supporting on-demand mobility, though has been limited to surface applications thus far [3], [5]. Alongside FIXM and GTFS, new models are necessary to facilitate seamless, end-to-end mobility. Proposed models include the Vehicle Information Exchange Model (VIXM), the Passenger Information Exchange Model (PIXM), and the Operator Information Exchange Model (OIXM) [1].This paper serves as an initial exploration of a data exchange model for future of transportation. The authors envision a future where a traveler can easily plan, dynamically re-plan, and track the real-time progress of a multimodal trip from the convenience of a smartphone application. The authors include a description of a future smartphone application to help illustrate the concept (Section 5). Section 6 provides a brief history of multimodal data exchange initiatives. Section 7 includes a brief discussion of next steps and recommendations for continued research.

Abstract. A new version of the Land Administration Domain Model (LADM) has been discussed and is under further development in ISO/TC 211 on Geographic Information. One of the extending parts is where the model can accommodate complex and advanced marine properties and cadastral objects. Currently, the fundamentals part of this new version (LADM Edition II) has been examined by the committee, and a few elements need to be considered, especially for marine space georegulation. Based on the possibility of embedding LADM with marine cadastre as agreed by several researchers, the concept of marine cadastre data model within land administration context has been anticipated in many countries (e.g., Canada, Greece, Turkey, Australia, and Malaysia). Part of the research focused on constructing and developing the appropriate data models to manage marine spaces and resources most effectively. Several studies have attempted to establish a conceptual model for marine cadastre in Malaysia. However, there is still no acceptable marine data model. Thus, this paper proposed a marine data model for Malaysia based on the international standard, LADM. The approach, by definition, can be applied to the marine environment in terms of controlling and modelling a variety of rights, responsibilities, and restrictions. The Unified Modelling Language (UML) application was utilized to construct the conceptual and technical models via Enterprise Architect as part of the validation process. The data model was constructed within the marine's concept in Malaysia to meet international standards. The features of the data model were also discussed in the FIG workshop (9th LADM International Workshop 2021). The experiment on the data model also includes 3D visualization and simple query.

Computer applications in non-traditional areas have put requirements on conceptual data modeling. Some conceptual data models, being the tool of design databases, have been proposed. However, information in real-world applications is often vague or ambiguous. Currently, less research has been done in modeling imprecision and uncertainty in conceptual data models and the design of databases with imprecision and uncertainty. In this chapter, a different level of fuzziness based on fuzzy set and possibility distribution theory will be introduced into the IFO data model and the corresponding graphical representations will be given. The IFO data model is then extended to a fuzzy IFO data model, denoted IF2O. In particular, we provide the approach to mapping an IF2O model to a fuzzy relational database schema.

Developing a three-dimensional (3D) data model for Geographic Information Systems (GIS) is an essential and complex issue. 3D modelling in GIS is becoming ever more important for the development of cyber cities and digital earth, which have recently become feasible. A competent 3D model forms an efficient foundation for 3D visualization, query and spatial analysis. As a development of the existing 3D models, this study proposes particular improvements in handling complex 3D objects. We present an object-oriented data model for handling complex 3D objects in GIS. First, the conceptual data model is developed based on the principle of object-oriented (OO) data modelling. This model is designed based on the following three basic geometric elements: node, segment and triangle. Accordingly, the abstract geometric objects are defined: including points, lines, surfaces and volumes. Second, the corresponding 3D logical model is designed based on the defined abstract objects and the relationships between them. Third, a formal representation of the 3D spatial objects is described in detail. Fourth, a prototype 3D GIS is developed based on the proposed 3D data model. Finally, we describe the results of an experimental study to reconstruct 3D objects using this 3D GIS and a comparison with the performance of other 3D data models. The proposed model is able to handle complex objects, such as complex buildings and TV towers, which is an essential functionality for building large-scale cyber cities, such as for Hong Kong. The proposed data model proves to be very efficient, particularly in visualization and rendering. The experimental results show which the data volume of the proposed model is compacted and the visualization speed for 3D objects is improved, compared with the existing models.

The vision of a Digital Earth calls for more dynamic information systems, new sources of information, and stronger capabilities for their integration. Sensor networks have been identified as a major information source for the Digital Earth, while Semantic Web technologies have been proposed to facilitate integration. So far, sensor data are stored and published using the Observations & Measurements standard of the Open Geospatial Consortium (OGC) as data model. With the advent of Volunteered Geographic Information and the Semantic Sensor Web, work on an ontological model gained importance within Sensor Web Enablement (SWE). In contrast to data models, an ontological approach abstracts from implementation details by focusing on modeling the physical world from the perspective of a particular domain. Ontologies restrict the interpretation of vocabularies toward their intended meaning. The ongoing paradigm shift to Linked Sensor Data complements this attempt. Two questions have to be addressed: (1) how to refer to changing and frequently updated data sets using Uniform Resource Identifiers, and (2) how to establish meaningful links between those data sets, that is, observations, sensors, features of interest, and observed properties? In this paper, we present a Linked Data model and a RESTful proxy for OGC's Sensor Observation Service to improve integration and inter-linkage of observation data for the Digital Earth.

A conceptual data model coupling with physically-based distributed hydrological models based on catchment discretization schemas