Myoung-Ah Kang

Spatial constraint modelling with a GIS extension of UML and OCL: application to agricultural information systems

In numerous cases, the modelling of Geographical Information Systems (GIS) is a difficult task. This fact is partially due to the natural complexity of spatial types and invariants. Based on this observation, the present paper aims at specializing the Unified Modelling Language (UML) and its associated Object Constraint Language (OCL) in order to facilitate the design of GIS. A complete study of the proposed extensions will be presented as well as several in-depth experiments in the domain of agricultural information systems.

First specifications of an information system for urban soundscape

Sounds are very important in our daily life with a twofold attitude for any citizen. On the one hand, music sounds are considered to enhance the quality of life, but on the other hand, traffic noise deteriorates the quality of life. Due to those contradictory characteristics, the new concept of soundscape tries to combine both positive and negative aspects of the auditory environment. Presently, and more and more in the future, any urban planning activities must try to diminish noise levels everywhere in the cities and also outside, for instance at the vicinity of airports. Local authorities daily receive complaints regarding noise, but they generally come from very quiet precincts, and practically never from very noisy zones such as along busy highways. So, it is very important to provide the urban decision-makers with an objective tool to compare not only noise levels but also soundscape, and to simulate the auditory impacts of any new urban developments. The goal of this paper is to give the first elements of the design of an information system dedicated to auditory information for cities. The paper describes the importance of the urban soundscape, the structure of the information system and some elements for the visualization of sounds.

Animated cartography for urban soundscape information

In urban areas, city noises represent today a great problem. They are real nuisances for city-dwellers. Noises are caused by traffic, road works, factories, and also by people. So taking into account noises on urban planning should enhance the quality of life of everybody. More knowledge about urban noise could allow to compare different citywards, to reduce noise in noisy places or to simulate sound impacts of new urban developments. These can be only done by means of noise information and a Geographic Information System (GIS) of a city. The long-term goal (five years) is to design a special GIS devoted to urban soundscape representation, management and simulation. For this purpose a lot of other information is required concerning urban landscape, traffic, and human behaviors. Pieces of information are quantitative but also qualitative. Because of this complexity of the whole phenomenon we first focus on soundscape representation, integration and visualization and leave simulation aspects for the second phase of the project. One of the most important aspects concerns information. Urban sounds are spatio-temporal data. So, to better understand sound evolution, we worked with dated data and enhance temporal aspect in animated cartography. The aim of the paper is to present the general specifications of the system and the prototype of animated cartography.

Indexing Values in Continuous Field Databases

With the extension of spatial database applications, during the last years continuous field databases emerge as an important research issue in order to deal with continuous natural phenomena during the last years. A field can be represented by a set of cells containing some explicit measured sample points and by arbitrary interpolation methods used to derive implicit values on non-sampled positions. The form of cells depends on the specific data model in an application. In this paper, we present an efficient indexing method on the value domain in a large field database for field value queries (e.g. finding regions where the temperature is between 20 degrees and 30 degrees). The main idea is to divide a field into subfields [15] in order that all of explicit and implicit values inside a subfield are similar each other on the value domain. Then the intervals of the value domain of subfields can be indexed using traditional spatial access methods, like R * -tree [1]. We propose an efficient and effective algorithm for constructing subfields. This is done by using the field property that values close spatially in a field are likely to be closer together. In more details, we linearize cells in order of the Hilbert value of the center position of cells. Then we form subfields by grouping sequentially cells by means of the cost function proposed in this paper, which tries to minimize the probability that subfields will be accessed by a value query. We implemented our method and carried out experiments on real and synthetic data. The results of experiments show that our method dramatically improves query processing time of field value queries compared to linear scanning.

Indexing field values in field oriented systems: interval Quadtree

With the extension of spatial database applications, field oriented systems emerge as an important research issue in order to deal with continuous natural phenomena during the last years. It however has a large volume of data and efficient indexing methods for field data are necessary to overcome the performance obstacle. In special, we introduce indexing methods for field value queries (i.e. searching some regions where the temperature is more 20 degrees). We introduce the concept of subfield and show how we make use of this concept to index field values in field oriented systems. We present two implementation methods based on Quadtree space subdivision. We modify traditional linear quadtree implementation method for field value query processing using subfields. We analyze the performance of our methods. Experimentation with real terrain data shows that proposed indexing methods improve the query processing time of field value queries in comparison with the case of no indexing method.

Using OCL to Model Constraints in Data Warehouses

Recent research works propose using Object-Oriented OO approaches, such as UML to model data warehouses. This paper overviews these recent OO techniques, describing the facts and different analysis dimensions of the data. The authors propose a tutorial of the Object Constraint Language OCL and show how this language can be used to specify constraints in OO-based models of data warehouses. Previously, OCL has been only applied to describe constraints in software applications and transactional databases. As such, the authors demonstrate in this paper how to use OCL to represent the different types of data warehouse constraints. This paper helps researchers working in the fields of business intelligence and decision support systems, who wish to learn about the major possibilities that OCL offer in the context of data warehouses. The authors also provide general information about the possible types of implementation of multi-dimensional models and their constraints.

Design and Implementation of Falling Star - A Non-Redudant Spatio-Multidimensional Logical Model for Document Stores.

In the context of Spatial Big Data, some NoSQL spatial DBMSs have been developed to deal with the Spatiality, Velocity, Variety, and Volume of Spatial Big Data. In this context, some works recently study NoSQL logical Data Warehouse (DW) models. However, these proposals do not investigate storing and querying spatial data. Therefore, in this paper we, propose a new logical model for document Spatial DWs. Moreover, motivated by the expressivity, readability and interoperability offered by UML profile, we represent our model using a UML profile. Finally, we present an implementation in document Spatial DBMSs.