Analysis of two-step index structure for complex spatial objects

An efficient index structure for complex multi-dimensional objects is one of the most challenging requirements in non-traditional applications such as geographic information systems, computer-aided design, and multimedia databases. In this paper we first propose a main memory data structure for complex multi-dimensional objects. Then, we present an extension of the existing multi-dimensional index structure. Among existing multi-dimensional index structures, the popular Ra-tree is selected. The Ra-tree is coupled with the main memory data structure to improve the performance of spatial query processing. An analytical model is developed for our index structure. Experimental results show that the analytical model is accurate, the relative error being below 15%. The performance of our index structure is compared with that of a state-of-the-art index structure by experimental measurements. Our index structure outperforms the state-of-the-art index structure due to its ability to reduce a large amount of storage.

Data warehouse systems store and process huge amounts of data. The main application of data warehouses is to support decision making process and to provide reports of various kinds. Those tasks require calculating aggregates, averages and other values. The calculations must be performed fast because it is very common that user wants to work interactively with a data warehouse system. There are two ways to increase the data warehouse performance. The first is to increase computing power by improving hardware infrastructure, and the second, to apply advanced, dedicated solutions like materialization, indexing etc. In this paper we present an indexing structure designed for spatial telemetric objects and suitable for processing streams of data. The presented solution is a result of integration of a few mechanisms. For spatial indexing we use CHR-Tree index which idea is based on the R-Tree index. To process data streams we use Materialized Aggregate List, a solution which allows processing data streams of any length and supports optional stream materialization. In the paper we present how those solutions are integrated into one indexing and caching structure. We also include efficiency test results showing the solution efficiency and scalability.

With the widespread application of Geographic Information System (GIS), three-dimensional spatial data, as the reflection of the real world entity, has an increasing amount of data, and the phenomenon of uneven data distribution appears. If a single spatial index structure is used to store and manage these data, there will be a waste of storage space and low query efficiency. A hybrid index structure based on 3D multi-level adaptive grid and R+ tree was proposed to solve these problems. The index structure was mainly composed of two structures, multi-level grid and R+ tree. Firstly, the data set was processed by the multi-level automatic grid algorithm based on normal distribution, and the length, width and height of the grid were obtained. Secondly, a multi-level adaptive grid structure was used to partition the data space quickly and effectively, and the advantage of zero overlap of the intermediate nodes of the R+ tree was used for efficient indexing. Finally, the maintenance and query algorithms of the index structure were given in detail, which solved the problem of low index establishment and retrieval efficiency under the condition of uneven distribution of massive data sets. In this paper, a data set subject to Gauss distribution was used to simulate the distribution of three-dimensional data. Through a large number of experimental comparison tests, it was proved that the hybrid index structure based on 3D multi-level adaptive grid-R+ tree proposed in this paper had good performance in both index structure construction and query in the case of massive data sets or uneven data distribution.

A flexible indexing structure supporting multi-attribute database applications: MAIN

An increasing number of emerging web database applications deal with large georeferenced data sets. However, exploring these large data sets through spatial queries can be very time and resource intensive. The need for interactive spatial queries has arisen in many applications such as Geographic Information Systems (GIS) for efficient decision-support. In this paper, we propose a new interactive spatial query processing technique for GIS. We present a family of the Incremental Refining Spatial Join (IRSJ) algorithms that can be used to report incrementally refined running estimates for aggregate queries while simultaneously displaying the actual query result tuples of the data sets sampled so far. Our goal is to minimize the time until an acceptably accurate estimate of the query result is available (to users) measured by a confidence interval. Our approach enables more interactive data exploration and analysis. While similar work has been done in relational databases, to the best of our knowledge, this is the first work using this approach in GIS. We investigate and evaluate different sampling methodologies through extensive experimental performance comparisons. Experiments on both real and synthetic data show an order of magnitude response time improvement relative to the final answer obtained when using a full R-tree join. We also show the impact of different index structures on the performance of our algorithms using three known sampling methods.

Spatial indexing technology is widely used in Geographic Information Systems (GIS) and spatial databases. As a data retrieval technology, spatial indexing is becoming increasingly important in the big-data age. The purpose of this study is to propose a unified indexing strategy for the mixed data of a future marine GIS. First, data organisation of the system is described. Second, the display condition of each type of data is introduced. These conditions are the basis for the construction of a unified indexing structure. Third, a unified indexing structure for mixed data is presented. The construction process and the search method of the indexing structure are described. Finally, we implement the indexing strategy in our system “Automotive Intelligent Chart Three-dimensional Electronic Chart Display and Information Systems” (AIC 3D ECDIS). Our strategy can provide fast and integrated data retrieval. The spatial indexing strategy we propose breaks through the limitation of data types in our system. It can also be applied in other GIS systems. With the advent of the big-data age, mixed data indexing will become more and more important.

Scalable multi-feature index structure for music databases

In many modern applications such as biometric identification systems, sensor networks, medical imaging, geology, and multimedia databases, the data objects are not described exactly. Therefore, recent solutions propose to model data objects by probability density functions(pdf). Since a pdf describing an uncertain object is often not explicitly known, approximation techniques like Gaussian mixture models(GMM) need to be employed. In this paper, we introduce a method for efficiently indexing and querying GMMs allowing fast object retrieval for arbitrary shaped pdf. We consider probability ranking queries which are very important for probabilistic similarity search. Our method stores the components and weighting functions of each GMM in an index structure. During query processing the mixture models are dynamically reconstructed whenever necessary. In an extensive experimental evaluation, we demonstrate that GMMs yield a compact and descriptive representation of video clips. Additionally, we show that our new query algorithm outperforms competitive approaches when answering the given probabilistic queries on a database of GMMs comprising about 100.000 single Gaussians.

The management of large collections of music data in a multimedia database has received much attention in the past few years. In the most of current works, the researchers extract the features, such as melodies, rhythms and chords, from the music data and develop indices that will help to retrieve the relevant music quickly and improve the query accuracy. Several reports have pointed out that these features of music can be transformed and represented in the forms of music feature strings. However, these approaches lack of scalability while increasing the music data. Recently, we proposed an approach to transform the music data into a numeric forms and developed an index structure base on R-tree for effective retrieval. This numeric index approach performed more efficiently than existing string index approaches for music database retrieval. In this paper, we will extend our study to develop a multi-feature numeric index structure for music data. Our experimental results show that the new proposed structure outperforms existing multi-feature string index approaches.

Data acquired from site surveys provide an essential resource to various exploration and production activities, such as field development planning, well positioning, and subsea equipment positioning. For many years, site survey data has been delivered as a Computer-aided Design (CAD) product. As operators move into a Geographic Information Systems (GIS) environment, shortfalls from CAD-based workflows have become obvious. This paper presents a method of managing site survey data based on geo-information management principles and practices. The methodology presented in this paper defines a GIS data model for seabed survey data interpretation that satisfies GIS query, presentation, and data exchange purposes. This paper also defines a standard for GIS seabed survey data deliverables from contractors to operators, including methods and processes to move the model to/from CAD-based applications. The implementation of the data model has proven to be a relative success and allows for a better integration of subsurface applications internally. The results have helped define an efficient contractor-operator data exchange process by eliminating data ambiguity and enabling seamless GIS data transfer. Results have also produced a more intelligent seabed survey GIS dataset with rules and behaviors capability offered by an ArcGIS Geodatabase embedded into the data model. Use of a standard GIS data model and a standard list of GIS data deliverables required from contractors to operators will allow project teams to fully embrace the power of GIS data integration and allow nearly seamless and lossless movement of CAD/GIS representations of the model. Introduction In order to reach maximum potential benefit of data provided from seabed site surveys throughout the E & P lifecylcle (Figure 1), there is a need to ensure that data delivered from survey contractors to operators is done so in a structured, efficient, and consistent manner.

We are on the edge of a revolution in the way we visualize and query digital data about our environment. To date, computer displays of our environment in the third dimension have been limited to computer-aided design (CAD) packages and the query of related data limited to geographical information systems (GIS) packages in two dimensions. The current innovation wave across the spatial data information field is based on the development and dissemination of three-dimensional GIS (3-D GIS) which allows data to be visualized and queried on an x, y and z axis plane. A number of the key players in information visualization allow conventional two-dimensional data to be viewed and exported in a three-dimensional format, currently using the standard Virtual Reality Modeling Language 2.0 (VRML 2.0). However such methods of visualization and data query are limited in their practicality. The move towards 3-D GIS in standard packages has been rather hit and miss, with the third dimension often only used as a substitute for basic CAD-like visualization. We argue here that 3-D GIS will only become a reality when it is directly linked with CAD models; and that the Internet is the most appropriate medium through which this is most likely to occur. We illustrate these arguments in an overview of research into the virtual city in general and our own development of ‘Virtual London’ in particular. Further, we explore the rise of the global virtual city, a network of virtual cities that provide an insight into the future of digital space.

Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not. In this exploratory research paper, we start from this premise and posit that all existing index structures can be replaced with other types of models, including deep-learning models, which we term learned indexes. The key idea is that a model can learn the sort order or structure of lookup keys and use this signal to effectively predict the position or existence of records. We theoretically analyze under which conditions learned indexes outperform traditional index structures and describe the main challenges in designing learned index structures. Our initial results show, that by using neural nets we are able to outperform cache-optimized B-Trees by up to 70% in speed while saving an order-of-magnitude in memory over several real-world data sets. More importantly though, we believe that the idea of replacing core components of a data management system through learned models has far reaching implications for future systems designs and that this work just provides a glimpse of what might be possible.

본 논문에서는 도로망에서 이동하는 객체들의 현재 위치를 효율적으로 갱신하는 색인 기법을 제안한다. 기존의 도로망 모델은 이웃한 도로 세그먼트의 연결 정보를 포함하지 않기 때문에 객체가 이웃한 도로 세그먼트로 이동할 때 갱신 성능을 저하시킨다. 본 논문에서는 이러한 문제점을 해결하기 위해 교차점 기반 도로망 모델과 새로운 색인 구조를 제안한다. 제안하는 교차점 기반 도로망 모델은 도로를 분할할 때 교차점을 포함하도록 분할하여 연결 정보가 유지되도록 한다. 성능 평가를 통해 제안하는 색인 기법이 기존 색인 구조에 비해 이동 객체의 갱신 성능이 3배 향상됨을 보인다. In this paper, we propose an indexing method for efficiently updating current positions of moving objects on road networks. The existing road network models increase update costs when objects move to adjacent road segments because their connectivity is not preserved. We propose an intersection based network model and a new index structure to solve this problem. The proposed intersection based network model preserves network connectivity through splitting road networks to contain intersection nodes always. The proposed index structure In our experiments, we show that our method is about 3 times faster than an existing index structure in terms of update costs.

While the use of three-dimensional (3D) geographical information system (GIS) is becoming in rapid development and being used in various fields such as urban and regional planning, disaster management and planning, mobile navigation and etc., commercial and open source GIS software packages tend to offer 3D-GIS functionalities for their products. On the basis, GIS analysis functions are to provide information with respect to geographical location and by having 3D spatial data as an input, it will give advantages in providing horizontal position information. However, to analyze moving objects (temporal) in 3D seems not an easy task and not fully supported by current GIS platform packages. Previously in two-dimensional (2D) GIS practice, main issue addressed by researchers in managing temporal spatial objects is GIS packages were designed based on hardware and software constraints whereby it should be based on the temporal spatial objects ontology. Nowadays, the trend of managing temporal 3D data is via 3D spatial simulation or animation. This approach will not in assistance for GIS users in conducting spatial queries. Without having a suitable ontology and valid topological data structure for temporal 3D data, it will cause repetitive of temporal data (redundancy) and complications in executing spatial analysis in 3D environment. Therefore this paper focuses on the ontology for managing moving 3D spatial objects (i.e. air pollution, flood). The characteristics of moving objects were reviewed thoroughly by categorizing it based on its different appearances. Moreover, existing methods in managing temporal database were addressed and discussed for its practicalities. Another important aspect in managing temporal 3D objects is the implementation of topological data structures for 3D spatial objects were reviewed. In the last section of this paper it summarized the issues and further ideas towards implementing and managing temporal 3D spatial objects in GIS based on the Geoinformation Ontology (GeO).

Boundaries of land have been documented and recorded throughout history dating back over 2000 years ago. Land has been an important commodity throughout time, and a move toward building a coordinate-based land cadastre has been implemented in other countries across the world. It is used in parts of Europe, British Columbia, and the Middle East to manage land records. The County of Riverside needed a process for checking and reporting surveyed land divisions that were submitted in the form of computer aided design (CAD) files, and loading them into a geographic information system (GIS). The current CAD data submitted had errors with the geometry, and in most cases did not have a projected coordinate system. Most of the CAD files were not used for their intended purpose: which was to be shared with the Riverside County Assessor’s staff to aid them in creating and updating their Assessor Parcel Layer. Without the digital data the Assessor’s staff followed its business practice of re-entering the parcels one at a time. This created redundancy of work since the same data supplied by the Land Surveyor or Civil Engineer was identical. Some of the problems listed above uncovered the need to come up with a digital submission standard, and an automation tool to help prepare the data for loading into the Parcel Fabric. The goal of the project was to create a tool that will automatically check the surveyed land division for compliance prior to approval; this tool is named County Automated Terrestrial CAD Helper (CATCH). CATCH uses GIS technology to automatically identify mapping errors and report these errors back to the Land Surveyor or Civil Engineer who created the data. CATCH has been well received by the professional engineering community, from a series of stakeholder meetings held at county offices to introduce the project to private industry professionals and county staff. These meetings were critical in the success of CATCH, and helped bring up issues that the industry have had in submitting their digital files in the past. Also, CATCH could be well suited as the platform for tracking and maintaining other county assets in a GIS such as: grading plans, storm drains, gas lines, and other critical utilities that come in the form of digital CAD files. The problem that was solved was having an accurate foundation: and that being the boundary survey tied to a CAD file that utilized global navigation satellite system (GNSS) and global positioning system (GPS) technology.