Indexing Techniques for Spatiotemporal Databases

2011 ◽  
pp. 1911-1916
Author(s):  
George Lagogiannis ◽  
Christos Makris ◽  
Yannis Panagis ◽  
Spyros Sioutas ◽  
Evangelos Theodoridis ◽  
...  
Keyword(s):  
Intelligent Transportation Systems ◽  
Environmental Science ◽  
Query Languages ◽  
Data Models ◽  
Time Dependent ◽  
Abstract Data Type ◽  
Spatiotemporal Databases ◽  
Geometric Properties ◽  
Research Areas ◽  
Database Research

We can define as spatiotemporal any database that maintains objects with geometric properties that change over time, where usual geometric properties are the spatial position and spatial extent of an object in a specific d-dimensional space. The need to use spatiotemporal databases appears in a variety of applications such as intelligent transportation systems, cellular communications, and meteorology monitoring. This field of database research collaborates tightly with other research areas such as mobile telecommunications, and is harmonically integrated with other disciplines such as CAD/CAM, GIS, environmental science, and bioinformatics. Spatiotemporal databases stand at the crossroad of two other database research areas: spatial databases (Güting, 1994; Gaede & Gunther, 1998) and temporal databases (Salzberg & Tsotras, 1999). The efficient implementation of spatiotemporal databases needs new data models and query languages and novel access structures for storing and accessing information. In Güting, Bohlen, Erwig, Jensen, Lorentzos, Schneider, and Vazirgiannis (2000) a data model and a query language capable of handling such time-dependent geometries, including those changing continuously that describe moving objects, were proposed; the basic idea was to represent time-dependent geometries as attribute data types and to provide an abstract data type extension to the traditional database data models and query languages. In that paper, it was also discussed how various temporal and spatial models could possibly be extended to be spatiotemporal models.

scholarly journals Data Portability Among Providers o Platform as a Service

2013 ◽  
Vol 21 (Special-Issue) ◽  
pp. 7-11
Author(s):  
Darko Androcec
Keyword(s):  
Data Storage ◽  
Query Languages ◽  
Data Models ◽  
Service Model ◽  
Data Types ◽  
Data Manipulation ◽  
Platform As A Service ◽  
Cloud Providers ◽  
Data Portability ◽  
Lock In

Abstract Platform as a service model has certain obstacles, including data lock-in. It is expensive and time-consuming to move data to the alternative providers. This paper presents data storage options in platform as a service offers and identifies the most common data portability problems between various commercial providers of platform as a service. There are differences among their storage models, data types, remote APIs for data manipulation and query languages. Representing data models of platform as a service and data mappings by means of ontology can provide a common layer to achieve data portability among different cloud providers.

scholarly journals Review of Clinical Research Informatics

2020 ◽  
Vol 29 (01) ◽  
pp. 193-202
Author(s):  
Anthony Solomonides
Keyword(s):  
Artificial Intelligence ◽  
Clinical Research ◽  
Big Data Analytics ◽  
Medical Knowledge ◽  
Data Models ◽  
Research Areas ◽  
Personal Awareness ◽  
Real World Evidence ◽  
Clinical Research Informatics ◽  
Active Research

Objectives: Clinical Research Informatics (CRI) declares its scope in its name, but its content, both in terms of the clinical research it supports—and sometimes initiates—and the methods it has developed over time, reach much further than the name suggests. The goal of this review is to celebrate the extraordinary diversity of activity and of results, not as a prize-giving pageant, but in recognition of the field, the community that both serves and is sustained by it, and of its interdisciplinarity and its international dimension. Methods: Beyond personal awareness of a range of work commensurate with the author’s own research, it is clear that, even with a thorough literature search, a comprehensive review is impossible. Moreover, the field has grown and subdivided to an extent that makes it very hard for one individual to be familiar with every branch or with more than a few branches in any depth. A literature survey was conducted that focused on informatics-related terms in the general biomedical and healthcare literature, and specific concerns (“artificial intelligence”, “data models”, “analytics”, etc.) in the biomedical informatics (BMI) literature. In addition to a selection from the results from these searches, suggestive references within them were also considered. Results: The substantive sections of the paper—Artificial Intelligence, Machine Learning, and “Big Data” Analytics; Common Data Models, Data Quality, and Standards; Phenotyping and Cohort Discovery; Privacy: Deidentification, Distributed Computation, Blockchain; Causal Inference and Real-World Evidence—provide broad coverage of these active research areas, with, no doubt, a bias towards this reviewer’s interests and preferences, landing on a number of papers that stood out in one way or another, or, alternatively, exemplified a particular line of work. Conclusions: CRI is thriving, not only in the familiar major centers of research, but more widely, throughout the world. This is not to pretend that the distribution is uniform, but to highlight the potential for this domain to play a prominent role in supporting progress in medicine, healthcare, and wellbeing everywhere. We conclude with the observation that CRI and its practitioners would make apt stewards of the new medical knowledge that their methods will bring forward.

Data Models and Query Languages for Linked Geospatial Data

2012 ◽  
pp. 290-328 ◽  
Author(s):  
Manolis Koubarakis ◽  
Manos Karpathiotakis ◽  
Kostis Kyzirakos ◽  
Charalampos Nikolaou ◽  
Michael Sioutis
Keyword(s):  
Query Languages ◽  
Data Models ◽  
Geospatial Data

scholarly journals Data models and query languages for spatial databases

1998 ◽  
Vol 25 (1-2) ◽  
pp. 29-53 ◽  
Author(s):  
Jan Paredaens ◽  
Bart Kuijpers
Keyword(s):  
Spatial Databases ◽  
Query Languages ◽  
Data Models

Graph data models, query languages and programming paradigms

2018 ◽  
Vol 11 (12) ◽  
pp. 2106-2109 ◽  
Author(s):  
Alin Deutsch ◽  
Yannis Papakonstantinou
Keyword(s):  
Query Languages ◽  
Data Models ◽  
Graph Data ◽  
Programming Paradigms

scholarly journals Routing and Mobility Management in the Internet of Things

2020 ◽  
Author(s):  
Bruno Pereira Santos ◽  
Luiz Filipe Menezes Vieira ◽  
Antonio Alfredo Ferreira Loureiro
Keyword(s):  
Internet Of Things ◽  
Mobility Management ◽  
Intelligent Transportation Systems ◽  
Computer Network ◽  
Smart Cities ◽  
Transportation Systems ◽  
The Internet ◽  
Research Areas ◽  
New Research ◽  
The Impact

This Ph.D. Thesis proposes new techniques for routing and mobility management for Internet of Things (IoT). In the future IoT, everyday mobile objects will probably be connected to the Internet. Currently, static IoT's devices have already been connected, but handle mobile devices suitably still being an open issue in IoT context. Then, solutions for routing mobility detection, handover, and mobility management are proposed through an algorithm that integrates Machine Learning (ML) and mobility metrics to figure out devices' mobility events, which we named Dribble. Also, an IPv6 hierarchical routing protocol named Mobile Matrix to boost efficient (memory and fault tolerance) end-to-end connectivity over mobility scenarios. The Thesis contributions are supported by numerous peer-reviewed publications in national and international conferences and journals included in ISI-JCR. Also, the applicability of this Thesis is evident by showing that our results overcome state-of-the-art in static and mobile scenarios, as well as, the impact of the proposed solutions is a step forward in at least two new research areas so-called Internet of Mobile Things (IoMT) and Social IoT, where devices move around and do social ties respectively. Moreover, during the Ph.D. degree, the author has contributed to different computer network fields rather than routing by publishing in areas like social networks, smart cities, intelligent transportation systems, software-defined networks, and parallel computing.

Agricultural hydroinformatics: agricultural water systems management as a new application for hydroinformatics

2020 ◽  
Author(s):  
Paul Celicourt ◽  
Silvio J. Gumiere ◽  
Alain Rousseau
Keyword(s):  
Agricultural Development ◽  
Environmental Science ◽  
Simulation Models ◽  
Water Systems ◽  
Agricultural Systems ◽  
Agricultural Water ◽  
Systems Management ◽  
Research Areas ◽  
Systems Research ◽  
Wide Range

<p>Hydroinformatics, throughout its more than 25 years of existence, has been applied to a set of research areas. So far, these applications include: hydraulics and hydrology, environmental science and technology, knowledge systems and knowledge management, urban water systems management.</p><p>This paper introduces agricultural water systems management as a new application for hydroinformatics, and terms it as “agricultural hydroinformatics”. It presents a discipline-delineated conceptual framework originating from the particularities of the socio-technical dimension of applying hydroinformatics in agriculture. It epitomizes the wholeness and inter-dependencies of agricultural systems studies and modelling. It is suitable to support, not only integrated agricultural water resources management in particular, but also agricultural sustainability in general, in addition to a wide range of agricultural development situations beyond connections between agro-economic and water engineering development and its socio-economic impacts.</p><p>The paper also highlights some contributions of hydroinformatics to agriculture including new kinds of sensing technologies, information and simulation models development that bear the potential to boost reproducibility of agricultural systems research through systematic and formal records of the relationships among raw data, the processes that produce results and the results themselves.</p>

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