scholarly journals From Spatial Data Infrastructures to Data Spaces—A Technological Perspective on the Evolution of European SDIs

2020 ◽  
Vol 9 (3) ◽  
pp. 176 ◽  
Author(s):  
Alexander Kotsev ◽  
Marco Minghini ◽  
Robert Tomas ◽  
Vlado Cetl ◽  
Michael Lutz
Keyword(s):  
Spatial Data ◽  
The European Union ◽  
The Public ◽  
Legal Provisions ◽  
Emerging Trends ◽  
Technological Developments ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures ◽  
High Level

The availability of timely, accessible and well documented data plays a central role in the process of digital transformation in our societies and businesses. Considering this, the European Commission has established an ambitious agenda that aims to leverage on the favourable technological and political context and build a society that is empowered by data-driven innovation. Within this context, geospatial data remains critically important for many businesses and public services. The process of establishing Spatial Data Infrastructures (SDIs) in response to the legal provisions of the European Union INSPIRE Directive has a long history. While INSPIRE focuses mainly on ’unlocking’ data from the public sector, there is need to address emerging technological trends, and consider the role of other actors such as the private sector and citizen science initiatives. The objective of this paper, given those bounding conditions is twofold. Firstly, we position SDI-related developments in Europe within the broader context of the current political and technological scenery. In doing so, we pay particular attention to relevant technological developments and emerging trends that we see as enablers for the evolution of European SDIs. Secondly, we propose a high level concept of a pan-European (geo)data space with a 10-year horizon in mind. We do this by considering today’s technology while trying to adopt an evolutionary approach with developments that are incremental to contemporary SDIs.

scholarly journals Large geospatial images discovery: metadata model and technological framework

2015 ◽  
Vol 14 (2) ◽  
pp. 21-36 ◽  
Author(s):  
Lukáš Brůha
Keyword(s):  
Spatial Data ◽  
Prototype System ◽  
Raster Data ◽  
Historical Collections ◽  
Metadata Model ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures ◽  
Early Maps

The advancements in geospatial web technology triggered efforts for disclosure of valuable resources of historical collections. This paper focuses on the role of spatial data infrastructures (SDI) in such efforts. The work describes the interplay between SDI technologies and potential use cases in libraries such as cartographic heritage. The metadata model is introduced to link up the sources from these two distinct fields. To enhance the data search capabilities, the work focuses on the representation of the content-based metadata of raster images, which is the crucial prerequisite to target the search in a more effective way. The architecture of the prototype system for automatic raster data processing, storage, analysis and distribution is introduced. The architecture responds to the characteristics of input datasets, namely to the continuous flow of very large raster data and related metadata. Proposed solutions are illustrated on the case study of cartometric analysis of digitised early maps and related metadata encoding.

scholarly journals OntoFire: an ontology-based geo-portal for wildfires

2011 ◽  
Vol 11 (12) ◽  
pp. 3157-3170 ◽  
Author(s):  
K. Kalabokidis ◽  
N. Athanasis ◽  
M. Vaitis
Keyword(s):  
Spatial Data ◽  
Focal Point ◽  
End Users ◽  
Disaster Mitigation ◽  
The Internet ◽  
Prevention Strategies ◽  
Geospatial Technologies ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures

Abstract. With the proliferation of the geospatial technologies on the Internet, the role of geo-portals (i.e. gateways to Spatial Data Infrastructures) in the area of wildfires management emerges. However, keyword-based techniques often frustrate users when looking for data of interest in geo-portal environments, while little attention has been paid to shift from the conventional keyword-based to navigation-based mechanisms. The presented OntoFire system is an ontology-based geo-portal about wildfires. Through the proposed navigation mechanisms, the relationships between the data can be discovered, which would otherwise not be possible when using conventional querying techniques alone. End users can use the browsing interface to find resources of interest by using the navigation mechanisms provided. Data providers can use the publishing interface to submit new metadata, modify metadata or removing metadata in/from the catalogue. The proposed approach can improve the discovery of valuable information that is necessary to set priorities for disaster mitigation and prevention strategies. OntoFire aspires to be a focal point of integration and management of a very large amount of information, contributing in this way to the dissemination of knowledge and to the preparedness of the operational stakeholders.

scholarly journals Knowledge Discovery Web Service for Spatial Data Infrastructures

2020 ◽  
Vol 10 (1) ◽  
pp. 12
Author(s):  
Morteza Omidipoor ◽  
Ara Toomanian ◽  
Najmeh Neysani Samany ◽  
Ali Mansourian
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Web Service ◽  
Spatial Data ◽  
Spatial Clustering ◽  
Spatial Data Mining ◽  
Data Mining Techniques ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures ◽  
High Level

The size, volume, variety, and velocity of geospatial data collected by geo-sensors, people, and organizations are increasing rapidly. Spatial Data Infrastructures (SDIs) are ongoing to facilitate the sharing of stored data in a distributed and homogeneous environment. Extracting high-level information and knowledge from such datasets to support decision making undoubtedly requires a relatively sophisticated methodology to achieve the desired results. A variety of spatial data mining techniques have been developed to extract knowledge from spatial data, which work well on centralized systems. However, applying them to distributed data in SDI to extract knowledge has remained a challenge. This paper proposes a creative solution, based on distributed computing and geospatial web service technologies for knowledge extraction in an SDI environment. The proposed approach is called Knowledge Discovery Web Service (KDWS), which can be used as a layer on top of SDIs to provide spatial data users and decision makers with the possibility of extracting knowledge from massive heterogeneous spatial data in SDIs. By proposing and testing a system architecture for KDWS, this study contributes to perform spatial data mining techniques as a service-oriented framework on top of SDIs for knowledge discovery. We implemented and tested spatial clustering, classification, and association rule mining in an interoperable environment. In addition to interface implementation, a prototype web-based system was designed for extracting knowledge from real geodemographic data in the city of Tehran. The proposed solution allows a dynamic, easier, and much faster procedure to extract knowledge from spatial data.

scholarly journals GEOGRAPHIC INFORMATION E‐TRAINING INITIATIVES FOR NATIONAL SPATIAL DATA INFRASTRUCTURES / GEOGRAFINĖS INFORMACIJOS E. MOKYMO INICIATYVOS NACIONALINĖMS ERDVINIŲ DUOMENŲ INFRASTRUKTŪROMS

2008 ◽  
Vol 14 (1) ◽  
pp. 11-28 ◽  
Author(s):  
Giedrė Beconytė ◽  
Michael Govorov ◽  
Tine F. Ningal ◽  
Eimuntas Paršeliūnas ◽  
Saulius Urbanas
Keyword(s):  
Spatial Data ◽  
Spatial Information ◽  
Information Infrastructure ◽  
Developed Countries ◽  
Geographic Information ◽  
Training System ◽  
The European Union ◽  
On Line ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures

National and regional geographic datasets with derivative spatial analysis techniques are often crucial for decision‐making in sustainable development for both developing and developed countries. The needs in the spatial data and respective training are demonstrated in this article by the two very diverse examples of Papua New Guinea and the Republic of Lithuania national spatial data infrastructures. Handling and efficient use of geographic data requires rather specific skills. However, the existing curricula are inconsistent and hardly match even the basic needs of geographic information managers in state institutions and municipalities. The main objective of the proposed geographic information e‐training system is to develop and provide the modularised Spatial Information Infrastructure courses intended for on‐line based learning. This mainly will target employees of civil service and private business in Lithuania and the European Union. The proposed curriculum is a set of modular courses adding up to 1,5‐year part‐time studies in the field of Geographic Information Science and Geographic Information Infrastructure. Main advantage of on‐line‐based training is increasing accessibility in terms of both geographic location and time. Santrauka Nacionaliniai ir regioniniai duomenų duomenų rinkiniai dažnai yra labai svarbūs priimant teisingus plėtros sprendimus. Be jų neįsivaizduojama subalansuota plėtra tiek išsivysčiusiose, tiek besivystančiose šalyse. Tačiau, siekiant šiuos duomenų rinkinius efektyviai panaudoti, būtina gerai suprasti geografinės informacijos naudojimo galimybes ir išmanyti erdvinės analizės metodus. Straipsnyje analizuojami dviejų labai skirtingų šalių – Lietuvos ir Papua Naujosios Gvinėjos – nacionalinių geografinės informacijos infrastruktūrų kūrimo pavyzdžiai, atskleidžiantys erdvinių duomenų poreikį ir su jų naudojimu susijusių mokymų svarbą ir galimybes. Geografinių duomenų tvarkymas ir efektyvus naudojimas neįmaomas be gana specifinių darbuotojų įgūdžių. Deja, daugumoje šalių egzistuojančios mokymo programos, susijusios su geografinės informacijos valdymu, yra nenuoseklios ir visiškai nepritaikytos geografinės informacijos valdytojų poreikiams valstybės ir savivaldos institucijose. Dažnai studijos nesuteikia šios srities specialistams net būtinųjų žinių. Siūlomos geografinės informacijos e. mokymo sistemos pagrindas yra atskiri kursai, orientuoti į erdvinės informacijos infrastruktūros poreikius ir kartu sudarantys nuoseklią studijų sistemą. Jie pritaikyti nuotoliniam mokymuisi darbo vietose. Tai ypač aktualu Lietuvos ir Europos Sąjungos valstybės tarnautojams, tačiau naudinga ir verslo įmonėms. Šie kursai visi kartu sudaro pusantrų metų trukmės geografinės informacijos mokslo ir geografinės informacijos infrastruktūros ir studijų programą, kurią galima įgyvendinti darbo metu. Nuotolinis mokymas labai patogus tuo, kad kursai bet kuriuo metu pasiekiami iš bet kurios vietos, todėl yra prieinami daug platesniam naudotojų ratui.

Spatial data in urban planning

2020 ◽  
Vol 965 (11) ◽  
pp. 29-39
Author(s):  
A.M. Tararin ◽  
V.L. Belyaev
Keyword(s):  
Urban Planning ◽  
Spatial Data ◽  
Coordinate Systems ◽  
State Information ◽  
The Real Estate ◽  
Gis Technologies ◽  
Characteristic Points ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures ◽  
High Level

In the view of the sections of the state information system for ensuring urban planning activities, the place is shown and the role in regulating the development of territories is revealed. The composition of spatial data contained in various types and sections of urban planning documentation is analyzed. A review of world practice has shown that many of the analyzed spatial data are included in national spatial data infrastructures, which indicates their high level of signifi cance. Consideration of the issues of updating graphic documents by maintaining duty plans of urban planning information using GIS technologies revealed the need to consolidate secondary (updated) documents at the legislative level. An analysis of the requirements for spatial data in the fi eld of urban planning and the real estate cadastre showed the need for their refi nement in terms of clarifying the requirements for the accuracy of describing the objects of urban planning activities and unifying the coordinate systems used. Proposals are given for the establishment of uniform requirements for methods for determining the coordinates of spatial objects and the rules for determining the permissible discrepancy, as well as requirements for the accuracy of determining the coordinates of the characteristic points of the boundaries of objects of urban planning activities.

Realizing Data Sharing: The Role of Spatial Data Infrastructures

2014 ◽  
pp. 155-169 ◽  
Author(s):  
Glenn Vancauwenberghe ◽  
Ezra Dessers ◽  
Joep Crompvoets ◽  
Danny Vandenbroucke
Keyword(s):  
Data Sharing ◽  
Spatial Data ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures
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