Spatial Data Interoperability Research Articles

Enabling Spatial Data Interoperability through the Use of a Semantic Meta-Model—The Peatland Example from the JRC SEPLA Project

Numerous geographic data on peatland exist but definitions vary, and the correspondent classes are often neither harmonized nor interoperable. This hinders the efforts to employ the available national datasets on peatlands and wetlands for policy monitoring and reporting. The existing meta-languages, such as ISO-Land Cover Meta Language (LCML) and EAGLE, offer the possibility to “deconstruct” the relevant nomenclatures in an object-oriented manner, allowing the comparability and interoperable use of related information. The complex nature of peatlands calls for a dedicated and structured vocabulary of keywords and terms, comprising the biotic substrate and the soil. In the SEPLA project, a semantic meta-model has been developed, combining the hierarchical ontology of the LCML with the matrix structure of the EAGLE model. The necessary elements were provided to describe peatland bio-physical characteristics, while representing the definitions in a concise and user-friendly manner (semantic passports). The proposed semantic meta-model is innovative as it enables the documentation of the spatial distribution of peatland characteristics, considering also their temporal dimension, their intrinsic relation with land use, and the soil. It has been successfully implemented for the translation of the national peatland nomenclature into common land categories relevant for reporting under LULUCF regulation, as part of the EU Climate Law.

STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysisand visualization.

Recent technological developments in spatial transcriptomics allow researchers to measure gene expression of cells and their spatial locations at the single-cell level, generating detailed biological insight into biological processes. A comprehensive database could facilitate the sharing of spatial transcriptomic data and streamline the data acquisition process for researchers. Here, we present the Spatial TranscriptOmics DataBase (STOmicsDB), a database that serves as a one-stop hub for spatial transcriptomics. STOmicsDB integrates 218 manually curated datasets representing 17 species. We annotated cell types, identified spatial regions and genes, and performed cell-cell interaction analysis for these datasets. STOmicsDB features a user-friendly interface for the rapid visualization of millions of cells. To further facilitate the reusability and interoperability of spatial transcriptomic data, we developed standards for spatial transcriptomic data archiving and constructed a spatial transcriptomic data archiving system. Additionally, we offer a distinctive capability of customizing dedicated sub-databases in STOmicsDB for researchers, assisting them in visualizing their spatial transcriptomic analyses. We believe that STOmicsDB could contribute to research insights in the spatial transcriptomics field, including data archiving, sharing, visualizationand analysis. STOmicsDB is freely accessible at https://db.cngb.org/stomics/.

Possible contributions of spatial semantic methods and technologies to multi-representation spatial database paradigm

Today, the amount and variety of spatial data have increased dramatically. In addition, the web has made it easier to disseminate and share this kind of data. Therefore, spatial data integration and interoperability have gained more importance. Spatial data are collected from different sources and often heterogeneous in terms of the levels of detail and the points of view. To able to meet the demands of different spatial applications, multi-source and heterogeneous spatial datasets need to be integrated as well as the consistency of these datasets needs to be maintained. In this context, multirepresentation spatial database (MRSDB) paradigm has been suggested by researchers. However, the heterogeneity constitutes a significant barrier in this respect and hence the implementations have so far been remained within a rather narrow scope. In this article, it is mainly discussed about the possible contributions of basic methods and technologies of spatial semantics such as ontologies, semantic web and linked data to the data integration for creating a MRSBD. Some examples are also given to illustrate the concept.

Spatial decision support systems (SDSS) and software applications for earthquake disaster management with special reference to Turkey

Earthquake disasters pose significant risks and remain a serious threat for millions of people causing a devastating loss of lives and damage to the infrastructure resulting in huge socio-economic and environmental losses in many regions worldwide. In the last decade, recent major and catastrophic earthquake occurrences have underscored the critical importance of the increasing need for effective disaster management in considering appropriate planning, responses and strategies, with time and complex decision-making, being vital across the four phases of the disaster and emergency management (DEM) life cycle-preparedness, mitigation, response and recovery. In this paper, selected spatial decision support systems (SDSSs) related to the geographic information system-based applications in earthquake DEM, ranging from scenario or simulation based, early warning and rapid response and loss estimation systems, have been analysed. These have been generalised into global systems to include HAZTURK, QLARM, SELENA, DBELA, CATS, PAGER and regional and local systems comprising of ELER, HAZUS-MH, KOERILoss, MAEviz, EQRM and LNECLOSS. From the analysis of SDSS usage worldwide, but especially in Turkey, HAZTURK has been recommended for implementation of earthquake risk and loss estimation studies in Turkey based on its significant comparative advantages over other SDSSs and the suitability and applicability to the local conditions of Turkey, which have been discussed in this research. Key challenges to be addressed, ranging from issues in spatial data acquisition, quality, interoperability, data exchange and lack of coordination among associated institutions involved in earthquake DEM and recommendations, as well as future functional improvements and developments of HAZTURK software, have been characterised for successful implementation in Turkey.

Przyszłość systemów rejestracji nieruchomości wobec rozwoju inteligentnych technologii. Wybrane problemy prawne na tle wniosków z konferencji „Common Vision Conference 2016. Migration to a Smart World”, Amsterdam, 5–7 czerwca 2016 roku

The development of information technologies offers new possibilities of use of information collected in public registers, such as land registers and cadastres, which play a significant role in establishing the infrastructure for spatial information. Efficient use of spatial information systems with the purpose of a sustainable land management shall be based on en suring the interconnection of different information resources, data exchange, as well as a broad access to data. The role of land registration systems in the context of technological advancement was the subject of the Common Vision Conference 2016. Migration to a Smart World, held on 5–7 June 2016 in Amsterdam. The conference was organized by Europe’s five leading mapping, cadastre and land registry associations, cooperating within a “Common Vision” agreement: EuroGeographics, Permanent Committee on Cadastre, European Land Registries Association, European Land Information Service and Council of European Geodetic Surveyors. The discussion during the conference focused on topics regarding the idea of smart cities, marine cadastre, interoperability of spatial data, as well as the impact of land registers and cadastres on creating the infrastructure for spatial information and developing e-government, at both national and European levels. The paper aims to present an overview of issues covered by the conference and also to highlight some important problems arising from implementing advanced technology solutions in the field of land registration.

Geodata interoperability and harmonization in transport: a case study of open transport net

BackgroundIn Europe, a lot of data portals are emerging on the local, national or interregional levels. These portals have a common objective to share data and information to its citizens and businesses, and to make information more accessible. However, studies showed that people are still facing difficulties in finding and reusing public sector information. To facilitate data reuse, the information should be available in a machine-readable format and agreed metadata standard, so that interoperability and discoverability could be enhanced.MethodsThis article focuses on the interoperability and harmonization of spatial and non-spatial data in the transport field. Both the open data and geospatial world have stable standards (such as DCAT and INSPIRE), and the GeoDCAT-AP is the first attempt in combining the two worlds. Through a case study approach, this article aims to provide insights in the implementation of this new standard and other interoperability cases in transport, such as the Data Tank data management system and a harmonized model for road network data.ResultsThe results are presented through a case study approach that was executed in the Open Transport Net project, and in consultation of the standard bodies Open Geospatial Consortium, the World Wide Web Consortium, and the in-house research centre of the European Commission, the Joint Research Centre.ConclusionsThe results highlight that still a lot of work needs to be done to combine both worlds, and that certain advantages and drawbacks need to be taken into account when combining spatial and non-spatial data.

Legal Principles for Assessing Illegality in Horizontal Agreement Cases

Three-dimensional GIS, which provides spatial information through expression techniques of virtual reality close to the real world and the web, is one of the fields that attract a new attention. In particular, Open GIS Consortium(OGC) announced a topological relationship specification of spatial object which supports interoperability while interest in interoperability of spatial data is increasing. However, this specification is limited to two-dimensional spatial object. So this research established a topological relationship of three-dimensional spatial object in order to improve urban landscape and provide a foundation to use GIS. Based on this, this study proposes ways to visualize landscape information which is appropriate for new town's circumstances. It can be concluded that this research has a bigger meaning since it established a base of sharing information about realistic urban landscape that can be accessed regardless of place and time.

The development of a GIS-based public GMO location register considering the needs of the EU Member States

The Directive 2001/18/EC regulates the deliberate release of genetically modified organisms (GMOs) into the environment. EU Member States are obligated by this Directive to establish location register to inform the public where GMOs are released into the environment. As a partner within the EU-project PRICE, the German Federal Office of Consumer Protection and Food Safety (BVL) developed a modern, GIS-based location register (GLOREG) for GMOs adaptable to the different needs of the EU member states. Using a questionnaire the BVL asked the Competent Authorities (CAs) under the Directive 2001/18/EC and CAs of non-EU countries in Europe about detailed background information of their current location registers. Most of EU-Member States already implemented the Directive into national law, even if they do not perform any deliberate release or cultivation of GMOs in their country. The CAs distinguish between deliberate release (mostly ‘experiments’) and cultivation of GMOs within their national regulations and notification rules. National regulations also vary regarding the organization of cadastral data in the agrarian landscape. GLOREG considers these differences with adaptable software and modular components. Furthermore, spatial information of GMOs are covered by Directive 2007/2/EC (INSPIRE) and must therefore comply with its requirements for the interoperability of spatial data.

Using ontological inference and hierarchical matchmaking to overcome semantic heterogeneity in remote sensing-based biodiversity monitoring

Ontology-based applications hold promise in improving spatial data interoperability. In this work we use remote sensing-based biodiversity information and apply semantic formalisation and ontological inference to show improvements in data interoperability/comparability. The proposed methodology includes an observation-based, “bottom-up” engineering approach for remote sensing applications and gives a practical example of semantic mediation of geospatial products. We apply the methodology to three different nomenclatures used for remote sensing-based classification of two heathland nature conservation areas in Belgium and Germany. We analysed sensor nomenclatures with respect to their semantic formalisation and their bio-geographical differences. The results indicate that a hierarchical and transparent nomenclature is far more important for transferability than the sensor or study area. The inclusion of additional information, not necessarily belonging to a vegetation class description, is a key factor for the future success of using semantics for interoperability in remote sensing.

Unique grid cell identification of Croatian official map grids

The Unique Grid Cell Identification (UGCI) system was created using the Croatian cartographic map grid system as a basis for development. A short description of the Croatian map grid system is therefore provided. Cartographic map nomenclature is used to uniquely identify map sheets; e.g. grid cells. Nonetheless, because such nomenclature uses alpha-numeric and special characters and complex coding/decoding systems, it is not well suited for use with GIS, databases, internet services and other Information and Communications Technologies applications. UGCI has been developed to uniquely identify all spatial grid cells, no matter their scale. It should enable easy connections with spatial grid cell identifier systems of other Spatial Data Infrastructure communities, such as ecology, geology, meteorology, etc. Easier identification and use of spatial grid cells contributes to the interoperability of maps and other spatial data. Map is cowering Croatian grid area in the scale 1:1 800,000. It is representing grids scales from 1:250,000 to 1:5000.

InSpace3D: A Middleware for Built Environment Data Access and Analytics

Standardisation, archiving, and digital access of spatial data pertaining to built-up environments is an area acquiring increasing attention amongst several interest groups: policy makers, designers and planners, civil engineers, infrastructure management and public service personnel, building users. Initiatives such as the Building Information Model (BIM), Industry Founda- tion Classes (IFC), and CityGML are creating the information-theoretic backbone that guides the crucial aspects of quality, exchange, and interoperability of spatial data at the environmental and urban scale. However, due to the inherent scale, com- plexity, and detailed geometric character of building information data, extracting useful semantic and qualitative knowledge for accomplishing high-level analytical tasks is still an extremely complex and error prone process involving data intensive computing. We propose a uniform spatial data access middleware that can provide a combination of high-level, multi-modal, semantic, and quantitative-qualitative spatial data access and analytical capability. We present the core computational capabil- ities for the proposed middleware and present an overview of the high-level spatial model and its compliance with the industry standard IFC. A key theoretical contribution is a framework for investigating the computational complexity of deriving spatial artefacts within the context of building informatics. Additionally, we empirically investigate the feasibility and practicality of the derivation of spatial artefacts by conducting experiments on seven industry-scale IFC models. The experiment results show that, despite having non-linear polynomial increase with respect to time, deriving spatial artefacts is practical with large designs.

A COMPARATIVE STUDY OF SPATIAL DATA HARVEST STANDARDS

Abstract. So far, thousand kinds of Spatial Data were acquired, produced, published and used for specialized applications. Heterogeneity is obviously one key problem for spatial data in the process of its creating, structuring or managing. The heterogeneity keeps the complete and variety of spatial data, but induces the difficulty of describing, publishing, sharing, interoperability or metadata harvesting. Decentralized, multi-organization and synchronization are the major features of the next generation spatial data service infrastructure. Standard research on geospatial metadata harvesting and data service is becoming a research focus. More and more organizations and consortiums (e.g. ISO/TC 211, OGC) drafted and released their geospatial metadata and service standards. However, these standards are diverse in order to fit to different spatial data format and research fields, which makes spatial data owner hard to choose standard. The paper focuses on analyzing metadata harvesting from multi-organizations archives, including Spatial Data description, publishing, sharing, and interoperability. Several of most widely used Spatial Data standards are introduced, and compared. Advices on how to choose the standards are given for Spatial Data owner.

Sharing Integrated Spatial and Thematic Data: The CRISOLA Case for Malta and the European Project Plan4all Process

Sharing data across diverse thematic disciplines is only the next step in a series of hard-fought efforts to ensure barrier-free data availability. The Plan4all project is one such effort, focusing on the interoperability and harmonisation of spatial planning data as based on the INSPIRE protocols. The aims are to support holistic planning and the development of a European network of public and private actors as well as Spatial Data Infrastructure (SDI). The Plan4all and INSPIRE standards enable planners to publish and share spatial planning data. The Malta case tackled the wider scenario for sharing of data, through the investigation of the availability, transformation and dissemination of data using geoportals. The study is brought to the fore with an analysis of the approaches taken to ensure that data in the physical and social domains are harmonised in an internationally-established process. Through an analysis of the criminological theme, the Plan4all process is integrated with the social and land use themes as identified in the CRISOLA model. The process serves as a basis for the need to view sharing as one part of the datacycle rather than an end in itself: without a solid protocol the foundations have been laid for the implementation of the datasets in the social and crime domains.

A parallel computing approach to fast geostatistical areal interpolation

Areal interpolation is the procedure of using known attribute values at a set of (source) areal units to predict unknown attribute values at another set of (target) units. Geostatistical areal interpolation employs spatial prediction algorithms, that is, variants of Kriging, which explicitly incorporate spatial autocorrelation and scale differences between source and target units in the interpolation endeavor. When all the available source measurements are used for interpolation, that is, when a global search neighborhood is adopted, geostatistical areal interpolation is extremely computationally intensive. Interpolation in this case requires huge memory space and massive computing power, even with the dramatic improvement introduced by the spectral algorithms developed by Kyriakidis et al. (2005. Improving spatial data interoperability using geostatistical support-to-support interpolation. In: Proceedings of geoComputation. Ann Arbor, MI: University of Michigan) and Liu et al. (2006. Calculation of average covariance using fast Fourier transform (FFT). Menlo Park, CA: Stanford Center for Reservoir Forecasting, Petroleum Engineering Department, Stanford University) based on the fast Fourier transform (FFT). In this study, a parallel FFT-based geostatistical areal interpolation algorithm was developed to tackle the computational challenge of such problems. The algorithm includes three parallel processes: (1) the computation of source-to-source and source-to-target covariance matrices by means of FFT; (2) the QR factorization of the source-to-source covariance matrix; and (3) the computation of source-to-target weights via Kriging, and the subsequent computation of predicted attribute values for the target supports. Experiments with real-world datasets (i.e., predicting population densities of watersheds from population densities of counties in the Eastern Time Zone and in the continental United States) showed that the parallel algorithm drastically reduced the computing time to a practical length that is feasible for actual spatial analysis applications, and achieved fairly high speed-ups and efficiencies. Experiments also showed the algorithm scaled reasonably well as the number of processors increased and as the problem size increased.

Development of an interoperable tool to facilitate spatial data integration in the context of SDI

The integration of multisource heterogeneous spatial data is one of the major challenges for many spatial data users. To facilitate multisource spatial data integration, many initiatives including federated databases, feature manipulation engines (FMEs), ontology-driven data integration and spatial mediators have been proposed. The major aim of these initiatives is to harmonize data sets and establish interoperability between different data sources. On the contrary, spatial data integration and interoperability is not a pure technical exercise, and there are other nontechnical issues including institutional, policy, legal and social issues involved. Spatial Data Infrastructure (SDI) framework aims to better address the technical and nontechnical issues and facilitate data integration. The SDIs aim to provide a holistic platform for users to interact with spatial data through technical and nontechnical tools. This article aims to discuss the complexity of the challenges associated with data integration and propose a tool that facilitates data harmonization through the assessment of multisource spatial data sets against many measures. The measures represent harmonization criteria and are defined based on the requirement of the respective jurisdiction. Information on technical and nontechnical characteristics of spatial data sets is extracted to form metadata and actual data. Then the tool evaluates the characteristics against measures and identifies the items of inconsistency. The tool also proposes available manipulation tools or guidelines to overcome inconsistencies among data sets. The tool can assist practitioners and organizations to avoid the time-consuming and costly process of validating data sets for effective data integration.

Modeling Cadastral Spatial Features Based on Geography Markup Language in GIS: A Case Study in Shanghai

Significant progresses have been made in the establishment of cadastre databases in developing countries and the use of cadastre as a base to the development of land information systems based on Geographic Information System (GIS). How to interoperate and share these homogenous data is still a big problem in the applications of cadastral databases. This paper presents a GML (Geography Markup Language) approach to model cadastral spatial features for data interoperability and sharing. The advantages of GML in data interoperability are that (1) it provides an open and standard way to share and interoperate spatial data, and (2) it enables on-line and variety of spatial data interoperability on the Web. The cadastral spatial feature models are first defined based on geography markup language. An application schema is then defined, in which the cadastral features are described as CityModel, StreetModel, BlockModel, LandModel and BuildingModel, and the relationships between them are defined as CityMember, StreetMember, BlockMember and Landmember. The creation of a GML document is discussed in details. Furthermore, a GML-based cadastral WebGIS system is developed based on Java, Document Object Model (DOM) and Simple Application Interface for XML (SAX), and the implementation of the system is illustrated through a case study, which shows the feasibility of the proposed spatial feature models and data interoperability based on GML.

Developing geographic information systems platforms for multijurisdictional transportation analyses: framework and techniques for spatial data sharing

Geographic information systems (GISs) have been presented as a powerful analysing tool for civil engineers to help their decision-making processes. Building GIS platforms for transportation analysis involving multiple jurisdictions has been challenging, however, because of the complexity and difficulty associated with conducting data sharing and ensuring spatial data interoperability among GISs for transportation (GIS-T) data sets. In the context of western Canadian urban and rural areas, this paper investigates the issues related to GIS-T data sharing, establishes a conceptual framework, develops techniques supporting the framework by solving recurring data-sharing problems, and constructs a number of GIS-T platforms facilitating comprehensive multijurisdictional transportation analyses. In addition, based on the knowledge gained through solving real-world problems, the authors propose an open GIS-T platform consisting of a series of customized base maps, each being tailored to suit the needs of individual application and, as a whole, linked together by interoperability to better support transportation applications.Key words: transportation engineering analysis, GIS, GIS-T, spatial data, interoperability, integration, data sharing.

A study on the cadastral management information system based on technology of spatial database

Traditional geographical information system uses file system to manage spatial data, which only suits to personal GIS (or named expert GIS), but cannot meet the requirement of enterprise GIS. The technology of spatial database, which uses Relational Database Management System (RDBMS) to manage spatial data, is an advanced technology driven by the socializationof GIS application. Integrating spatial data and other data into relational database, it is possible to give its rights of management spatial data to RDBMS, this can achieveseamless integration and take advantages of RDBMS, include data sharing, bulky amount of spatial data management, data consistent maintenance, data safety, high query efficiency, and more others. Therefore, studies on spatial database (also named Spatial Data Engine) to manage spatial data have become a research focus in GIS fields. In this paper, the author brought forward and analyzed the spatial data object which has four properties: common attributes, temporal, geometry, and behavior. Among these properties the geometry is the essential property of spatial data object distinguishedcommon data object which is the componentof the database. The mapping of spatial dataobject's properties to relational database are columns (or fields), methods and valid rules respectively. Alsothe author analyzed the realization of the application of spatial database technology in Cadastral Administration System from the points of spatial data interoperability, large quantity of spatial data management, the efficiency of queryin large area, and the control of the data safety and others based on the development of specific application system, it figuredout the frame of Land Information System using spatial database technology.

Techniques for Building Multijurisdictional Geographic Information System Platforms for Transportation Analysis

Transportation analysis involving multiple jurisdictions requires data sharing and spatial data interoperability among geographic information system (GIS) data sets. Data sharing and spatial data interoperability issues related to multijurisdictional transportation analysis are discussed. Specific techniques based on practical data-sharing, problem-solving experience are developed. To further enhance the data-sharing process, a conceptual framework is established to guide technique implementations. Regional GIS transportation (GIS-T) platforms integrated from various data sources by applying the framework and the associated techniques are also presented. To better support different transportation applications, an open GIS-T platform is proposed, consisting of a series of customized base maps, each tailored to suit individual applications and, as a whole, linked together by inherently established interoperability.