scholarly journals One Archaeology: A Manifesto for the Systematic and Effective Use of Mapped Data from Archaeological Fieldwork and Research

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 222 ◽  
Author(s):  
Peter McKeague ◽  
Anthony Corns ◽  
Åsa Larsson ◽  
Anne Moreau ◽  
Axel Posluschny ◽  
...  
Keyword(s):  
Spatial Data ◽  
Spatial Information ◽  
Economic Value ◽  
Research Data ◽  
Primary Data ◽  
Full Potential ◽  
Data Infrastructure ◽  
Efficient Data ◽  
Environmental Focus ◽  
Public Organisations

The Infrastructure for Spatial Information in Europe (INSPIRE) Directive (2007) requires public organisations across Europe to share environmentally-related spatial datasets to support decision making and management of the environment. Despite the environmental focus of INSPIRE, it offers limited guidance for archaeological datasets. Most primary data is created outside, but ultimately curated within, the public sector. As spatial evidence from fieldwork activities is not considered by the Directive, it overlooks a range of barriers to sharing data, such as project-based fieldwork, a lack of data standards, and formatting and licencing variations. This paper submits that these challenges are best addressed through the formalised management of primary research data through an archaeological Spatial Data Infrastructure (SDI). SDIs deliver more efficient data management and release economic value by saving time and money. Better stewardship of archaeological data will also lead to more informed research and stewardship of the historic environment. ARIADNE already provides a digital infrastructure for research data, but the landscape and spatial component has been largely overlooked. However, rather than developing a separate solution, the full potential of spatial data from archaeological research can and should be realised through ARIADNE.

Factors influencing integrated information management: Spatial data infrastructure in Pakistan

2021 ◽  
pp. 026666692110484
Author(s):  
Asmat Ali ◽  
Muhammad Imran ◽  
Munazza Jabeen ◽  
Zahir Ali ◽  
Syed Amer Mahmood
Keyword(s):  
Information Management ◽  
Spatial Data ◽  
Structural Equation ◽  
Explanatory Power ◽  
Primary Data ◽  
Equation Modeling ◽  
Geospatial Information ◽  
Data Infrastructure ◽  
Significance Level ◽  
Retrieval Processes

Spatial data is one of the core components in all information retrieval processes for decision-making. Spatial data acquisition consumes enormous monetary resources and time. The Integrated Geospatial Information Framework (IGIF) provides a basis and guide for developing, integrating, strengthening, and maximizing geospatial information management and related resources in all countries. To this, governments all over the world are establishing national spatial data infrastructures (SDIs). However, such initiatives face a considerable amount of resistance as organizations often do not want to share their data assets. The present study investigates these barriers in the establishment of national SDI in Pakistan. The constraints studied through the IGIF pathways and past studies were adapted via a pilot study and conceptualized in a hypothesized model. We collected primary data via the administration of 520 questionnaire surveys to 280 public and private organizations. Partial least squares structural equation modeling (PLS-SEM) was applied to statistically confirm the conceptual model of the barriers to disseminating spatial data. The results indicate institutional barriers from the absence of national data policy, lack of specified roles of stakeholders, poor inter-organizational coordination, missing data-sharing policy, and weak organizational partnerships, with coefficients 0.26, 1.555, 1.305, 8.288, and 0.136, respectively, at the p < 0.001 significance level. The PLS-SEM R2 0.65 indicates a good explanatory power of the model. The methodology developed in the present study will allow devising more sustainable policies for spatial data management and dissemination in Pakistan and beyond.

scholarly journals Implementing an open source spatio-temporal search platform for Spatial Data Infrastructures

2016 ◽  
Author(s):  
Paolo Corti ◽  
Benjamin G Lewis ◽  
Athanasios Tom Kralidis ◽  
Ntabathia Jude Mwenda
Keyword(s):  
Open Source ◽  
Search Engine ◽  
Language Processing ◽  
Spatial Data ◽  
Spatial Information ◽  
National Endowment ◽  
Data Infrastructure ◽  
Advanced Search ◽  
Data Infrastructures ◽  
Spatio Temporal

A Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide an efficient and flexible way to use spatial information. One of the key software components of an SDI is the catalogue service which is needed to discover, query, and manage the metadata. Catalogue services in an SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard which defines common interfaces for accessing the metadata information. A search engine is a software system capable of supporting fast and reliable search, which may use “any means necessary” to get users to the resources they need quickly and efficiently. These techniques may include features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting, recommendations, feedback mechanisms based on log mining, usage statistic gathering, and many others. In this paper we will be focusing on improving geospatial search with a search engine platform that uses Lucene, a Java-based search library, at its core. In work funded by the National Endowment for the Humanities, the Centre for Geographic Analysis (CGA) at Harvard University is in the process of re-engineering the search component of its public domain SDI (WorldMap http://worldmap.harvard.edu ) which is based on the GeoNode platform. In the process the CGA has developed Harvard Hypermap (HHypermap), a map services registry and search platform independent from WorldMap. The goal of HHypermap is to provide a framework for building and maintaining a comprehensive registry of web map services, and because such a registry is expected to be large, the system supports the development of clients with modern search capabilities such as spatial and temporal faceting and instant previews via an open API. Behind the scenes HHypermap scalably harvests OGC and Esri service metadata from distributed servers, organizes that information, and pushes it to a search engine. The system monitors services for reliability and uses that to improve search. End users will be able to search the SDI metadata using standard interfaces provided by the internal CSW catalogue, and will benefit from the enhanced search possibilities provided by an advanced search engine. HHypermap is built on an open source software source stack.

scholarly journals Implementing an open source spatio-temporal search platform for Spatial Data Infrastructures

2016 ◽  
Author(s):  
Paolo Corti ◽  
Benjamin G Lewis ◽  
Tom Kralidis ◽  
Jude Mwenda
Keyword(s):  
Open Source ◽  
Search Engine ◽  
Language Processing ◽  
Spatial Data ◽  
Search Engines ◽  
Spatial Information ◽  
Data Infrastructure ◽  
Advanced Search ◽  
Data Infrastructures ◽  
Spatio Temporal

A Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide the most efficient and flexible way to use spatial information. One of the key software components of a SDI is the catalogue service, needed to discover, query and manage the metadata. Catalogue services in a SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard, that defines common interfaces to access the metadata information. A search engine is a software system able to perform very fast and reliable search, with features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting and many others. The Centre of Geographic Analysis (CGA) at Harvard University is trying to integrate within its public domain SDI (named WorldMap), the benefits of both worlds (OGC catalogues and search engines). Harvard Hypermap (HHypermap) is a component that will be part of WorldMap, totally built on an open source stack, implementing an OGC catalogue, based on pycsw, to provide access to metadata in a standard way, and a search engine, based on Solr/Lucene, to provide the advanced search features typically found in search engines.

scholarly journals Implementing an open source spatio-temporal search platform for Spatial Data Infrastructures

2016 ◽  
Author(s):  
Paolo Corti ◽  
Benjamin G Lewis ◽  
Tom Kralidis ◽  
Jude Mwenda
Keyword(s):  
Open Source ◽  
Search Engine ◽  
Language Processing ◽  
Spatial Data ◽  
Search Engines ◽  
Spatial Information ◽  
Data Infrastructure ◽  
Advanced Search ◽  
Data Infrastructures ◽  
Spatio Temporal

A Spatial Data Infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide the most efficient and flexible way to use spatial information. One of the key software components of a SDI is the catalogue service, needed to discover, query and manage the metadata. Catalogue services in a SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard, that defines common interfaces to access the metadata information. A search engine is a software system able to perform very fast and reliable search, with features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting and many others. The Centre of Geographic Analysis (CGA) at Harvard University is trying to integrate within its public domain SDI (named WorldMap), the benefits of both worlds (OGC catalogues and search engines). Harvard Hypermap (HHypermap) is a component that will be part of WorldMap, totally built on an open source stack, implementing an OGC catalogue, based on pycsw, to provide access to metadata in a standard way, and a search engine, based on Solr/Lucene, to provide the advanced search features typically found in search engines.

Developing the Niger Delta Transport System Using Adequate Geo-Spatial Information

2007 ◽  
Vol 18-19 ◽  
pp. 365-373 ◽  
Author(s):  
J.O. Ehiorobo ◽  
Henry A.P. Audu
Keyword(s):  
Spatial Data ◽  
Niger Delta ◽  
Spatial Information ◽  
Transportation System ◽  
Delta Region ◽  
Data Infrastructure ◽  
Goods And Services ◽  
Niger Delta Region ◽  
Water Transportation ◽  
Good Schools

The Niger Delta Region, although the back bone of Nigerian economy, has been neglected by successive governments over time. There are no good schools, no health facilities, no water and other facilities within this area. The problem of the area is compounded by lack of good transportation system. This has been a hindrance both for security agencies and the people in the restive area. A good transportation system should ensure that people, goods and services move speedily, conveniently, safely and cost effectively. To have an efficient ground and water transportation system needed in this area requires adequate and accurate Geo-spatial information. In this paper, the benefits of adequate transportation system in the Niger Delta Region are highlighted. The roles of Geo-spatial data and Geo-spatial information system in the planning, development and management of an efficient transportation system are discussed. The paper also examines Geospatial Data infrastructure (GDI) in the development of the Niger Delta transportation sector Master plan, with data generated for Edo and Delta States presenting case study scenarios.

Use of Geo-Information in Environmental Policy

2014 ◽  
Vol 5 (1) ◽  
pp. 38-58
Author(s):  
Wies Vullings ◽  
Jandirk Bulens ◽  
Dennis Walvoort
Keyword(s):  
Environmental Policy ◽  
Conceptual Framework ◽  
Spatial Data ◽  
Policy Making ◽  
Daily Practice ◽  
Spatial Thinking ◽  
Full Potential ◽  
Policy Makers ◽  
Data Infrastructure

To date, use of the full potential of geo-information is not often applied in the daily practice of policy makers. The main questions explored by this research are: Why is geo-information not widely used in policy and how can this be improved? A conceptual framework was developed to evaluate the use of geo-information. For five cases, the use of geo-information was evaluated by means of this framework. The results of the evaluation, as well as the usefulness of the framework, are discussed. Recommendations on spatial thinking and practice, availability and quality of a spatial data infrastructure and implementation of new geo-applications in policy-making are also made.

Geospatial Semantic Query Engine for Urban Spatial Data Infrastructure

2019 ◽  
Vol 15 (4) ◽  
pp. 31-51
Author(s):  
Sunitha Abburu
Keyword(s):  
Spatial Data ◽  
Spatial Information ◽  
Semantic Relations ◽  
Semantic Relationship ◽  
Data Infrastructure ◽  
Semantic Query ◽  
Semantic Relationships ◽  
Query Engine ◽  
Spatial Method ◽  
User Friendly

The research aims at design and develop a special semantic query engine “CityGML Spatial Semantic Web Client (CSSWC)” that facilitates ontology-based multicriteria queries on CityGML data in OGC standard. Presently, there is no spatial method, spatial information infrastructure or any tool to establish the spatial semantic relationship between the 3D city objects in CityGML model. The present work establishes the spatial and semantic relationships between the 3DCityObjects and facilitates ontology-driven spatial semantic query engine on 3D city objects, class with multiple attributes, spatial semantic relations like crosses, nearby, etc., with all other city objects. This is a novel and original work practically implemented generic product for any 3D CityGML model on the globe. A user-friendly form-based interface is designed to compose effective ontology based GeoSPARQL query. CSSWC enhances CityGML applications performance through effective and efficient querying system.

Integration of GIS with Remote Sensing and GPS for Disaster Mitigation

2015 ◽  
Vol 10 (2) ◽  
pp. 225-230
Author(s):  
Sikander Nawaz Khan ◽  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Spatial Information ◽  
Service Providers ◽  
Disaster Mitigation ◽  
Sensor Nodes ◽  
Physical Contact ◽  
Current Status ◽  
Target Area ◽  
Full Potential

Natural disasters like flood, earthquake, cyclone, volcanic eruption and others are causing immense losses to the property and lives every year. Current status and actual loss information on natural hazards can be determined and also prediction for next probable disasters can be made using different remote sensing and mapping technologies. Global Positioning System (GPS) calculates the exact position of damage. It can also communicate with wireless sensor nodes embedded in potentially dangerous places. GPS provides precise and accurate locations and other related information like speed, track, direction and distance of target objects to emergency responders.Remote Sensing facilitates to map damages without having physical contact with target area. Now with the addition of more remote sensing satellites and other advancements, early warning system is used very efficiently. Remote sensing is being used both at local and global scale. High Resolution Satellite Imagery (HRSI), airborne remote sensing and space-borne remote sensing is playing a vital role in disaster management.Early in Geographic Information System (GIS) was used to collect, arrange, and map the spatial information, but now it has the capability to analyze spatial data. This analytical ability of GIS is the main cause of its adoption by different emergency service providers like the police and ambulance service.The full potential of these so called 3S technologies cannot be used alone. Integration of GPS and other remote sensing techniques with GIS has pointed new horizons in modeling of earth science activities. Many remote sensing cases, including Asian Ocean Tsunami in 2004, Mount Mangart landslides and Pakistan-India earthquake in 2005 are described in this paper.

scholarly journals Διαμόρφωση βασικών παραμέτρων σχεδιασμού και υλοποίησης της Ελληνικής Εθνικής Υποδομής Γεωχωρικών Πληροφοριών

2015 ◽  
Author(s):  
Παναγιώτης Τζιαχρής
Keyword(s):  
European Community ◽  
Spatial Data ◽  
Spatial Information ◽  
Spatial Data Infrastructure ◽  
Data Infrastructure

Αντικείμενο της παρούσας διδακτορικής διατριβής είναι η μελέτη της Υποδομής Γεωχωρικών Πληροφοριών (ΥΓΕΠ, Spatial Data Infrastructure - SDI) ειδικά για την περίπτωση της Ελλάδας και η πρόταση διαμόρφωσης βασικών παραμέτρων σχεδιασμού και υλοποίησης της, με την δόμηση και αξιοποίηση ενός "Μοντέλου Σύνθεσης Τάσεων". Επιπλέον, καταγράφει την υφιστάμενη προσέγγιση από την εδαφολογική επιστημονική κοινότητα, των Ελληνικών αγροτικών εδαφολογικών δεδομένων και την συγκρίνει με τις απαιτήσεις του νόμου 3882/2010 για την Ελληνική Εθνική ΥΓΕΠ (ΕΥΓΕΠ) και της Ευρωπαϊκής ΥΓΕΠ (Infrastructure for Spatial Information in the European Community, INSPIRE). Τέλος αξιοποιώντας τα θεωρητικά συμπεράσματα της παρούσας διατριβής, παραθέτει δυο διαφορετικές προσεγγίσεις (τεχνοκεντρική, κοινωνικοτεχνική) ενσωμάτωσης και αξιοποίησης των Ελληνικών εδαφολογικών δεδομένων σε μια μελλοντική Ελληνική ΕΥΓΕΠ, προκρίνοντας ωστόσο την κοινωνικοτεχνική ως πιο πιθανά βιώσιμη και επιτυχημένη, καθώς και πιο συμβατή τόσο με την σύγχρονη θεωρία όσο και με τα αποτελέσματα της παρούσας διατριβής.

scholarly journals HARMONISATION MODEL OF ADMINISTRATIVE UNITS OF THE REPUBLIC OF SRPSKA ACCORDING TO INSPIRE DIRECTIVE

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Ivana Janković ◽  
Mladen Amović
Keyword(s):  
Public Sector ◽  
European Commission ◽  
Spatial Data ◽  
Spatial Information ◽  
Structure Development ◽  
Joint Research ◽  
Data Infrastructure ◽  
The Republic ◽  
Administrative Units ◽  
Republika Srpska

The INSPIRE Directive establishes a framework for the creation of a spatial data infrastructure(SDI), which will enable the exchange of spatial information between public sector organizationsand better access to spatial information in general across the Europe. This paper describes theharmonization of the INSPIRE theme Administrative Units. Data harmonization was carried outwithin the framework of the IMPULS project implemented by the Republic Geodetic and PropertyAdministration of Republika Srpska with the support of the Swedish Agency for Cadastre andCartography. Implementation involves the development of a GML scheme with mapping of existingdata in accordance with that structure, development and testing of INSPIRE services, andpreparation of metadata for data and services. The model was verified by the Joint Research Centerin Ispra, established by the European Commission (Joint Research Center).

Sign in / Sign up

Export Citation Format

Share Document