scholarly journals Enhancing discovery in spatial data infrastructures using a search engine

2018 ◽  
Vol 4 ◽  
pp. e152 ◽  
Author(s):  
Paolo Corti ◽  
Athanasios Tom Kralidis ◽  
Benjamin Lewis
Keyword(s):  
Search Engine ◽  
Language Processing ◽  
Spatial Data ◽  
Spatial Information ◽  
Harvard University ◽  
Text Search ◽  
Data Infrastructure ◽  
Data Infrastructures ◽  
Open Geospatial Consortium ◽  
Spatial Data Infrastructures

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 full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting, recommendations and many others. In this paper we present an example of a search engine being added to an SDI to improve search against large collections of geospatial datasets. The Centre for Geographic Analysis (CGA) at Harvard University re-engineered the search component of its public domain SDI (Harvard WorldMap) which is based on the GeoNode platform. A search engine was added to the SDI stack to enhance the CSW catalogue discovery abilities. It is now possible to discover spatial datasets from metadata by using the standard search operations of the catalogue and to take advantage of the new abilities of the search engine, to return relevant and reliable content to SDI users.

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 ◽  
Text Search ◽  
Advanced Search ◽  
Data Infrastructures ◽  
Spatio Temporal

A Spatial Database 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 component 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 catalogs 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 catalog, 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.

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 MAKING TEMPORAL SEARCH MORE CENTRAL IN SPATIAL DATA INFRASTRUCTURES

2017 ◽  
Vol IV-4/W2 ◽  
pp. 93-95
Author(s):  
P. Corti ◽  
B. Lewis
Keyword(s):  
Search Engine ◽  
Language Processing ◽  
Spatial Data ◽  
Spatial Information ◽  
Temporal Distribution ◽  
Data Infrastructure ◽  
Temporal Aspects ◽  
Data Infrastructures ◽  
Dimension One ◽  
Temporal Search

A temporally enabled 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 which includes the historical dimension. One of the key software components of an SDI is the catalogue service which is needed to discover, query, and manage the metadata. 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, temporal search based on enrichment, visualization of patterns in distributions of results in time and space using temporal and spatial faceting, and many others. In this paper we will focus on the temporal aspects of search which include temporal enrichment using a time miner - a software engine able to search for date components within a larger block of text, the storage of time ranges in the search engine, handling historical dates, and the use of temporal histograms in the user interface to display the temporal distribution of search results.

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

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

A Spatial Database 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 component 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 catalogs 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 catalog, 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 ◽  
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 ◽  
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 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, with features such as full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting and many others. In this paper we will be focusing on the Lucene, a powerful Javabased search library. The Centre of Geographic Analysis (CGA) at Harvard University is trying to integrate within its public domain SDI (WorldMap http://worldmap.harvard.edu), the benefits of both worlds (OGC catalogues and search engines). Harvard Hypermap (HHypermap) is a component that will be part of WorldMap, built on an open source stack. The system implements an OGC catalogue based on pycsw, to provide access to metadata in a standard way, and uses a search engine based on Solr/Lucene, to provide advanced search features typically found in search engines.

scholarly journals Geodesign as a support for proposing actions to fulfil the Sustainable Development Goals

2021 ◽  
Vol 4 ◽  
pp. 1-8
Author(s):  
Ana Clara Mourão Moura ◽  
Fabiana Carmo de Vargas Vieira ◽  
Camila Fernandes de Morais
Keyword(s):  
Sustainable Development ◽  
Transformative Learning ◽  
Spatial Data ◽  
Sustainable Development Goals ◽  
The Sustainable Development ◽  
Territorial Planning ◽  
Data Infrastructures ◽  
Development Goals ◽  
Open Geospatial Consortium ◽  
Spatial Data Infrastructures

Abstract. This paper discusses the state of the art in Geodesign, as a result from the evolution in the use of geospatial data for shared and co-creative planning. The evolution of Geographic Information Systems (GIS) led to significant advances in geovisualization, the use of cartographic data via the Internet and the construction of SDIs (Spatial Data Infrastructures). These advances fostered the emergence of Geodesign as one of the foundations for territorial planning. The text will also introduce a Brazilian Geodesign platform, GISColab, developed according to the standards set by the Open Geospatial Consortium (OGC). The platform introduces layer creation resources via WPS (Web Processing Service), as well as tools for measuring the performance of participatory planning workshops, presently focusing on the UN’s Sustainable Development Goals (SDGs). We introduce case studies in which SDGs were explored in different ways: in post-workshop analyses conducted by coordinators and participants, as well as its application as a supportive tool for decision-making during the workshop, via WPS. Finally, we also discuss the inclusion of SDGs to raise awareness of its key themes and support opinion building, resulting in transformative learning experiences.

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