spatial datasets
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Author(s):  
Menuka Warushavithana ◽  
Saptashwa Mitra ◽  
Mazdak Arabi ◽  
Jay Breidt ◽  
Sangmi Lee Pallickara ◽  
...  

2021 ◽  
Author(s):  
Asmat Ali ◽  
Muhammad Imran

Agriculture is directly linked to the socioeconomic development of every region. Agriculture impacts us all, whether we are seeking food security, better health or striving to conserve natural resources. Goal 2 of Sustainable Development Goals (SDGs) underlines the significance of agriculture as a means to achieve food security. United Nations in its recently published report titled "World Economic Situation and Prospects 2020"(UN, 2020) has declared agriculture as one of the global priorities for achieving high-quality health care and formal employment opportunities. Agriculture is a spatial subject. Policy makers demand unrestricted access to spatial data of various kinds in order to address agricultural issues and for evidence-based policy-making. Therefore, what types of spatial datasets are required for agricultural policy-making is a relevant question which is the objective of this paper. This paper also explores agriculture in Pakistan, main challenges faced by the agriculture sector of the country, and how many as well as what kind of spatial datasets are required to address these policy challenges.


2021 ◽  
Vol 2 ◽  
pp. 1-5
Author(s):  
Mehdi Zrhal ◽  
Bénédicte Bucher ◽  
Marie-Dominique Van Damme ◽  
Fayçal Hamdi

Abstract. A growing number of spatial datasets are published every year. These can usually be found in dedicated web portals with different structures and specificities. However, finding the dataset that fits user needs is a real challenge as prior knowledge of these portals is needed to retrieve it efficiently. In this article, we present the problem of spatial dataset search and how the use of a geographic Knowledge Graph could improve it. A proposed direction for future work, extending these contributions, is then presented.


2021 ◽  
Vol 5 (2) ◽  
pp. 17
Author(s):  
Vasilis Kopsachilis ◽  
Michail Vaitis

The increasing availability of linked data poses new challenges for the identification and retrieval of the most appropriate data sources that meet user needs. Recent dataset catalogs and recommenders provide advanced methods that facilitate linked data search, but none exploits the spatial characteristics of datasets. In this paper, we present GeoLOD, a web catalog of spatial datasets and classes and a recommender for spatial datasets and classes possibly relevant for link discovery processes. GeoLOD Catalog parses, maintains and generates metadata about datasets and classes provided by SPARQL endpoints that contain georeferenced point instances. It offers text and map-based search functionality and dataset descriptions in GeoVoID, a spatial dataset metadata template that extends VoID. GeoLOD Recommender pre-computes and maintains, for all identified spatial classes in the Web of Data (WoD), ranked lists of classes relevant for link discovery. In addition, the on-the-fly Recommender allows users to define an uncatalogued SPARQL endpoint, a GeoJSON or a Shapefile and get class recommendations in real time. Furthermore, generated recommendations can be automatically exported in SILK and LIMES configuration files in order to be used for a link discovery task. In the results, we provide statistics about the status and potential connectivity of spatial datasets in the WoD, we assess the applicability of the recommender, and we present the outcome of a system usability study. GeoLOD is the first catalog that targets both linked data experts and geographic information systems professionals, exploits geographical characteristics of datasets and provides an exhaustive list of WoD spatial datasets and classes along with class recommendations for link discovery.


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