scholarly journals Reducing Consumer Uncertainty: Towards an Ontology for Geospatial User-Centric Metadata

2020 ◽  
Vol 9 (8) ◽  
pp. 488
Author(s):  
Hasti Ziaimatin ◽  
Alireza Nili ◽  
Alistair Barros
Keyword(s):  
Spatial Data ◽  
Open Data ◽  
Source Selection ◽  
Consumer Uncertainty ◽  
Selection Decisions ◽  
Metadata Standards ◽  
Geospatial Metadata ◽  
User Groups ◽  
Data Source ◽  
User Centric

With the increased use of geospatial datasets across heterogeneous user groups and domains, assessing fitness-for-use is emerging as an essential task. Users are presented with an increasing choice of data from various portals, repositories, and clearinghouses. Consequently, comparing the quality and evaluating fitness-for-use of different datasets presents major challenges for spatial data users. While standardization efforts have significantly improved metadata interoperability, the increasing choice of metadata standards and their focus on data production rather than potential data use and application, renders typical metadata documents insufficient for effectively communicating fitness-for-use. Thus, research has focused on the challenge of communicating fitness-for-use of geospatial data, proposing a more “user-centric” approach to geospatial metadata. We present the Geospatial User-Centric Metadata ontology (GUCM) for communicating fitness-for-use of spatial datasets to users in the spatial and other domains, to enable them to make informed data source selection decisions. GUCM enables metadata description for various components of a dataset in the context of different application domains. It captures producer-supplied and user-described metadata in structured format using concepts from domain-independent ontologies. This facilitates interoperability between spatial and nonspatial metadata on open data platforms and provides the means for searching/discovering spatial data based on user-specified quality and fitness-for-use criteria.

scholarly journals A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration

Epidemiologia ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 315-324
Author(s):  
Juan M. Banda ◽  
Ramya Tekumalla ◽  
Guanyu Wang ◽  
Jingyuan Yu ◽  
Tuo Liu ◽  
...  
Keyword(s):  
Large Scale ◽  
Social Dynamics ◽  
Additional Data ◽  
Open Data ◽  
Data Sources ◽  
Research Projects ◽  
Research Groups ◽  
The World ◽  
Data Source

As the COVID-19 pandemic continues to spread worldwide, an unprecedented amount of open data is being generated for medical, genetics, and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic is allowing other scientists to learn from local experiences and data generated on the front lines of the COVID-19 pandemic. However, there is a need to integrate additional data sources that map and measure the role of social dynamics of such a unique worldwide event in biomedical, biological, and epidemiological analyses. For this purpose, we present a large-scale curated dataset of over 1.12 billion tweets, growing daily, related to COVID-19 chatter generated from 1 January 2020 to 27 June 2021 at the time of writing. This data source provides a freely available additional data source for researchers worldwide to conduct a wide and diverse number of research projects, such as epidemiological analyses, emotional and mental responses to social distancing measures, the identification of sources of misinformation, stratified measurement of sentiment towards the pandemic in near real time, among many others.

The role of data source selection in chemical hazard assessment: A case study on organic photovoltaics

2019 ◽  
Vol 365 ◽  
pp. 227-236 ◽  
Author(s):  
Haoyang He ◽  
Yadira Gutierrez ◽  
Thomas M. Young ◽  
Julie M. Schoenung
Keyword(s):  
Hazard Assessment ◽  
Organic Photovoltaics ◽  
Source Selection ◽  
Chemical Hazard ◽  
Data Source

scholarly journals USING PARTICIPATORY APPROACH TO IMPROVE AVAILABILITY OF SPATIAL DATA FOR LOCAL GOVERNMENT

2016 ◽  
Vol III-4/W1 ◽  
pp. 139-144
Author(s):  
T. Kliment ◽  
V. Cetl ◽  
H. Tomič ◽  
J. Lisiak ◽  
M. Kliment
Keyword(s):  
Spatial Data ◽  
Local Governments ◽  
Local Level ◽  
Property Tax ◽  
Open Data ◽  
Quality Level ◽  
Tax Rates ◽  
Geospatial Information ◽  
Data Infrastructure ◽  
Participatory Gis

Nowadays, the availability of authoritative geospatial features of various data themes is becoming wider on global, regional and national levels. The reason is existence of legislative frameworks for public sector information and related spatial data infrastructure implementations, emergence of support for initiatives as open data, big data ensuring that online geospatial information are made available to digital single market, entrepreneurs and public bodies on both national and local level. However, the availability of authoritative reference spatial data linking the geographic representation of the properties and their owners are still missing in an appropriate quantity and quality level, even though this data represent fundamental input for local governments regarding the register of buildings used for property tax calculations, identification of illegal buildings, etc. We propose a methodology to improve this situation by applying the principles of participatory GIS and VGI used to collect observations, update authoritative datasets and verify the newly developed datasets of areas of buildings used to calculate property tax rates issued to their owners. The case study was performed within the district of the City of Požega in eastern Croatia in the summer 2015 and resulted in a total number of 16072 updated and newly identified objects made available online for quality verification by citizens using open source geospatial technologies.

scholarly journals Geographic Information System Produksi Energi dan Pertambangan Kabupaten Musi Banyuasin

2018 ◽  
Vol 3 (3) ◽  
pp. 360-369 ◽  
Author(s):  
Usman Ependi
Keyword(s):  
Decision Making ◽  
Information System ◽  
Geographic Information System ◽  
Spatial Data ◽  
Open Data ◽  
Geographic Information ◽  
Extreme Programming ◽  
Programming Approach ◽  
User Needs ◽  
Government Control

Energy and mining reporting have to conduct for the exploration company in order to make control while exploration. Government control can perform by making profiling of energy and mining data that exist in the area as consideration in taking policy or decision. Stages of energy and mining reporting are very important to do especially in areas that have energy and mining resources such as Musi Banyuasin regency. Profiling can performed by mapping the location of energy and mining results using a geographic information system (GIS) to organize data between explorers and governments. Based on these conditions GIS was developed using a technique that prioritizes user needs with extreme programming development techniques. The result of GIS development shows that the processing of data becomes information based on spatial and non-spatial data with the final result of energy and mining report. The report presented can be used as a report to the relevant parties as an effort to open data of energy and mining as material in decision-making or policy. Geographic information system generated systematically developed using extreme programming approach with five stages of exploration, planning, iteration, production and maintenance so that it can run funtionaly according to its function

A novel computational knowledge-base framework for visualization and quantification of geospatial metadata in spatial data infrastructures

2018 ◽  
Vol 22 (2) ◽  
pp. 269-305
Author(s):  
Gangothri Rajaram ◽  
Harish Chandra Karnatak ◽  
Swaminathan Venkatraman ◽  
K. R. Manjula ◽  
Kannan Krithivasan
Keyword(s):  
Knowledge Base ◽  
Spatial Data ◽  
Geospatial Metadata ◽  
Data Infrastructures ◽  
Spatial Data Infrastructures
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