Spatio-Temporal Data Quality for Civil Science Information

Dear Colleagues,

Spatial and temporal data quality is at the core of any quantitative analysis in space and time. A typical example is the quantitative analysis of movement patterns. Data quality is here defined as the precision of the data in relation to their fitness for use. We all realize that with poor quality of data, poor results will also be achieved. In the era of big data and data mining, aspects of spatial and spatiotemporal quality become an even more important issue. The standard ways of addressing the consequences of low-quality data will regularly become obsolete due to intensive calculations. Moreover, more and different aspects of data quality become important, such as confidentiality, accessibility, and trustworthiness of the data and the role of metadata. When data support expands from space to space x time, we will also see issues of cause and effect that are affected by the quality of the data. Important issues as well are related to data collection with, e.g., wireless sensor systems, crowd sourcing, and computational issues. Those in turn request location-based services. 

In this Special Issue, attention will be given to all the aspects, and more, of data quality for big spatial and spatiotemporal data in terms of their volume and variability. The Special Issue will show the trends and the latest developments in this fields. We favor a quantitative approach, where general procedures and methodologies for analysis are presented. All methods are illustrated with relevant applications and examples. Purely theoretical manuscripts will only be considered if they are novel, generic, and presented in an accessible fashion. We invite original research contributions covering a broad variety of aspects related to data management in different research fields and organizations. We encourage papers across disciplines that focus on the themes of this Special Issue. 

Topics include but are not limited to: 

Artificial intelligence in spatial data quality assessment; 

Statistical issues of spatial and spatiotemporal data quality analysis; 

Standards for spatial data quality assessment; 

Innovative concepts in spatial and spatiotemporal data quality; 

Ontological modeling in spatial and spatiotemporal data quality; 

The effect of spatial and spatiotemporal data quality in smart data fusion; 

The impact of data quality in data mining; 

Visualization of big spatial and spatiotemporal data quality; 

Data quality for big spatial and spatiotemporal data from various disciplines; 

Big data case studies with a clear and apparent spatial or spatiotemporal data quality element; 

Computational movement analysis; 

Modeling the consequences of the lack of big spatial and spatiotemporal data quality; 

Ubiquitous computing; 

Crowd sourcing, user-generated content, and VGI in big data analysis; 

The quality of geosensor network (GSN), wireless sensor network (WSN) and social location-based services (LBSN); 

Metadata for big spatial and spatiotemporal data; 

The impact of data quality in smart city management; 

Management services for big spatial and spatiotemporal data quality.

In addition, selected and extended papers, originally presented at the ISPRS workshop on spatial data quality in Nice, will be included in this Special Issue.

Prof. Dr. A. Stein
Prof. Dr. John Shi
Prof. Dr. Mahmoud Reza Delavar
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• big spatial data
• spatiotemporal data quality
• accuracy
• fitness for use
• uncertainty modeling
• uncertainty propagation
• VGI
• spatial data mining
• geo-AI