Development of an Algorithm to Evaluate the Quality of Geolocated Addresses in Urban Areas

Round 1

Reviewer 1 Report

The paper presents the development and testing of an algorithm to evaluate the quality of geolocated addresses in urban areas. The proposed algorithm is tested with both Volunteered Geographic Information (VGI) and authoritative datasets from repositories in European countries. The study compares the algorithm's performance with that of commercial geocoding web services like Google, Microsoft, and Here, as well as the crowdsourced geocoding service OSM-Nominatim. The algorithm allows for both direct and reverse geocoding methods to assess the spatial quality in a reference address dataset. The paper also examines the spatial quality of address datasets and the usability of geocoders. User-configurable input parameters are included to adjust the address quality analysis based on data size and other factors. My concerns are as follows:

 

    1. Grammar and Language Issues: The paper contains numerous grammar and language issues, which need to be addressed to ensure clarity and coherence of the content.

    2. Missing Related Work Section: The absence of a related work section is a major drawback as it overlooks previous research on address matching algorithms and quality evaluation techniques, making it difficult to assess the novelty and relevance of the study.

    3. Lack of Explicit Mention of Contribution: There is a lack of an explicit mention of the contribution of this study in the introduction section. The authors should clearly articulate the novel aspects and specific contributions of their work, highlighting what sets their algorithm apart from existing approaches in the field of address quality evaluation

 

Extensive editing of English language is required

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

This paper presents an algorithm for evaluating the quality of semantic and geographic information in geospatial address datasets. The methodology compares open data platforms, SDI, and VGI with commercial datasets, providing insights into their usability for geocoding in specific urban areas.

1.       The authors state in the Introduction section that the purpose of this paper is to automatically evaluate the quality of voluntary or commercial geographic information on postal addresses to determine if it is sufficient for checking or updating authoritative address datasets. However, the significance of this evaluation is not adequately explained. Figure 1 provides a compelling reason for conducting this evaluation: it demonstrates that many countries lack a government-maintained address database and rely solely on commercial or crowd-sourced address data. Emphasizing this point earlier in the Introduction would strengthen the paper's argument and highlight the need for assessing the quality of non-authoritative address datasets to address this data gap.

2.       I am not sure if the proposed methodology aligns with the purpose of the paper. If voluntary or commercial addresses are utilized for the purpose of verifying or updating authoritative address datasets, it seems contradictory to assess their quality by comparing them to the very same authoritative address datasets.

3.       The primary focus of this paper is the development of quality control algorithms for addresses. However, the presentation of the algorithm itself lacks clarity. For instance, on page 7 lines 272 to 277, the introduction of the ETL process lacks details regarding the reference dataset, the comparison methodology, and the input and output of the process. This issue arises consistently whenever there are multiple datasets involved in other parts of the paper.

4.       Figure 3 could indeed be beneficial for illustrating the algorithm; however, it would be more effective if presented earlier in the paper. Placing an algorithm overview between the "Methods" section and the specific development of the quality control algorithm (Section 3.1) and including Figure 3 there would provide readers with an overview of the algorithm before delving into the details. Regarding Figure 3, there is some confusion in the diagram. Specifically, the two "N" arrows originating from "Exists?" are unclear in terms of their subsequent direction and purpose. It is not apparent whether we need to regenerate the tile and download area or why it is necessary.

5.       The proposed algorithm predominantly relies on open-source packages without introducing any innovative methods. In order to showcase its contribution, the algorithm should be made open source and publicly accessible.

 

 

The language of this paper should be refined. There are numerous fragmented and incomplete sentences that need to be addressed.

 

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

Unfortunately, due to lack of attention to the scientific English language writing, terminological consistencly, correctness of citation, the presentation of this research is suffering. Another study on quality of volunteered spatial data (this time on addresses) could be interesting, but the paper needs to be considerably revised to present the scientific method, its application and results clearly.

The quality of English language needs to be improved considerably.

Author Response

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Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The authors have solved all of my concerns.

It has been drastically improved by the authors

Reviewer 2 Report

My questions are addressed.