![]() Automatic document metadata extraction using support vector machines. Available online: (accessed on 1 June 2021). Beyond Metadata: Towards Uzser-Centric Description of Data Quality. In Proceedings of the 10th AGILE International Conference on Geographic Information Science, Aalborg, Denmark, 8– pp. User-Focused Metadata for Spatial Data, Geographical Information and Data Quality Assessments. The funders had no role in the design of the study in the collection, analyses, or interpretation of data in the writing of the manuscript or in the decision to publish the results. However, the approach was able to engage participants from different continents. We note that the authors are Asia- and Pacific-based researchers. As such, even if the bias exists, it does not mean that the results are invalid. However, to the best of our knowledge, there is no study that suggests a correlation exists between being a social media user and having a prejudice toward spatial data portals. If most of them are, then the sampling was biased toward a specific group of spatial data users who use social media. As such, the study lacks insight into how many of the participants are social media users. However, our questions to the participants did not include the channel of recruitment. We note that the sampling strategy included both social media users and non-social media users. We also used our social media channels and asked our associates to use their channels to recruit participants. We considered the starting sample when contacting our associates to participate in the study and assist us with recruiting more participants. The authors acknowledge that controlling the sampling frame in the snowball method is challenging and considered a weakness. Following this research’s human ethics requirements, we did not ask for the identities of the portals to avoid potential exposure to the study participants. To ensure participant validity with this open distribution method, several questions were designed to obtain their backgrounds and experiences and detect whether or not they were suitable for this survey. Selected social media accounts belonging to spatial communities and organizations were also tagged. The authors circulated the questionnaire via LinkedIn and Twitter. These people were asked to pass the questionnaire to their own associates who shared similar qualifications. ![]() The authors circulated the questionnaire internationally via email to their known associates. Spatial data users known to the authors were contacted and asked to be participants. Purposive sampling was implemented for the sample selection by conducting snowball sampling worldwide. Building on the outcomes of, a questionnaire was developed to engage an international audience and gauge their opinions about the spatial data portals they utilize. ![]()
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