<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Data from National Statistical Institutes is generally considered an important source of credible evidence for a variety of users. Summarization and dissemination via traditional methods is a convenient approach for providing this evidence. However, this is usually comprehensible only for users with a considerable level of statistical literacy. A promising alternative lies in augmenting the summarization linguistically. Less statistically literate users (e.g., domain experts and the general public), as well as disabled people can benefit from such a summarization. This article studies the potential of summaries expressed in short quantified sentences. Summaries including, for example, “<italic>most visits from remote countries are of a short duration</italic>” can be immediately understood by diverse users. Linguistic summaries are not intended to replace existing dissemination approaches, but can augment them by providing alternatives for the benefit of diverse users of official statistics. Linguistic summarization can be achieved via mathematical formalization of linguistic terms and relative quantifiers by fuzzy sets. To avoid summaries based on outliers or data with low coverage, a quality criterion is applied. The concept based on linguistic summaries is demonstrated on test interfaces, interpreting summaries from real municipal statistical data. The article identifies a number of further research opportunities, and demonstrates ways to explore those.</p></abstract>

Data from National Statistical Institutes is generally considered an important source of credible evidence for a variety of users. Summarization and dissemination via traditional methods is a convenient approach for providing this evidence. However, this is usually comprehensible only for users with a considerable level of statistical literacy. A promising alternative lies in augmenting the summarization linguistically. Less statistically literate users (e.g., domain experts and the general public), as well as disabled people can benefit from such a summarization. This article studies the potential of summaries expressed in short quantified sentences. Summaries including, for example, “most visits from remote countries are of a short duration” can be immediately understood by diverse users. Linguistic summaries are not intended to replace existing dissemination approaches, but can augment them by providing alternatives for the benefit of diverse users of official statistics. Linguistic summarization can be achieved via mathematical formalization of linguistic terms and relative quantifiers by fuzzy sets. To avoid summaries based on outliers or data with low coverage, a quality criterion is applied. The concept based on linguistic summaries is demonstrated on test interfaces, interpreting summaries from real municipal statistical data. The article identifies a number of further research opportunities, and demonstrates ways to explore those.

Augmenting Statistical Data Dissemination by Short Quantified Sentences of Natural Language

Holzinger Group HCI-KDD, Institute for Medical Informatics, Statistics and Documentation

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Data from National Statistical Institutes is generally considered an important source of credible evidence for a variety of users. Summarization and...

Augmenting Statistical Data Dissemination by Short Quantified Sentences of Natural Language

Published Online: Dec 14, 2018

Page range: 981 - 1010

Received: Jun 01, 2017

Accepted: Oct 01, 2018

DOI: https://doi.org/10.2478/jos-2018-0048

Keywords
Linguistic summaries, linguistic quantifiers, fuzzy sets, database queries, user interface

© 2018 Miroslav Hudec et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Augmenting Statistical Data Dissemination by Short Quantified Sentences of Natural Language

Published Online: Dec 14, 2018

Page range: 981 - 1010

Received: Jun 01, 2017

Accepted: Oct 01, 2018

DOI: https://doi.org/10.2478/jos-2018-0048

KeywordsLinguistic summaries, linguistic quantifiers, fuzzy sets, database queries, user interface

© 2018 Miroslav Hudec et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
Linguistic summaries, linguistic quantifiers, fuzzy sets, database queries, user interface