# Uncertainty in Automated Ontology Matching: Lessons from an Empirical Evaluation
## 5 Case Study: Spatio-Temporal Alignment of Indicators
### Experiment Description  
The case study proposed in this paper has been inspired by the famous portal _Our World in Data_[46], which publishes and discusses heterogeneous indicators. In the portal, different datasets are published as independent csv files. For the most part, the terminology in the different files is supposed to be uniform. The experiment assumes as an input the raw data as originally provided by the respective sources. It aims to achieve automatic integration. Details are reported in Table 1. As shown, each experiment involves a pair of input datasets. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Experiment ID** & **Input Dataset 1** & **Input Dataset 2** \\ \hline Exp. 1 & Countries of the World [47] & Country Profile Variables [48] \\ \hline Exp. 2 & Food Security Indicators (V\_2.6) [49] & Prevalence of Undernourishment [50] \\ \hline Exp. 3 & Food Security Indicators (I\_2.3) [51] & Prevalence of Undernourishment [50] \\ \hline Exp. 4 & Food Security Indicators (I\_2.4) [51] & Prevalence of Undernourishment [50] \\ \hline Exp. 5 & Macroeconomic Data (GDP) [52] & GDP (current USD) [53] \\ \hline Exp. 6 & WDI Country [54] & WUP2018 Largest Cities [55] \\ \hline Exp. 7 & Total Life Expectancy—Historical [56] & Life Expectancy at Birth [57] \\ \hline Exp. 8 & Historical Gas Emissions [58] & List of Electoral Democracies [59] \\ \hline Exp. 9 & List of Electoral Democracies [59] & Sexual Violence in Childhood [60] \\ \hline Exp. 10 & Historical Gas Emissions [58] & Sexual Violence in Childhood [60] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Experiment overview. The considered pairs can involve datasets belonging to the same domain as well as datasets from different domains. Regardless of the meaning of the data, the original tables report the values of given indicators for different countries in different years. The actual structure may vary from case to case, but in most cases, it proposes typical patterns used to organize spatio-temporal data. For tables describing a particular indicator, rows represent the names of countries and columns represent years (or intervals of years) or vice versa. In some other cases, tables report the values of more than one indicator for different countries in a single year (or in a single interval of years): rows represent the names of countries, and columns represent indicators. More rarely, tables report the values of multiple indicators for different countries in different years: rows represent ID numbers (enumerated numbers/indexes), and columns contain a year or interval column, a country column, and indicator columns. Overall, the test bed proposed cannot be considered critical, neither in terms of size nor complexity. It is, rather, characterized by a small scale and relatively low complexity. Input datasets are characterized by a number of columns that vary from 2 to 63 and rows in a range [46; 47; 48; 49; 50]. The experiment adopts available tools for alignment, as described later on in the paper. After converting and matching the input dataset pairs, we will get the output alignments. First, we will evaluate the quality of the output alignments. Then, we will trim and/or disambiguate these alignments and evaluate them again. We aim to see how the alignment _trimming_ and _disambiguation_ processes can affect the quality and uncertainty of the output alignments. For alignment _trimming_, we will use the Alignment API ([[https://moex.gitlabpages.inria.fr/alignapi/](https://moex.gitlabpages.inria.fr/alignapi/)]([https://moex.gitlabpages.inria.fr/alignapi/](https://moex.gitlabpages.inria.fr/alignapi/)) (accessed on 20 October 2020)) [61; 62]. That is a Java programming interface that facilitates the manipulation and evaluation of ontology alignments in RDF format. Given an alignment and a threshold value as an input, the Alignment API automatically trims the input alignment using the predefined method cut() and returns a new trimmed alignment.