Refining Statistical Data on the Web
s these issues to well known Semantic Web data integration problems. We survey existing research on current approaches to solve these problems. This Chapter is based on research published in: Merono Penuela, A. Ashkpour, A. van Erp, M. Mandemakers, K. Breure, L. Scharnhorst, A. Schlobach, S. van Harmelen, F. Semantic Technologies for Historical Research: A Survey. Semantic Web Interoperability, Usability, Applicability, 6(6) pp. 539 564. IOS Press. (2015) This paper provides a survey of the related work to Chapter 3. Ashkpour, A. Merono Penuela, A. Mandemakers, K. TheAggregatedDutch Historical Censuses: Harmonization and RDF. In: Historical Methods: A Journal of Quantitative and Interdisciplinary History, 48(4) pp. 230 245. Taylor Francis. (2015) In this paper I contributed the technical related work, the data models used, and the technical design of the solution. This paper is used in Chapter 3 to provide an analysis of data integration problems in Social History and historical census data. Merono Penuela, A. Ashkpour, A. Gueret, C. Schlobach, S. An Ecosystem for Integrating and Web Enabling Messy Spreadsheet Collections. Knowledge Based Systems, 2015 (under submission) In this paper I was the main contributor, performed the requirements analysis, wrote a substantial part of the code, and run all the experiments. This paper contributes a list of integration problems of messy spreadsheet collections to Chapter 3. 1.2 integration of messy spreadsheet collections In the second part of the thesis, the current stack of Semantic Web standards is used to address the four integration problems of messy spreadsheet collections identi ed in Chapter 3 of Part i: arbitrary data layout location, implicit dimensions, incomparable measurements and data errors. We use messy spreadsheet collections from the prototypical domain of Social History as a use case to develop Semantic Web based solutions to these integration problems. Interestingly, these integration problems are independent from the domain and also occur in messy spreadsheet collections of other elds. Consequently, these solutions are also applied to messy spreadsheet collections in other use cases with the same integration problems, in order to assess their applicability to di erent domains. The following questions are considered: 1.2 integration of messy spreadsheet collections 23 RQ3. What set of Semantic Web standard vocabularies and methods are useful to solve data integration problems of messy spreadsheet collections in multiple domains? What is the cost of applying them? Can the distinction between primary and secondary sources be preserved? RQ4. What integration issues do Semantic Web technologies solve in prototypical Social History datasets? Which of these problems are solved by the same technologies in datasets from other domains? Which ones remain unsolved? Chapter 4 addresses RQ3. In this chapter we describe an ecosystem, built on top of current standard Semantic Web technology, designed to integrate messy spreadsheet collections and solve the integration issues of Chapter 3 in a semiautomatic way. It describes the assumptions on the input messy spreadsheets, the technologies and vocabularies selected, and an algorithm for representing these messy spreadsheets as Linked Data. To evaluate the e ectiveness and genericity of this method, three di erent messy spreadsheet collections are integrated: the Wages, prices and welfare dataset; messy spreadsheets from the UK open government data initiative; and the historical Dutch aggregated censuses (1795 1971) This chapter is based on research published in: Merono Penuela, A. Gueret, C. Ashkpour, A. Schlobach, S. An Ecosystem for Integrating and Web Enabling Messy Spreadsheet Collections. Knowledge Based Systems, 2015 (under submission) This paper's role in Chapter 4 is to describe a work ow and software pipeline for integrating messy spreadsheet collections on the Web. Merono Penuela, A. LSD Dimensions: Use and Reuse of Linked Statistical Data. In: Proceedings of the 19th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2014, LNCS 8982, pp. 159 163, Springer. Linkoping, Sweden, 2014. In this paper I was the only contributor, created the idea, and designed and implemented the system. This paper is used in Chapter 4 to describe an index of statistical properties on the Web, and use such index for data integration purposes. Chapter 5 addresses RQ4. To analyse what integration issues are solved by the ecosystem proposed in Chapter 4, we investigate in detail the integrated dataset that results from running this ecosystem on the dataset of the historical Dutch aggregated censuses (1795 1971) a prototypical Social History dataset. To do so, we introduce the nature of census data and their historical context, and previous