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1. class evaluation that classifies each statement as true, viewpoint or erroneous; and 2) 2-class evaluation that distinguishes between the true statements and all the others (i.e. viewpoint and erroneous statements were considered as one category). Interestingly, as shown in Table 2 the obtained results for the baselines are comparable for the two experiments, while for all the aggregation measures the second experiment's results were consistently higher (by up to 17%) than those of the first experiment. Therefore, we conclude that workers have quite a good ability to objectively assess the others' opinions, while their own opinions seem less reliable and consequently yield lower accuracy in classification. The accuracy of the individual worker judgment baseline is quite low for both experiments (0.7 and 0.72). Approximately 30,000 individual worker judgments were produced in each of the crowdsourcing experiments. Thus, every worker in isolation does not do any better than the "all true" baseline strategy (0.73), as could be expected. However, the workers' collective decisions (after aggregation) for each statement were much more accurate. We observe that the aggregation measure has a crucial influence on the results: a better aggregation measure can increase the accuracy by over 25% compared to the baselines. The best results were obtained by the Bayesian inference measure with alpha=0.5 and beta=0.5 for Jeffrey's prior. The AUC values are presented in Table 2 and the ROC curves are shown in Figure 3. This measure elicited 0.92 accuracy (by definition this measure could only be applied for the 2-class classification). CONCLUSION The main contribution of this research is that we show that crowdsourcing workers can quite accurately assess statements in a multi-viewpoint ontology to distinguish between true, viewpoint and erroneous statements for a given professional domain, and especially to differentiate true statements from the others. In addition, we found that a h

2. Enhancing lives through information and technology: Watson davis's project for information organisation and dissemination.

3. How I learned to love classical studies: Information representation design of the digital latin library.

4. What are we talking about when we talk about sustainability of digital archives, repositories and libraries?

5. Digital storytelling and memory institutions: A case study using activity theory.

6. Extended Date/Time Format (EDTF) in the Digital Public Library of America's Metadata: Exploratory Analysis.

7. Metadata Change in Traditional Library Collections and Digital Repositories: Exploratory Comparative Analysis.

8. Bibliometrics and information retrieval: Creating knowledge through research synergies.

9. Document representation methods for clustering bilingual documents.

10. Disambiguating descriptions: Mapping digital special collections metadata into linked open data formats.

11. Strategic Planning for A Data-Driven, Shared-Access Research Enterprise: Virginia Tech Research Data Assessment and Landscape Study.

12. Exploratory Search in Digital Libraries: A Preliminary Examination of the Use and Role of Interface Features.

13. Observing Serendipity in Digital Information Environments.

14. Educators of the Information Society: Information Literacy Instruction in Public and Academic Libraries of Canada.

15. Digital Latin Library: Information Work Practices of Classics Scholars, Graduate Students, and Teachers.