Artefacts and Errors: Acknowledging Issues of Representation in the Digital: Imaging of Ancient Texts

It is assumed, in palaeography, papyrology and epigraphy, that a certain amount of uncertainty is inherent in the reading of damaged and abraded texts. Yet we have not really grappled with the fact that, nowadays, as many scholars tend to deal with digital images of texts, rather than handling the texts themselves, the procedures for creating digital images of texts can insert further uncertainty into the representation of the text created. Technical distortions can lead to the unintentional introduction of ‘artefacts’ into images, which can have an effect on the resulting representation. If we cannot trust our digital surrogates of texts, can we trust the readings from them? How do scholars acknowledge the quality of digitised images of texts? Furthermore, this leads us to the type of discussions of representation that have been present in Classical texts since Plato: digitisation can be considered as an alternative form of representation, bringing to the modern debate of the use of digital technology in Classics the familiar theories of mimesis (imitation) and ekphrasis (description): the conversion of visual evidence into explicit descriptions of that information, stored in computer files in distinct linguistic terms, with all the difficulties of conversion understood in the ekphratic process. The community has not yet considered what becoming dependent on digital texts means for the field, both in practical and theoretical terms. Issues of quality, copying, representation, and substance should be part of our dialogue when we consult digital surrogates of documentary material, yet we are just constructing understandings of what it means to rely on virtual representations of artefacts. It is necessary to relate our understandings of uncertainty in palaeography and epigraphy to our understanding of the mechanics of visualization employed by digital imaging techniques, if we are to fully understand the impact that these will have

What constrains Africa's exports?

This paper examines the effects of transit, documentation, and ports and customs delays on Africa’s exports. The authors find that transit delays have the most economically and statically significant effect on exports. A one-day reduction in inland travel times leads to a 7 percent increase in exports. Put another way, a one-day reduction in inland travel times translates to a 1.5 percentage point decrease in all importing-country tariffs. By contrast, longer delays in the other areas have a far smaller impact on trade. The analysis controls for the possibility that greater trade leads to shorter delays in three ways. First, it examines the effect of trade times on exports of new products. Second, it evaluates the effect of delays in a transit country on the exports of landlocked countries. Third, it examines whether delays affect time-sensitive goods relatively more. The authors show that large transit delays are relatively more harmful because of high within-country variation

Reconstructing Native Language Typology from Foreign Language Usage

Linguists and psychologists have long been studying cross-linguistic transfer, the influence of native language properties on linguistic performance in a foreign language. In this work we provide empirical evidence for this process in the form of a strong correlation between language similarities derived from structural features in English as Second Language (ESL) texts and equivalent similarities obtained from the typological features of the native languages. We leverage this finding to recover native language typological similarity structure directly from ESL text, and perform prediction of typological features in an unsupervised fashion with respect to the target languages. Our method achieves 72.2% accuracy on the typology prediction task, a result that is highly competitive with equivalent methods that rely on typological resources.Comment: CoNLL 201

Recording, Documentation, and Information Management for the Conservation of Heritage Places: Guiding Principles

Provides guidance on integrating recording, documentation, and information management of territories, sites, groups of buildings, or monuments into the conservation process; evaluating proposals; consulting specialists; and controlling implementation

Science Models as Value-Added Services for Scholarly Information Systems

The paper introduces scholarly Information Retrieval (IR) as a further dimension that should be considered in the science modeling debate. The IR use case is seen as a validation model of the adequacy of science models in representing and predicting structure and dynamics in science. Particular conceptualizations of scholarly activity and structures in science are used as value-added search services to improve retrieval quality: a co-word model depicting the cognitive structure of a field (used for query expansion), the Bradford law of information concentration, and a model of co-authorship networks (both used for re-ranking search results). An evaluation of the retrieval quality when science model driven services are used turned out that the models proposed actually provide beneficial effects to retrieval quality. From an IR perspective, the models studied are therefore verified as expressive conceptualizations of central phenomena in science. Thus, it could be shown that the IR perspective can significantly contribute to a better understanding of scholarly structures and activities.Comment: 26 pages, to appear in Scientometric

Sharing Social Research Data in Ireland: A Practical Tool

Your data is valuable and has an importance outside your own original project. Allowing other researchers to reuse your data maximises the impact of your work, and benefits both the scholarly community and society in general. Sharing your data allows other researchers to use your material in ways you may not have thought of, or may not have been able to do within your research project. It allows other researchers to replicate your findings, to verify your results, test your instruments and compare with other studies. It also allows them to use your work to expand knowledge in important areas. It provides value for money by reducing duplication and advancing knowledge and also has a significant value in education, as it allows both graduate and under-graduate students to develop their skills in qualitative and quantitative research by using high-quality data in their studies, without having to conduct their own surveys.Archiving your data also guarantees its long-term preservation and accessibility. As many research teams are assembled only for individual projects, long-term preservation and access to research data collections can only be guaranteed if they are deposited in an archive which will manage them, ensure access and provide user-support. In addition, the archives will ensure that the datasets do not become obsolescent or corrupted.Finally, increasingly funders require that you make your research data available as a condition of their funding your research, so that other researchers can test your findings, and use your data to extend research in your area. Equally, publishers are also specifying access to research data as a condition for publication