Word segmentation for Akkadian cuneiform

We present experiments on word segmentation for Akkadian cuneiform, an ancient writing system and a language used for about 3 millennia in the ancient Near East. To our best knowledge, this is the first study of this kind applied to either the Akkadian language or the cuneiform writing system. As a logosyllabic writing system, cuneiform structurally resembles Eastern Asian writing systems, so, we employ word segmentation algorithms originally developed for Chinese and Japanese. We describe results of rule-based algorithms, dictionary-based algorithms, statistical and machine learning approaches. Our results may indicate possible promising steps in cuneiform word segmentation that can create and improve natural language processing in this area

A GeoSPARQL Compliance Benchmark

We propose a series of tests that check for the compliance of RDF triplestores with the GeoSPARQL standard. The purpose of the benchmark is to test how many of the requirements outlined in the standard a tested system supports and to push triplestores forward in achieving a full GeoSPARQL compliance. This topic is of concern because the support of GeoSPARQL varies greatly between different triplestore implementations, and such support is of great importance for the domain of geospatial RDF data. Additionally, we present a comprehensive comparison of triplestores, providing an insight into their current GeoSPARQL support

CNN based Cuneiform Sign Detection Learned from Annotated 3D Renderings and Mapped Photographs with Illumination Augmentation

Motivated by the challenges of the Digital Ancient Near Eastern Studies (DANES) community, we develop digital tools for processing cuneiform script being a 3D script imprinted into clay tablets used for more than three millennia and at least eight major languages. It consists of thousands of characters that have changed over time and space. Photographs are the most common representations usable for machine learning, while ink drawings are prone to interpretation. Best suited 3D datasets that are becoming available. We created and used the HeiCuBeDa and MaiCuBeDa datasets, which consist of around 500 annotated tablets. For our novel OCR-like approach to mixed image data, we provide an additional mapping tool for transferring annotations between 3D renderings and photographs. Our sign localization uses a RepPoints detector to predict the locations of characters as bounding boxes. We use image data from GigaMesh's MSII (curvature, see https://gigamesh.eu) based rendering, Phong-shaded 3D models, and photographs as well as illumination augmentation. The results show that using rendered 3D images for sign detection performs better than other work on photographs. In addition, our approach gives reasonably good results for photographs only, while it is best used for mixed datasets. More importantly, the Phong renderings, and especially the MSII renderings, improve the results on photographs, which is the largest dataset on a global scale.Comment: This paper was accepted to ICCV23 and includes the DOI for an Open Access Dataset with annotated cuneiform scrip

“If it makes you happy … it can’t be that bad”: An explanatory study of students’ well-being during international exchange

This study reports on adolescents’ experiences as exchange students in an international exchange program. Based on a literature review and multivariate analysis of original on-line survey data collected from 408 students from 40 countries that had spent a year in one out of 37 destinations, it is concluded that the student’s language proficiency and perceived social support during the exchange impacted students’ wellbeing during the exchange, while cultural distance between the student’s home country and destination nor the student’s adventurousness as a personality trait had an impact. It is concluded that the students’ social support and ability to interact during the exchange play an important role in enabling exchange students to reap the benefits of international and intercultural exchange in their formative years

“If it makes you happy … it can’t be that bad”:An explanatory study of participant wellbeing during international exchange

This study reports on adolescents’ experiences as exchange students in an international exchange program. Based on a literature review and multivariate analysis of original on-line survey data collected from 408 students from 40 countries that had spent a year in one out of 37 destinations, it is concluded that the student’s language proficiency and perceived social support during the exchange impacted students’ wellbeing during the exchange, while cultural distance between the student’s home country and destination nor the student’s adventurousness as a personality trait had an impact. It is concluded that the students’ social support and ability to interact during the exchange play an important role in enabling exchange students to reap the benefits of international and intercultural exchange in their formative years.

Towards Creating A Best Practice Digital Processing Pipeline For Cuneiform Languages

Abstract of paper 1204 presented at the Digital Humanities Conference 2019 (DH2019), Utrecht , the Netherlands 9-12 July, 2019

Paleo Codage - A machine-readable way to describe cuneiform characters paleographically

Abstract of paper 0259 presented at the Digital Humanities Conference 2019 (DH2019), Utrecht , the Netherlands 9-12 July, 2019

GeoSPARQL 1.1: Motivations, Details and Applications of the Decadal Update to the Most Important Geospatial LOD Standard

In 2012, the Open Geospatial Consortium published GeoSPARQL defining “an RDF/OWL ontology for [spatial] information”, “SPARQL extension functions” for performing spatial operations on RDF data and “RIF rules” defining entailments to be drawn from graph pattern matching. In the 8+ years since its publication, GeoSPARQL has become the most important spatial Semantic Web standard, as judged by references to it in other Semantic Web standards and its wide use for Semantic Web data. An update to GeoSPARQL was proposed in 2019 to deliver a version 1.1 with a charter to: handle outstanding change requests and source new ones from the user community and to “better present” the standard, that is to better link all the standard’s parts and better document and exemplify elements. Expected updates included new geometry representations, alignments to other ontologies, handling of new spatial referencing systems, and new artifact presentation. This paper describes motivating change requests and actual resultant updates in the candidate version 1.1 of the standard alongside reference implementations and usage examples. We also describe the theory behind particular updates, initial implementations of many parts of the standard, and our expectations for GeoSPARQL 1.1’s use