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News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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Open data ecosystems: an international comparison

Transforming Government: People, Process and Policy. 2017. Vol. 11. No. 1. P. 132–156.
Styrin E. M., Luna-Reyes L., Harrison T.

Purpose. In this paper we compare the open government data ecosystems of Mexico, Russia and the United States in an effort to extract some of the major points of similarity and differentiation between these countries, and to trace how variations in these ecosystems may be related to context-specific historical problems and politics, particularly with regard to the possibility of sustained and institutionalized practice. Methodology. We take a comparative approach, using a set of concepts commonly applied to the three countries to analyze similarities and differences within this group. We gathered textual data and information, our searches for relevant documents guided by a set of concepts or criteria that are frequently employed in studies of government’s open data readiness assessment. Findings. We conclude by focusing on the very different national exigencies that have given rise to open data ecosystems in the three countries, the variations in policy vehicles and implementation schemes that have instantiated open data practices within the three ecosystems, and the common challenges that each country faces in institutionalizing open government data programs beyond the tenures of their current executives. Originality/Value. Open government data is an information policy with near global relevance and increasing application. Practitioners and scholars alike have used the concept of an “ecosystem” to guide their approach to implementing this policy and to theorizing its scope and benefits. The international comparison is original and adds to our current understanding of an ecosystem approach to open government data

Research target: Economics and Management
Priority areas: state and public administration
Language: English
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Keywords: comparative analysisinformation policyopen dataecosystemopen government data
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