Practical 3D Reconstruction of Cultural Heritage Artefacts from Photographs – Potentials and Issues

[EN] A new technology is on the rise that allows the 3D-reconstruction of Cultural Heritage objects from image sequences taken by ordinary digital cameras. We describe the first experiments we made as early adopters in a community-funded research project whose goal is to develop it into a standard CH technology. The paper describes in detail a step-by-step procedure that can be reproduced using free tools by any CH professional. We also give a critical assessment of the workflow and describe several ideas for developing it further into an automatic procedure for 3D reconstruction from images.We gratefully acknowledge the funding from the European Commission for the FP7-IP 3D-COFORM under grant No. 231809. With this support, we are confident to provide solutions for the mentioned problems soon.Fellner, DW.; Havemann, S.; Beckmann, P.; Pan, X. (2011). Practical 3D Reconstruction of Cultural Heritage Artefacts from Photographs – Potentials and Issues. Virtual Archaeology Review. 2(4):95-103. https://doi.org/10.4995/var.2011.4564OJS9510324CROFTS N., DOERR M., GILL T., STEAD S., STIFF M.: Definition of the CIDOC Conceptual Reference Model, version 4.2 ed. CIDOC Documentation Standards Working Group, June 2005. Also ISO/PRF 21127, available from cidoc.ics.forth.gr.LONDON CHARTER INITIATIVE (HUGH DENARD): The london charter, June 2006. www.londoncharter.org.PAN, X., BECKMANN, P., HAVEMANN, S., TZOMPANAKI, K., DOERR, M., FELLNER, D.W., A distributed Object Repository for Cultural Heritage, Proc. VAST 2010 conference, Eurographics Press, 201

Open data as open educational resources

Presentation slides from the 7th Open Education Working Group Call (webinar

Identifying Overlapping and Hierarchical Thematic Structures in Networks of Scholarly Papers: A Comparison of Three Approaches

We implemented three recently proposed approaches to the identification of overlapping and hierarchical substructures in graphs and applied the corresponding algorithms to a network of 492 information-science papers coupled via their cited sources. The thematic substructures obtained and overlaps produced by the three hierarchical cluster algorithms were compared to a content-based categorisation, which we based on the interpretation of titles and keywords. We defined sets of papers dealing with three topics located on different levels of aggregation: h-index, webometrics, and bibliometrics. We identified these topics with branches in the dendrograms produced by the three cluster algorithms and compared the overlapping topics they detected with one another and with the three pre-defined paper sets. We discuss the advantages and drawbacks of applying the three approaches to paper networks in research fields.Comment: 18 pages, 9 figure

Local multiresolution order in community detection

Community detection algorithms attempt to find the best clusters of nodes in an arbitrary complex network. Multi-scale ("multiresolution") community detection extends the problem to identify the best network scale(s) for these clusters. The latter task is generally accomplished by analyzing community stability simultaneously for all clusters in the network. In the current work, we extend this general approach to define local multiresolution methods, which enable the extraction of well-defined local communities even if the global community structure is vaguely defined in an average sense. Toward this end, we propose measures analogous to variation of information and normalized mutual information that are used to quantitatively identify the best resolution(s) at the community level based on correlations between clusters in independently-solved systems. We demonstrate our method on two constructed networks as well as a real network and draw inferences about local community strength. Our approach is independent of the applied community detection algorithm save for the inherent requirement that the method be able to identify communities across different network scales, with appropriate changes to account for how different resolutions are evaluated or defined in a particular community detection method. It should, in principle, easily adapt to alternative community comparison measures.Comment: 19 pages, 11 figure

Open Data as Open Educational Resources: Case studies of emerging practice

This collection presents the stories of our contributors’ experiences and insights, in order to demonstrate the enormous potential for openly-licensed and accessible datasets (Open Data) to be used as Open Educational Resources (OER). Open Data is an umbrella term describing openly-licensed, interoperable, and reusable datasets which have been created and made available to the public by national or local governments, academic researchers, or other organisations. These datasets can be accessed, used and shared without restrictions other than attribution of the intellectual property of their creators1.While there are various definitions of OER, these are generally understood as openly-licensed digital resources that can be used in teaching and learning. On the basis of these definitions, it is reasonable to assert that while Open Data is not always OER, it certainly becomes OER when used within pedagogical contexts. Yet while the question may appear already settled at the level of definition, the potential and actual pedagogical uses of Open Data appear to have been under-discussed. As open education researchers who take a wider interest in the various open ‘movements’, we have observed that linkages between them are not always strong, in spite of shared and interconnecting values. So, Open Data tends to be discussed primarily in relation to its production, storage, licensing and accessibility, but less often in relation to its practical subsequent uses. And, in spite of widespread understanding that use of the term ‘OER’ is actually context-dependent, and, therefore, could be almost all-encompassing, the focus of OER practice and research has tended to be on educator-produced learning materials. The search for relevant research literature in the early stages of this project turned up sources which discuss the benefits of opening data, and others advocating improving student engagement with data3, but on the topic of Open Data as an educational resource specifically, there appeared to be something of a gap

World citation and collaboration networks: uncovering the role of geography in science

Modern information and communication technologies, especially the Internet, have diminished the role of spatial distances and territorial boundaries on the access and transmissibility of information. This has enabled scientists for closer collaboration and internationalization. Nevertheless, geography remains an important factor affecting the dynamics of science. Here we present a systematic analysis of citation and collaboration networks between cities and countries, by assigning papers to the geographic locations of their authors' affiliations. The citation flows as well as the collaboration strengths between cities decrease with the distance between them and follow gravity laws. In addition, the total research impact of a country grows linearly with the amount of national funding for research & development. However, the average impact reveals a peculiar threshold effect: the scientific output of a country may reach an impact larger than the world average only if the country invests more than about 100,000 USD per researcher annually.Comment: Published version. 9 pages, 5 figures + Appendix, The world citation and collaboration networks at both city and country level are available at http://becs.aalto.fi/~rajkp/datasets.htm