Urban data cultures in post-socialist countries: challenges for evidence-based policy towards housing sustainability

This draft report summarises the initial results from the research project "Urban Data Cultures: Understanding Creation and Management of Housing-Related Information in Post-Communist Republics". This project seeks to better understand the how geographically-varied ‘data cultures’ (i.e. variegated representations, values, norms, epistemologies, practices, infrastructures, standards, power structures, etc, through which data is produced and used) inform the monitoring of progress towards the UN’s Sustainable Development Goals (SDGs), particularly as they relate to urban housing. For this pilot module, the countries of Georgia, Ukraine, Albania and Kyrgyzstan have been selected as research settings. Our main methods were: in-depth interviews with officials engaged in housing policy and management at the central, regional and local levels (n=24); notes from informal conversations, workshops and visits to state departments; and an analysis of background policy reports, journalism and academic literature related to the case study countries. On the basis of this material, we explore how management styles of housing data are observably impacted in our field settings by three key dynamics: marketization/decentralization; knowledge and expertise; and the evolution of data sharing infrastructures. We then proceed to outline a five-dimensional model of 'data cultures', comprising: 'relationships between data and decision-making'; 'relationships between the data of particular public organizations and civil society'; 'systematicity of data collection'; 'attitudes towards data sharing'; and 'specialization of data-related functions'. In conclusion, we outline some preliminary recommendations

Prayer-bots and religious worship on Twitter: a call for a wider research agenda

The automation of online social life is an urgent issue for researchers and the public alike. However, one of the most significant uses of such technologies seems to have gone largely unnoticed by the research community: religion. Focusing on Islamic Prayer Apps, which automatically post prayers from its users’ accounts, we show that even one such service is already responsible for millions of tweets daily, constituting a significant portion of Arabic-language Twitter traffic. We argue that the fact that a phenomenon of these proportions has gone unnoticed by researchers reveals an opportunity to broaden the scope of the current research agenda on online automation

Doing Gender Online : Digital Spaces for Identity Politics

Peer reviewe

Blogging the Virtual: New Geographies of Domination and Resistance In and Beyond Russia

Russia’s accelerating authoritarian turn has not ignored the internet, and in recent years, the Russian state has clamped down on internet activities that diverge from the statist line, employing a variety of strategies to dominate online spaces. Nevertheless, oppositional voices flourish on the Russian internet, taking shape in independent blogs and videos. This paper explores three political bloggers through surveillant and resistance assemblages, making sense of this contestation through an interpretation of the Deleuzian virtual that underscores the emancipatory potential of online activities for producing more egalitarian configurations, but also taking stock of the ways that these technologies have increased domination. Encompassing the blurriness between digital and corporeal spaces, the paper contributes by revealing new geographies of contestation against state strategies to dominate the Russian internet. Overlapping with but not corresponding to Russian territorial boundaries, these dynamics highlight shifting spaces of power and resistance in the increasingly illiberal world

Two theorems about similarity maps

Dress A, Lokot T, Schubert W, Serocka P. Two theorems about Similarity Maps. Annals of Combinatorics. 2008;12(3):279-290.One of the problems arising when exploring toponome or other multivariate-image data is the following: Given a family of n gray-value images of, e. g., a given sample of cell tissue, indexed by a collection of n proteins under investigation (so-called MELK data) U each single image representing the varying local concentration of one of those n proteins at the various sites (pixels) of the given sample, how should one quantify, for any two pixels (or clusters of pixels), the (dis) similarity between the corresponding "vectors" of local protein concentrations in question. Some (dis) similarity mappings defined on R-n allowing for fast OpenGL texture mapping turned out to be useful in visual inspection of toponome data. Here, we derive two rather general results regarding similarity and dissimilarity mappings and, as a corollary, the fact that the functions that were used for visual inspection of MELK data are, indeed, metrics. We believe that our results are, however, also of more general interest within the ongoing program of elucidating the structure of metrics from a more abstract point of view

Urban data cultures in post-socialist countries: challenges for evidence-based policy towards housing sustainability (Draft version)

This draft report summarises the initial results from the research project "Urban Data Cultures: Understanding Creation and Management of Housing-Related Information in Post-Communist Republics". This project seeks to better understand the how geographically-varied ‘data cultures’ (i.e. variegated representations, values, norms, epistemologies, practices, infrastructures, standards, power structures, etc, through which data is produced and used) inform the monitoring of progress towards the UN’s Sustainable Development Goals (SDGs), particularly as they relate to urban housing. For this pilot module, the countries of Georgia, Ukraine, Albania and Kyrgyzstan have been selected as research settings. Our main methods were: in-depth interviews with officials engaged in housing policy and management at the central, regional and local levels (n=24); notes from informal conversations, workshops and visits to state departments; and an analysis of background policy reports, journalism and academic literature related to the case study countries. On the basis of this material, we explore how management styles of housing data are observably impacted in our field settings by three key dynamics: marketization/decentralization; knowledge and expertise; and the evolution of data sharing infrastructures. We then proceed to outline a five-dimensional model of 'data cultures', comprising: 'relationships between data and decision-making'; 'relationships between the data of particular public organizations and civil society'; 'systematicity of data collection'; 'attitudes towards data sharing'; and 'specialization of data-related functions'. In conclusion, we outline some preliminary recommendations