Synthetic knowledge and the internet of things

In principle, there is broad consensus that knowledge should be the basis of environmental sustainability policies. Knowledge about the environment is often generated by corporations, in addition to governments, as part of their industrial activities (Mukerji 1989)

LA ELECCIÓN DIRECTA DE AUTORIDADES UNIPERSONALES EN LAS UNIVERSIDADES NACIONALES ARGENTINAS: ¿MODIFICA LA PARTICIPACIÓN PROPORCIONAL DE CADA CLAUSTRO?

Este trabajo es parte de un proyecto que tuvo como objetivo analizar, en primer lugar, la forma en que se adoptó la elección directa como modalidad de elección de autoridades unipersonales en aquellas universidades nacionales que modificaron sus estatutos en este sentido. En segundo lugar, se investigó si existen indicios respecto de que esas universidades hayan experimentado cambios en la gobernabilidad institucional que sean atribuibles a la elección directa de autoridades. Por último se verificó si al pasar de la elección indirecta a la directa se modificó el peso relativo que tiene cada claustro en la elección del rector. Se relevó cual es el sistema de elección vigente en cada una de las 38 universidades nacionales, comparando para aquellas que han optado por la elección directa si la manera en que participa cada claustro es equivalente. Se compararon las ponderaciones entre claustros y que relación se da entre la participación de cada claustro en la Asamblea Universitaria y la ponderación en la elección directa. Las principales conclusiones a las que hemos arribado, entre las ocho universidades nacionales que adoptaron la modalidad de elección directa de autoridades unipersonales, es que solo en algunas se verifica que la ponderación por claustro, en el voto directo, es equivalente a la participación porcentual de cada claustro en la Asamblea Universitaria. En dos casos, la ponderación es equivalente a la participación de cada claustro en el Consejo Superior, pero no a la asamblea universitaria

Data Infrastructures in the Public Sector: A Critical Research Agenda Rooted in Scandinavian IS Research

Extant Information Systems research emphasizes the strategic benefits of digitalization and value co-creation for business. Less is known, however, about the dynamics of how value is co-created in the digitalization of the public sector, where data infrastructures are increasingly adopted. We identify three core empirical challenges for value co-creation in the public sphere, corresponding to the following conceptual tenets: participation in infrastructuring processes, data curation, and data protection. We propose to draw on the Participatory Design tradition that permeates the Information Systems field in Scandinavia to critically harness the political meaning of value co-creation. Drawing on a two-year project on the design of data infrastructures in three areas of the public domain (environmental monitoring, healthcare, and smart cities), we contribute to Information Systems by proposing a research agenda consisting of three future directions for critical studies of value co-creation in data infrastructures in the public sector

On the statistical contribution of cloud fraction cover to the summer sea-ice extent of 15 Arctic sub-regions, 1982-2015

Sea ice is one of the most important components of the polar climate system. The decline of the Arctic sea-ice extent (SIE), particularly during the melting season (Aug.-Oct.), is widely observed. Important roles in the melting process are played by the changes in thermodynamics and radiation forcing, in particular in relation to surface temperature and cloud cover, and also by the ocean and atmospheric circulation. Even if several studies already analysed the behaviour of SIE in the Arctic using standard linear and non-linear regression methods, this work aims to investigate the correlation between cloud fraction cover (CFC) and summer SIE in 15 Arctic sub-regions. CFC, together with surface temperature and u- and v- wind components, are also used as predictor variables in multiple regression equations for a statistical forecast of SIE for each one of the 15 sub-regions. The data used are: i) monthly SIE, obtained from the sea ice concentration (SIC) dataset over the Arctic as provided by the National Snow and Ice Data Center (NSIDC) and computed using the Nasa Team (NT) algorithm; ii) monthly CFC (for all, high, middle and low clouds) available from the CLARA-A2 dataset produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF), the data being on a 25km x 25km regular grid; iii) monthly air temperatures and u- and v- wind components at sigma 0.995 collected from NCEP/NCAR R1. All data are given on a global regular lat-lon grid with resolution 2.5x2.5 and refer to the period 1982-2015; they were also seasonally and spatially averaged over each sub-region. As expected, the contribution of cloud fraction cover to the SIE variability is lower of that due to thermodynamic forcing through the ‘surface’ temperature and the ‘surface’ wind. However, for some sub-regions (e. g. Greenland Sea, Beaufort Sea) the cloud cover contribution to SIE became relevant. For most sub-regions, the largest contribution seems to come from the middle clouds (440hPa - 680 hPa)

The Case of Norway and Digital Transformation over the Years

Norway is generally characterized by a pervasive presence of digital services. It is currently undergoing a digital transformation across different domains, from daily life to public and private enterprises. In this introductory chapter, we first unpack the main drivers of digital transformation in Norway so far and its enabling conditions based on three illustrative examples: the development of Altinn, a digital platform supporting digital communication between citizens and public and private organizations; the evolution of BankID, Norway’s electronic identification system; and the current push for open data sharing leveraging experiences in the energy industry. We identify key common enabling conditions: a trust-based cooperation across social partners and across public and private sectors, the public sector’s driving role, cross-organization consolidations and consortia, and application-oriented initiatives. In the second part of the chapter, we summarize the content of the subsequent chapters in this book shedding light on different facets of digital transformation in Norway.publishedVersio

Data Curation as Governance Practice

Data governance is concerned with leveraging the potential value of data in data infrastructures. In IS research, data governance has developed as a management perspective, implying a narrow view of who makes decisions about the data in infrastructures. In contrast, we propose a data governance in practice view and focus on the day-to-day decisions of users working with the data. Drawing on an interpretive case study of three data infrastructures in the Norwegian public sector, we ask: How can we characterize data governance in practice? We find that the work of data curation is a fundamental element of data governance practice. Data emerge dynamically as assets, enfolding the involved users’ interests and contexts. We contribute to the IS literature in two ways. First, we characterize three main practices of data curation: achieving data quality, filtering the relevant data, and ensuring data protection. In so doing we foreground the role of the users as contributing to shaping data infrastructures. Second, we develop an analytical framework which specifies the unfolding of user involvement in data infrastructures-in-use and conceptualizes this work as emergent. Our contributions have implications for developing training support for users as data curators, and for the ethics of data managemen

Seasonal co-variability of surface downwelling longwave radiation for the 1982-2009 period in the Arctic

The decreasing of the sea ice cover observed in the Arctic represent a strong indicator of the ongoing climate change. Several physical processes are contributing to this one. The study of the co-variability of sea ice concentration (SIC) with other physical parameters may be useful to a better understanding of the strength and nature of the Arctic sea ice decline. This work concerns the investigation of the mutual variability between the seasonal fields of SIC and the downwelling surface shortwave radiation (SIS) in clear sky conditions, for the 1982-2009 period. SIC and SIS monthly data were collected from the National Snow and Ice Data Center (NSDIC) and from the Satellite Application Facility on Climate Monitoring (SAFCM), respectively. Then mainly analyzed through the method of maximum covariance analysis (MCA). Interesting results were found during the summer season, which is the relevant season since the sea ice melting: regions of maximum co-variability are located close to the Barents Sea and the Kara Sea. In addition, in these areas, expansion coefficients time series (of principal modes), show statistically significant (at 95%) correlations with climate oscillations such as the Northern Annular Mode (NAM), the North Atlantic Oscillation (NAO) and the Pacific North America (PNA) pattern

The Way Forward: A Practical Guideline for Successful Digital Transformation

This chapter presents key lessons learned and implications for practice resulting from the analysis of the empirical cases included in this book. We map emerging themes across five layers: unit or project, organization, organization ecosystem, ethical and environmental sustainability, and society. We identify two emerging trends: the co-evolution of organizational forms and new technologies and the fact that digital transformation increasingly happens on the organizational ecosystem level. This has consequences in terms of increased data work, new work processes, and the need to actively engage with sustainability policies. We highlight the need for a focus on the long-term effects of digital transformation initiatives with attention to their ripple effects over time.publishedVersio

Sea ice extent annual extremes analysis in the Arctic regions

This work analyses the minimum and maximum annual values of Sea Ice Extent (SIE) in the entire Arctic region and in some of its sub-regions. The SIE was computed from the daily sea ice concentration (SIC) data provided by the National Snow and Ice Data Center (NSIDC). The analysis, which covers the 1979-2016 period, aims to answer the following questions: (1) Do annual SIE maxima and minima trends of the various Arctic sub-regions present substantial differences among them? (2) Is the time span between SIE maxima and minima changing over the 38 years of the analysed period? (3) Which maxima and minima extremes can be detected, according to some objective criteria? (4) How much effective are the cross-correlations between the annual SIE maxima and minima time series and between these and some important climatic oscillations indices (Southern Oscillation and Arctic Oscillation)? and (5) are there any relationships of these cross-correlations with the extremes eventually identified in point (3)? With regard to the first point, SIE minima show a substantial decreasing trend, more or less statistically significant; for some sub-regions it can be observed that, after 2007 \u2013 year of a strong summer melting\u2013 previous sea ice levels have never resumed, suggesting that, around 2007, a substantial reduction of multi-year ice occurred. On the contrary, SIE maxima, show a decreasing trend in some sub-regions and an increasing one in others, a result which may be explained by the relative geographic location. For the different sub-regions: i) the time span between maxima and minima does not change significantly; ii) extremes of SIE maxima and/or minima have been detected for several years; and iii) significant cross-correlations of SIE maxima and/or minima with SOI have been found