Assessing an Open Government Data Initiative. The Case of OpenCoesione

2016 ◽  
Author(s):  
Carmelofrancesco Origlia ◽  
Domenico Cersosimo ◽  
Tito Bianchi ◽  
Alfredo Fortunato
Keyword(s):  
Open Government ◽  
Open Government Data ◽  
Government Data

scholarly journals Smarter Open Government Data for Society 5.0: Are Your Open Data Smart Enough?

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5204
Author(s):  
Anastasija Nikiforova
Keyword(s):  
Industry 4.0 ◽  
Economic Value ◽  
Open Data ◽  
Digital Data ◽  
Open Government ◽  
Data Sets ◽  
Time Data ◽  
Open Government Data ◽  
Information And Communication ◽  
Government Data

Nowadays, governments launch open government data (OGD) portals that provide data that can be accessed and used by everyone for their own needs. Although the potential economic value of open (government) data is assessed in millions and billions, not all open data are reused. Moreover, the open (government) data initiative as well as users’ intent for open (government) data are changing continuously and today, in line with IoT and smart city trends, real-time data and sensor-generated data have higher interest for users. These “smarter” open (government) data are also considered to be one of the crucial drivers for the sustainable economy, and might have an impact on information and communication technology (ICT) innovation and become a creativity bridge in developing a new ecosystem in Industry 4.0 and Society 5.0. The paper inspects OGD portals of 60 countries in order to understand the correspondence of their content to the Society 5.0 expectations. The paper provides a report on how much countries provide these data, focusing on some open (government) data success facilitating factors for both the portal in general and data sets of interest in particular. The presence of “smarter” data, their level of accessibility, availability, currency and timeliness, as well as support for users, are analyzed. The list of most competitive countries by data category are provided. This makes it possible to understand which OGD portals react to users’ needs, Industry 4.0 and Society 5.0 request the opening and updating of data for their further potential reuse, which is essential in the digital data-driven world.

Ranking hospitals’ burn care capacity using cluster analysis on open government data

2021 ◽  
pp. 106166
Author(s):  
HuiYan Ho ◽  
Sheuwen Chuang ◽  
Niann-Tzyy Dai ◽  
Chia-Hsin Cheng ◽  
Wei-Fong Kao
Keyword(s):  
Cluster Analysis ◽  
Open Government ◽  
Burn Care ◽  
Open Government Data ◽  
Government Data ◽  
Care Capacity

scholarly journals Open Government Data: A Stage Model

2011 ◽  
pp. 235-246 ◽  
Author(s):  
Evangelos Kalampokis ◽  
Efthimios Tambouris ◽  
Konstantinos Tarabanis
Keyword(s):  
Open Government ◽  
Stage Model ◽  
Open Government Data ◽  
Government Data

scholarly journals Mining Open Government Data for Business Intelligence Using Data Visualization: A Two-Industry Case Study

2021 ◽  
Vol 16 (4) ◽  
pp. 1042-1065
Author(s):  
Anne Gottfried ◽  
Caroline Hartmann ◽  
Donald Yates
Keyword(s):  
Data Visualization ◽  
Business Intelligence ◽  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Open Government ◽  
Open Government Data ◽  
Market Opportunities ◽  
Government Data ◽  
Source Of Information

The business intelligence (BI) market has grown at a tremendous rate in the past decade due to technological advancements, big data and the availability of open source content. Despite this growth, the use of open government data (OGD) as a source of information is very limited among the private sector due to a lack of knowledge as to its benefits. Scant evidence on the use of OGD by private organizations suggests that it can lead to the creation of innovative ideas as well as assist in making better informed decisions. Given the benefits but lack of use of OGD to generate business intelligence, we extend research in this area by exploring how OGD can be used to generate business intelligence for the identification of market opportunities and strategy formulation; an area of research that is still in its infancy. Using a two-industry case study approach (footwear and lumber), we use latent Dirichlet allocation (LDA) topic modeling to extract emerging topics in these two industries from OGD, and a data visualization tool (pyLDAVis) to visualize the topics in order to interpret and transform the data into business intelligence. Additionally, we perform an environmental scanning of the environment for the two industries to validate the usability of the information obtained. The results provide evidence that OGD can be a valuable source of information for generating business intelligence and demonstrate how topic modeling and visualization tools can assist organizations in extracting and analyzing information for the identification of market opportunities.

scholarly journals UVLens

2021 ◽  
Vol 5 (2) ◽  
pp. 1-26
Author(s):  
Longbiao Chen ◽  
Chenhui Lu ◽  
Fangxu Yuan ◽  
Zhihan Jiang ◽  
Leye Wang ◽  
...  
Keyword(s):  
Large Scale ◽  
Floating Population ◽  
Open Government ◽  
Residential Areas ◽  
Rapid Urbanization ◽  
Urban Village ◽  
Open Government Data ◽  
Government Data ◽  
Real World Datasets ◽  
Urban Villages

Urban villages refer to the residential areas lagging behind the rapid urbanization process in many developing countries. These areas are usually with overcrowded buildings, high population density, and low living standards, bringing potential risks of public safety and hindering the urban development. Therefore, it is crucial for urban authorities to identify the boundaries of urban villages and estimate their resident and floating populations so as to better renovate and manage these areas. Traditional approaches, such as field surveys and demographic census, are time consuming and labor intensive, lacking a comprehensive understanding of urban villages. Against this background, we propose a two-phase framework for urban village boundary identification and population estimation. Specifically, based on heterogeneous open government data, the proposed framework can not only accurately identify the boundaries of urban villages from large-scale satellite imagery by fusing road networks guided patches with bike-sharing drop-off patterns, but also accurately estimate the resident and floating populations of urban villages with a proposed multi-view neural network model. We evaluate our method leveraging real-world datasets collected from Xiamen Island. Results show that our framework can accurately identify the urban village boundaries with an IoU of 0.827, and estimate the resident population and floating population with R2 of 0.92 and 0.94 respectively, outperforming the baseline methods. We also deploy our system on the Xiamen Open Government Data Platform to provide services to both urban authorities and citizens.

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