scholarly journals Framework for WASH Sector Data Improvements in Data-Poor Environments, Applied to Accra, Ghana

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1278
Author(s):  
Rembrandt H. E. M. Koppelaar ◽  
May N. Sule ◽  
Zoltán Kis ◽  
Foster K. Mensah ◽  
Xiaonan Wang ◽  
...  
Keyword(s):  
Data Integration ◽  
Day Treatment ◽  
Open Data ◽  
Data Availability ◽  
Treated Wastewater ◽  
Data Sets ◽  
Infrastructure Development ◽  
Integration Framework ◽  
Modelling Methodology ◽  
Level Of Understanding

Improvements in water, sanitation and hygiene (WASH) service provision are hampered by limited open data availability. This paper presents a data integration framework, collects the data and develops a material flow model, which aids data-based policy and infrastructure development for the WASH sector. This model provides a robust quantitative mapping of the complete anthropogenic WASH flow-cycle: from raw water intake to water use, wastewater and excreta generation, discharge and treatment. This approach integrates various available sources using a process-chain bottom-up engineering approach to improve the quality of WASH planning. The data integration framework and the modelling methodology are applied to the Greater Accra Metropolitan Area (GAMA), Ghana. The highest level of understanding of the GAMA WASH sector is achieved, promoting scenario testing for future WASH developments. The results show 96% of the population had access to improved safe water in 2010 if sachet and bottled water was included, but only 67% if excluded. Additionally, 66% of 338,000 m3 per day of generated wastewater is unsafely disposed locally, with 23% entering open drains, and 11% sewage pipes, indicating poor sanitation coverage. Total treated wastewater is <0.5% in 2014, with only 18% of 43,000 m3 per day treatment capacity operational. The combined data sets are made available to support research and sustainable development activities.

scholarly journals Framework for a Symmetric Integration Approach

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 224
Author(s):  
Mihaela Muntean ◽  
Claudiu Brândaş ◽  
Tanita Cîrstea
Keyword(s):  
Data Integration ◽  
Open Data ◽  
Application Integration ◽  
Cloud Environment ◽  
Integration Framework ◽  
Symmetry Approach ◽  
Integration Approach ◽  
Implementation Aspects

An Application-to-Application integration framework in the cloud environment is proposed. The methodological demarche is developed using a data symmetry approach. Implementation aspects of integration considered the Open Data Protocol (OData) service as an integrator. An important issue in the cloud environment is to integrate and ensure the quality of transferred and processed data. An efficient way of ensuring the completeness and integrity of data transferred between different applications and systems is the symmetry of data integration. With these considerations, the integration of SAP Hybris Cloud for Customer with S/4 HANA Cloud was implemented.

scholarly journals BIG GEO DATA MANAGEMENT: AN EXPLORATION WITH SOCIAL MEDIA AND TELECOMMUNICATIONS OPEN DATA

2016 ◽  
Vol XLI-B2 ◽  
pp. 595-601
Author(s):  
C. Arias Munoz ◽  
M. A. Brovelli ◽  
S. Corti ◽  
G. Zamboni
Keyword(s):  
Data Integration ◽  
High Speed ◽  
High Performance ◽  
Open Data ◽  
Geospatial Data ◽  
Data Sets ◽  
Complex Data ◽  
Complex Data Sets ◽  
Computationally Intensive ◽  
The Government

The term Big Data has been recently used to define big, highly varied, complex data sets, which are created and updated at a high speed and require faster processing, namely, a reduced time to filter and analyse relevant data. These data is also increasingly becoming Open Data (data that can be freely distributed) made public by the government, agencies, private enterprises and among others. There are at least two issues that can obstruct the availability and use of Open Big Datasets: Firstly, the gathering and geoprocessing of these datasets are very computationally intensive; hence, it is necessary to integrate high-performance solutions, preferably internet based, to achieve the goals. Secondly, the problems of heterogeneity and inconsistency in geospatial data are well known and affect the data integration process, but is particularly problematic for Big Geo Data. Therefore, Big Geo Data integration will be one of the most challenging issues to solve. With these applications, we demonstrate that is possible to provide processed Big Geo Data to common users, using open geospatial standards and technologies. NoSQL databases like MongoDB and frameworks like RASDAMAN could offer different functionalities that facilitate working with larger volumes and more heterogeneous geospatial data sources.

Integrating Semi-Open Data in a Criminal Judicial Setting

2017 ◽  
pp. 137-156 ◽  
Author(s):  
Mortaza S. Bargh ◽  
Sunil Choenni ◽  
Ronald F. Meijer
Keyword(s):  
Data Integration ◽  
Open Data ◽  
Management Systems ◽  
Public Prosecutor ◽  
Data Sets ◽  
New Paradigm ◽  
Criminal Cases ◽  
Raw Data ◽  
The Public ◽  
Data Requirements

Judiciary systems comprise various partner organizations (e.g., police, public prosecutor, courts, and rehabilitation centres) that collaboratively resolve criminal cases. These partner organizations have their own data administration and management systems, which are setup/operated separately and integrated barely. This chapter explains the approach of the authors' organization for integrating the data sets of the Dutch judiciary systems, and for opening the data integration outcomes to the public and/or to specific groups. These outcomes (e.g., data sets and reports) are meant to provide useful insights into (the performances of) the partner organizations individually and collectively. Such data opening efforts do not comply with all Open Data requirements, mainly due to the quality, (privacy) sensitivity and interoperability issues of the raw data. Nevertheless, since these initiatives aim at delivering some benefits of Open Data, the chapter introduces the new paradigm of Semi-Open Data for acknowledging such data opening initiatives.

scholarly journals Linked Administrative Data at Statistics Canada – new data resources for horizontal research

2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Li Xue
Keyword(s):  
Data Integration ◽  
Financial Literacy ◽  
Record Linkage ◽  
Economic Status ◽  
Data Availability ◽  
Data Sets ◽  
Full Spectrum ◽  
Social Data ◽  
Factors Affecting ◽  
Statistics Canada

There has been an increasing demand for analytics and research related to cross-cutting and horizontal issues in Canada, such as in the domains of housing, aging and immigration. Very often policy makers and stakeholders are posing a full spectrum of questions around a specific topic, requiring multidisciplinary evidence and data. Statistics Canada has a long history of record linkage. Over the past decade, the number of record linkage projects has increased exponentially. Several established platforms have been developed to facilitate linkage – Canadian Employer and Employer Database which brings together tax and employment records from both employees and employers; the Social Data Linkage Environment created to support linkages at the individuals level across a broad spectrum of social data (health, justice, education, socio-economic); and the Linkable File Environment for business data. The breadth of our data holdings married with record linkage capabilities allows the creation of data sets that crosses disciplines and areas or research. This presentation will showcase the innovative data integration approaches that Statistics Canada has advanced to meet the inter-disciplinary data needs. Statistics Canada are pioneering in some innovative linkages across various domains to help answer cross-cutting questions. For example, Longitudinal Administrative Databank linking longitudinal tax records to numerous other data files including tax records of spouses and children in the household, longitudinal Immigration Database linkage key and health records, is used to study economic impact of hospitalization, as well as better understand health outcomes of immigrants by various dimensions including socio-economic status. Other examples include the pilot projects linking Canadian Financial Capability Survey to tax records, to gauge the relationship between financial literacy and annual retirement savings behavior and Intergenerational Income Database being linked to Census to understand socio-economic factors affecting the intergenerational mobility. Rapid growth in data availability for research also poses new challenges on IM/IT, governance, access, capacity building, etc. As Statistics Canada has moved on a path of modernization, data integration is key to the development of new data sources to fill information gaps as we move forward.

scholarly journals BIG GEO DATA MANAGEMENT: AN EXPLORATION WITH SOCIAL MEDIA AND TELECOMMUNICATIONS OPEN DATA

2016 ◽  
Vol XLI-B2 ◽  
pp. 595-601
Author(s):  
C. Arias Munoz ◽  
M. A. Brovelli ◽  
S. Corti ◽  
G. Zamboni
Keyword(s):  
Data Integration ◽  
High Speed ◽  
High Performance ◽  
Open Data ◽  
Geospatial Data ◽  
Data Sets ◽  
Complex Data ◽  
Complex Data Sets ◽  
Computationally Intensive ◽  
The Government

The term Big Data has been recently used to define big, highly varied, complex data sets, which are created and updated at a high speed and require faster processing, namely, a reduced time to filter and analyse relevant data. These data is also increasingly becoming Open Data (data that can be freely distributed) made public by the government, agencies, private enterprises and among others. There are at least two issues that can obstruct the availability and use of Open Big Datasets: Firstly, the gathering and geoprocessing of these datasets are very computationally intensive; hence, it is necessary to integrate high-performance solutions, preferably internet based, to achieve the goals. Secondly, the problems of heterogeneity and inconsistency in geospatial data are well known and affect the data integration process, but is particularly problematic for Big Geo Data. Therefore, Big Geo Data integration will be one of the most challenging issues to solve. With these applications, we demonstrate that is possible to provide processed Big Geo Data to common users, using open geospatial standards and technologies. NoSQL databases like MongoDB and frameworks like RASDAMAN could offer different functionalities that facilitate working with larger volumes and more heterogeneous geospatial data sources.

scholarly journals Multisource Spatial Data Integration for Use Cases Applications

2021 ◽  
Author(s):  
Francesca Noardo
Keyword(s):  
Data Integration ◽  
Spatial Data ◽  
Open Data ◽  
Use Cases ◽  
Data Sets ◽  
Data Merging ◽  
Geometrical Complexity ◽  
Long Time ◽  
Spatial Data Integration ◽  
Definition Of

Big opportunities are given by the reuse and integration of data, which, nowadays, are more and more available, thanks to advances in acquisition and modelling technologies and the open data paradigm. Seamlessly integrating data from heterogenous data sources has been an interest of the geospatial community for long time. However, the higher semantic and geometrical complexity pose new challenges which have never been tackled in a comprehensive methodology. Building on the previous theories and studies, this paper proposes an overarching methodology for multisource spatial data integration. Starting from the definition of the use case-based requirements for the integrated data, it proposes a framework to analyse the involved datasets with respect to integrability and suggests actions to harmonise them towards the destination model. The overall workflow is explained, including the data merging phase and validation. The methodology is tested and exemplified on a case study. Considering the specific data sets&rsquo; features and parameters, this approach will allow the development of consistent, well documented and inclusive data integration workflows, for the sake of use cases processes automation and the production of Interoperable and Reusable data.

Integrating Semi-Open Data in a Criminal Judicial Setting

2020 ◽  
pp. 872-891
Author(s):  
Mortaza S. Bargh ◽  
Sunil Choenni ◽  
Ronald F. Meijer
Keyword(s):  
Data Integration ◽  
Open Data ◽  
Management Systems ◽  
Public Prosecutor ◽  
Data Sets ◽  
New Paradigm ◽  
Criminal Cases ◽  
Raw Data ◽  
The Public ◽  
Data Requirements

Judiciary systems comprise various partner organizations (e.g., police, public prosecutor, courts, and rehabilitation centres) that collaboratively resolve criminal cases. These partner organizations have their own data administration and management systems, which are setup/operated separately and integrated barely. This chapter explains the approach of the authors' organization for integrating the data sets of the Dutch judiciary systems, and for opening the data integration outcomes to the public and/or to specific groups. These outcomes (e.g., data sets and reports) are meant to provide useful insights into (the performances of) the partner organizations individually and collectively. Such data opening efforts do not comply with all Open Data requirements, mainly due to the quality, (privacy) sensitivity and interoperability issues of the raw data. Nevertheless, since these initiatives aim at delivering some benefits of Open Data, the chapter introduces the new paradigm of Semi-Open Data for acknowledging such data opening initiatives.

Government Open Data and Sensing Data Integration Framework for Smart Construction Site Management

2019 ◽  
Author(s):  
Chiu-Ming Lee ◽  
Wei-Liang Kuo ◽  
Tzu-Jan Tung ◽  
Bo-Kai Huang ◽  
Shu-Hsiang Hsu ◽  
...  
Keyword(s):  
Data Integration ◽  
Open Data ◽  
Construction Site ◽  
Site Management ◽  
Integration Framework ◽  
Sensing Data

scholarly journals A Knowledge Graph-Based Data Integration Framework Applied to Battery Data Management

2021 ◽  
Vol 13 (3) ◽  
pp. 1583
Author(s):  
Tahir Emre Kalaycı ◽  
Bor Bricelj ◽  
Marko Lah ◽  
Franz Pichler ◽  
Matthias K. Scharrer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Integration ◽  
Electric Vehicles ◽  
Data Science ◽  
Transportation Systems ◽  
Transformation Process ◽  
Knowledge Graph ◽  
Data Sets ◽  
Use Case ◽  
Integration Framework

Today, the automotive and transportation sector is undergoing a transformation process to meet the requirements of sustainable and efficient operations. This transformation mainly reveals itself by electric vehicles, hybrid electric vehicles, and electric vehicle sharing. One significant, and the most expensive, component in electric vehicles is the batteries, and the management of batteries is crucial. It is essential to perform constant monitoring of behavior changes for operational purposes and quickly adjust components and operations to these changes. Thus, to address these challenges, we propose a knowledge graph-based data integration framework for simplifying access and analysis of data accumulated through the operations of vehicles and related transportation systems. The proposed framework aims to enable the effortless analysis and navigation of integrated knowledge and the creation of additional data sets from this knowledge to use during the application of data analysis and machine learning. The knowledge graph serves as a significant component to simplify the extraction, enrichment, exploration, and generation of data in this framework. We have developed it according to the human-centered design, and various roles of the data science and machine learning life cycle can use it. Its main objective is to streamline the exploration and interaction with the integrated data to maximize human productivity. Finally, we present a battery use case to show the feasibility and benefits of the proposed framework. The use case illustrates the usage of the framework to extract knowledge from raw data, navigate and enrich it with additional knowledge, and generate data sets.

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.

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