scholarly journals Data Sources Analysis for Sustainable Trip Planner Development for Riga City

2021 ◽  
Vol 22 (3) ◽  
pp. 321-331
Author(s):  
Alise Dinko ◽  
Irina Yatskiv Jackiva ◽  
Evelina Budilovich Budiloviča
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Open Data ◽  
Life Quality ◽  
Data Sources ◽  
Added Value ◽  
Transportation Services ◽  
Data Usage ◽  
Trip Planner ◽  
To Receive

Abstract In today’s daily traveller world, not only the time and money became important, but climate change and pandemic raised the importance of safety and sustainability of future trip plans. In order to provide such a wide coverage for a variety of important information, a sustainable trip planner needs to receive a lot of data from a variety of differentiated data sources. Provided review of related works shows that a lot of started activities in this aspects gives all of us promises and hope that available Big Data sources will be wisely used in order to bring added value not only to individual travellers, but also society, the transportation services will become better structured and information will be easily available for smart and safe decision making, that gradually will increase life quality. The study’s main goal is analysis of open data sources for the trip planner development. Authors analysed availability of data for Riga transport system and data usage for sustainable trip planner.

scholarly journals A Smart Decision System for Digital Farming

Agronomy ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 216 ◽  
Author(s):  
Carlos Cambra Baseca ◽  
Sandra Sendra ◽  
Jaime Lloret ◽  
Jesus Tomas
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Information Exchange ◽  
New Technologies ◽  
Open Data ◽  
Weather Conditions ◽  
Added Value ◽  
Aerial Images ◽  
Sampled Data ◽  
Application Development

New technologies have the potential to transform agriculture and to reduce environmental impact through a green revolution. Internet of Things (IoT)-based application development platforms have the potential to run farm management tools capable of monitoring real-time events when integrated into interactive innovation models for fertirrigation. Their capabilities must extend to flexible reconfiguration of programmed actions. IoT platforms require complex smart decision-making systems based on data-analysis and data mining of big data sets. In this paper, the advantages are demonstrated of a powerful tool that applies real-time decisions from data such as variable rate irrigation, and selected parameters from field and weather conditions. The field parameters, the index vegetation (estimated using aerial images), and the irrigation events, such as flow level, pressure level, and wind speed, are periodically sampled. Data is processed in a decision-making system based on learning prediction rules in conjunction with the Drools rule engine. The multimedia platform can be remotely controlled, and offers a smart farming open data network with shared restriction levels for information exchange oriented to farmers, the fertilizer provider, and agricultural technicians that should provide the farmer with added value in the form of better decision making or more efficient exploitation operations and management.

Patient-Centered Clinical Trials Decision Support Using Linked Open Data

2018 ◽  
pp. 1765-1782
Author(s):  
Bonnie MacKellar ◽  
Christina Schweikert ◽  
Soon Ae Chun
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
Clinical Trials ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Linked Data ◽  
Open Data ◽  
Data Sources ◽  
Patient Centered

Patients often want to participate in relevant clinical trials for new or more effective alternative treatments. The clinical search system made available by the NIH is a step forward to support the patient's decision making, but, it is difficult to use and requires the patient to sift through lengthy text descriptions for relevant information. In addition, patients deciding whether to pursue a given trial often want more information, such as drug information. The authors' overall aim is to develop an intelligent patient-centered clinical trial decision support system. Their approach is to integrate Open Data sources related to clinical trials using the Semantic Web's Linked Data framework. The linked data representation, in terms of RDF triples, allows the development of a clinical trial knowledge base that includes entities from different open data sources and relationships among entities. The authors consider Open Data sources such as clinical trials provided by NIH as well as the drug side effects dataset SIDER. The authors use UMLS (Unified Medical Language System) to provide consistent semantics and ontological knowledge for clinical trial related entities and terms. The authors' semantic approach is a step toward a cognitive system that provides not only patient-centered integrated data search but also allows automated reasoning in search, analysis and decision making using the semantic relationships embedded in the Linked data. The authors present their integrated clinical trial knowledge base development and a prototype, patient-centered Clinical Trial Decision Support System that include capabilities of semantic search and query with reasoning ability, and semantic-link browsing where an exploration of one concept leads to other concepts easily via links which can provide visual search for the end users.

scholarly journals The meaningfulness of open data in Public Health and Healthcare

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
J Pita Costa ◽  
F Fuart ◽  
B Cleland ◽  
J Wallace ◽  
A Staines ◽  
...  
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Open Data ◽  
Knowledge Bases ◽  
Data Sources ◽  
Local Context ◽  
Easy Access ◽  
New Information ◽  
Challenges And Opportunities ◽  
Complex Ecosystem

Abstract Background The growing challenges and opportunities of Big Data for Public Health have revealed the potential to improve the efficiency and cost-effectiveness of public policy, for example through better targeting of resources with regard to General Practice (GP) prescribing. Open data has an important role due to its easy access and potential to complement proprietary data sources from, e.g., regional hospitals, and also itself be complemented with social data acquired by specialized approaches. Methods MIDAS pipeline of open source tools aiming integrating, analysing and visualising Open Data enabling health professionals and decision-makers to: (i) improve the usability of open data in combination with proprietary data through combining multiple visualisation tools in an integrated dashboard (ii) to explore the meaning of data in a global/local context based on new information using tone analysis and natural language techniques; and (iii) to have better informed decision-making based on evidence from trusted knowledge-bases. Specific data sources used have included information extracted from the biomedical database MEDLINE, worldwide news and government open data. Social media sources have also been used to gather information from the general public. Results Results include a strong correlation between antidepressant prescribing and economic deprivation, and a wide variation in how individual GP practices respond to demographic conditions. Automated anomaly detection based on the Local Outlier Probability has also been shown to be an easily understood and controllable approach to identifying prescribing outliers. Conclusions MIDAS demonstrates the significant value of open data from heterogeneous sources as basis decision-making in public health and healthcare, particularly when it is combined with proprietary or closed datasets. A key challenge in this regard is the ability to integrate and utilize data from diverse sources in a variety of formats and standards. Key messages MIDAS is exemplar on tackling the need for improved standards of open data, and new software architectures, tools and platforms addressing a complex ecosystem of heterogenous data sources and formats. MIDAS demonstrates the significant value of open data from heterogeneous sources as basis decision-making in public health and healthcare, particularly when combined with proprietary datasets.

Climate services for large scale investments in infrastructure and climate resilience in the Danube Basin

2020 ◽  
Author(s):  
Jelena Radonić ◽  
Maja Turk Sekulić ◽  
Dubravko Ćulibrk ◽  
Martin Drews ◽  
Mads L. Dømgaard ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Danube River ◽  
Added Value ◽  
Modeling Framework ◽  
Danube Basin ◽  
Climate Services ◽  
Flood Risks ◽  
Novi Sad ◽  
Adaptation Options

<p>The results presented in this contribution demonstrate the value of climate services for the planned construction of the new Wastewater Treatment Plant (WWTP) in Novi Sad, Serbia. In this case, climate services provided added value for the decision-making processes, in terms of enhanced effectiveness, optimized technological opportunities and minimized risks and by serving as the means of involving and better-informing end-users and stakeholders. The specific goal of the research was to improve climate change resilience of the WWTP and to facilitate better overall hygienic conditions in Novi Sad and to safeguard the potable water resources and the quality of the environment in the areas located downstream and under the influence of the Danube River.</p><p>In order to achieve it, preliminary activities were oriented on analyzing the current climate and hydrological conditions, engaging the relevant data providers, stakeholders and policy makers and evaluating what relevant local data would be useful for the study. The data collected was applied in the testing and for improving the Future Danube Multi-hazard, Multi-risk Model (FDM), a catastrophe model implemented in the OASIS Loss Modeling Framework (Oasis-LMF). The FDM is implemented for the entire Danube Basin. High-resolution components for pluvial flood risks were further implemented to the city of Novi Sad, Serbia, after successful testing in the Budapest region. Observations and model results were used in a climate change impact assessment with the purpose of identifying adaptation options, appraisal of adaptation options and integration of an adaptation action plan into the Feasibility Study of the WWTP construction. The results of the pluvial flood model for Novi Sad clearly suggested that it is important to consider pluvial flood risks and that protective measures have to be considered as part of the WWTP construction, both under current and future climate conditions. Moreover, novel estimates of drainage water intensities during heavy rains would advise the design of the simultaneously planned pumping station on the banks of the Danube. Combined, this clearly demonstrates the added value of the climate services and risk information delivered by the FDM also beyond the insurance sector, as well as its potential to support adaptation decision making with respect to infrastructural investments in Novi Sad.</p>

Patient-Centered Clinical Trials Decision Support using Linked Open Data

2014 ◽  
Vol 6 (3) ◽  
pp. 31-48 ◽  
Author(s):  
Bonnie MacKellar ◽  
Christina Schweikert ◽  
Soon Ae Chun
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
Clinical Trials ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Linked Data ◽  
Open Data ◽  
Data Sources ◽  
Patient Centered

Patients often want to participate in relevant clinical trials for new or more effective alternative treatments. The clinical search system made available by the NIH is a step forward to support the patient's decision making, but, it is difficult to use and requires the patient to sift through lengthy text descriptions for relevant information. In addition, patients deciding whether to pursue a given trial often want more information, such as drug information. The authors' overall aim is to develop an intelligent patient-centered clinical trial decision support system. Their approach is to integrate Open Data sources related to clinical trials using the Semantic Web's Linked Data framework. The linked data representation, in terms of RDF triples, allows the development of a clinical trial knowledge base that includes entities from different open data sources and relationships among entities. The authors consider Open Data sources such as clinical trials provided by NIH as well as the drug side effects dataset SIDER. The authors use UMLS (Unified Medical Language System) to provide consistent semantics and ontological knowledge for clinical trial related entities and terms. The authors' semantic approach is a step toward a cognitive system that provides not only patient-centered integrated data search but also allows automated reasoning in search, analysis and decision making using the semantic relationships embedded in the Linked data. The authors present their integrated clinical trial knowledge base development and a prototype, patient-centered Clinical Trial Decision Support System that include capabilities of semantic search and query with reasoning ability, and semantic-link browsing where an exploration of one concept leads to other concepts easily via links which can provide visual search for the end users.

Kepemimpinan Demokratis Kepala Sekolah dalam Meningkatkan Prestasi di Madrasah Aliyah Negeri Model Palangka Raya

2016 ◽  
Vol 2 (2) ◽  
pp. 6-9
Author(s):  
Shanty Bahar Ising ◽  
Mujiono Mujiono
Keyword(s):  
Secondary Data ◽  
Data Sources ◽  
Primary Data ◽  
Democratic Leadership ◽  
Model State ◽  
Teachers And Students ◽  
Secondary Data Sources ◽  
Conceptual Skills ◽  
To Receive ◽  
Teacher Trainer

This study aims to find out, describe and analyze the democratic leadership of the Principal in improving achievement at the Palangka Raya Model State Madrasah (MAN). The research method used is descriptive qualitative. The researcher wanted to describe the Principal's democratic leadership in improving achievement at the Palangka Raya Model State Islamic Senior High School (MAN). Primary data sources (person) are the Principal, Teachers (Teachers) and Students of MAN Model Palangka Raya. Whereas secondary data sources are the data in the Palangka Raya Model MAN and supporting literature. The results of the study show that the Principal's leadership in improving achievement in the Palangka Raya Model MAN is very democratic, this condition can be seen from: (1) Principals are happy to receive suggestions, opinions and even criticism from subordinates both delivered by students and teachers through suggestion boxes and in the teacher council meeting, (2) the Principal always strives to prioritize teamwork cooperation in an effort to achieve the goal by appointing the instructor teacher, trainer teacher and mentor teacher and conducting deliberation in planning, implementing and evaluating activities, (3) the Principal always tries to make subordinates more success than him, which is realized by including teachers in seminars, workshops, training and competitions so that they get achievements both locally and nationally, and (4) Principals always try to develop their personal capacity as good leaders in conceptual skills, human skill and technical skill.

Megadrought and Collapse

2017 ◽  
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Case Studies ◽  
Agricultural Landscapes ◽  
15Th Century ◽  
Societal Collapse ◽  
The Face ◽  
Time Periods ◽  
Paleoclimate Proxy ◽  
Habitat Tracking

This is the first book to treat the major examples of megadrought and societal collapse, from the late Pleistocene end of hunter–gatherer culture and origins of cultivation to the 15th century AD fall of the Khmer Empire capital at Angkor, and ranging from the Near East to South America. Previous enquiries have stressed the possible multiple and internal causes of collapse, such overpopulation, overexploitation of resources, warfare, and poor leadership and decision-making. In contrast, Megadrought and Collapse presents case studies of nine major episodes of societal collapse in which megadrought was the major and independent cause of societal collapse. In each case the most recent paleoclimatic evidence for megadroughts, multiple decades to multiple centuries in duration, is presented alongside the archaeological records for synchronous societal collapse. The megadrought data are derived from paleoclimate proxy sources (lake, marine, and glacial cores; speleothems, or cave stalagmites; and tree-rings) and are explained by researchers directly engaged in their analysis. Researchers directly responsible for them discuss the relevant current archaeological records. Two arguments are developed through these case studies. The first is that societal collapse in different time periods and regions and at levels of social complexity ranging from simple foragers to complex empires would not have occurred without megadrought. The second is that similar responses to megadrought extend across these historical episodes: societal collapse in the face of insurmountable climate change, abandonment of settlements and regions, and habitat tracking to sustainable agricultural landscapes. As we confront megadrought today, and in the likely future, Megadrought and Collapse brings together the latest contributions to our understanding of past societal responses to the crisis on an equally global and diverse scale.

scholarly journals ParlTech: Transformation Framework for the Digital Parliament

2021 ◽  
Vol 5 (1) ◽  
pp. 15
Author(s):  
Dimitris Koryzis ◽  
Apostolos Dalas ◽  
Dimitris Spiliotopoulos ◽  
Fotios Fitsilis
Keyword(s):  
Business Processes ◽  
Rapid Evolution ◽  
Open Data ◽  
Added Value ◽  
User Perspective ◽  
Novel Technologies ◽  
Innovative Methods ◽  
Data Production ◽  
Governance Institutions ◽  
Transformational Framework

Societies are entering the age of technological disruption, which also impacts governance institutions such as parliamentary organizations. Thus, parliaments need to adjust swiftly by incorporating innovative methods into their organizational culture and novel technologies into their working procedures. Inter-Parliamentary Union World e-Parliament Reports capture digital transformation trends towards open data production, standardized and knowledge-driven business processes, and the implementation of inclusive and participatory schemes. Nevertheless, there is still a limited consensus on how these trends will materialize into specific tools, products, and services, with added value for parliamentary and societal stakeholders. This article outlines the rapid evolution of the digital parliament from the user perspective. In doing so, it describes a transformational framework based on the evaluation of empirical data by an expert survey of parliamentarians and parliamentary administrators. Basic sets of tools and technologies that are perceived as vital for future parliamentary use by intra-parliamentary stakeholders, such as systems and processes for information and knowledge sharing, are analyzed. Moreover, boundary conditions for development and implementation of parliamentary technologies are set and highlighted. Concluding recommendations regarding the expected investments, interdisciplinary research, and cross-sector collaboration within the defined framework are presented.

scholarly journals A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration

Epidemiologia ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 315-324
Author(s):  
Juan M. Banda ◽  
Ramya Tekumalla ◽  
Guanyu Wang ◽  
Jingyuan Yu ◽  
Tuo Liu ◽  
...  
Keyword(s):  
Large Scale ◽  
Social Dynamics ◽  
Additional Data ◽  
Open Data ◽  
Data Sources ◽  
Research Projects ◽  
Research Groups ◽  
The World ◽  
Data Source

As the COVID-19 pandemic continues to spread worldwide, an unprecedented amount of open data is being generated for medical, genetics, and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic is allowing other scientists to learn from local experiences and data generated on the front lines of the COVID-19 pandemic. However, there is a need to integrate additional data sources that map and measure the role of social dynamics of such a unique worldwide event in biomedical, biological, and epidemiological analyses. For this purpose, we present a large-scale curated dataset of over 1.12 billion tweets, growing daily, related to COVID-19 chatter generated from 1 January 2020 to 27 June 2021 at the time of writing. This data source provides a freely available additional data source for researchers worldwide to conduct a wide and diverse number of research projects, such as epidemiological analyses, emotional and mental responses to social distancing measures, the identification of sources of misinformation, stratified measurement of sentiment towards the pandemic in near real time, among many others.

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