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A FRAMEWORK FOR IMPROVED DATA FLOW AND INTEROPERABILITY THROUGH DATA STRUCTURES, AGRICULTURAL SYSTEM MODELS, AND DECISION SUPPORT TOOLSSamuel A Noel (13171302) 28 July 2022 (has links)
<p>The agricultural data landscape is largely dysfunctional because of the industry’s highvariability in scale, scope, technological adoption, and relationships. Integrated data andmodels of agricultural sub-systems could be used to advance decision-making, but interoperability challenges prevent successful innovation. In this work, temporal and geospatial indexing strategies and aggregation were explored toward the development of functional data structures for soils, weather, solar, and machinery-collected yield data that enhance data context, scalability, and sharability.</p>
<p>The data structures were then employed in the creation of decision support tools including web-based applications and visualizations. One such tool leveraged a geospatial indexing technique called geohashing to visualize dense yield data and measure the outcomes of on-farm yield trials. Additionally, the proposed scalable, open-standard data structures were used to drive a soil water balance model that can provide insights into soil moisture conditions critical to farm planning, logistics, and irrigation. The model integrates SSURGO soil data,weather data from the Applied Climate Information System, and solar data from the National Solar Radiation Database in order to compute a soil water balance, returning values including runoff, evaporation, and soil moisture in an automated, continuous, and incremental manner.</p>
<p>The approach leveraged the Open Ag Data Alliance framework to demonstrate how the data structures can be delivered through sharable Representational State Transfer Application Programming Interfaces and to run the model in a service-oriented manner such that it can be operated continuously and incrementally, which is essential for driving real-time decision support tools. The implementations rely heavily on the Javascript Object Notation data schemas leveraged by Javascript/Typescript front-end web applications and back-end services delivered through Docker containers. The approach embraces modular coding concepts and several levels of open source utility packages were published for interacting with data sources and supporting the service-based operations.</p>
<p>By making use of the strategies laid out by this framework, industry and research canenhance data-based decision making through models and tools. Developers and researchers will be better equipped to take on the data wrangling tasks involved in retrieving and parsing unfamiliar datasets, moving them throughout information technology systems, and understanding those datasets down to a semantic level.</p>
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Combining Business Intelligence, Indicators, and the User Requirements Notation for Performance MonitoringJohari Shirazi, Iman 26 November 2012 (has links)
Organizations use Business Intelligence (BI) systems to monitor how well they are meeting
their goals and objectives. Yet, very often BI systems do not include clear models of
the organization’s goals or of how to measure whether they are satisfied or not. Several
researchers now attempt to integrate goal models into BI systems, but there are still major
challenges related to how to get access to the BI data to populate the part of the goal
model (often indicators) used to assess goal satisfaction.
This thesis explores a new approach to integrate BI systems with goal models. In
particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI
tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open
source graphical editor for the User Requirements Notation (URN), which includes the
Use Case Map notation for scenarios and processes and the Goal-oriented Requirement
Language for business objectives. URN was recently extended with the concept of Key
Performance Indicator (KPI) to enable performance assessment and monitoring of business
processes. In jUCMNav, KPIs are currently calculated or modified manually. The
new integration proposed in this thesis maps these KPIs to report elements that are generated
automatically by Cognos based on the model defined in jUCMNav at runtime, with
minimum effort. We are using IBM Cognos Mashup Service, which includes web services
that enable the retrieval of report elements at the most granular level. This transformation
provides managers and analysts with useful goal-oriented and process-oriented
monitoring views fed by just-in-time BI information. This new solution also automates
retrieving data from Cognos servers, which helps reducing the high costs usually caused
by the amount of manual work required otherwise.
The novel approach presented in this thesis avoids manual report generation and
minimizes any contract with respect to the location of manually created reports, hence
leading to better usability and performance. The approach and its tool support are illustrated
with an ongoing example, validated with a case study, and verified through testing.
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Combining Business Intelligence, Indicators, and the User Requirements Notation for Performance MonitoringJohari Shirazi, Iman 26 November 2012 (has links)
Organizations use Business Intelligence (BI) systems to monitor how well they are meeting
their goals and objectives. Yet, very often BI systems do not include clear models of
the organization’s goals or of how to measure whether they are satisfied or not. Several
researchers now attempt to integrate goal models into BI systems, but there are still major
challenges related to how to get access to the BI data to populate the part of the goal
model (often indicators) used to assess goal satisfaction.
This thesis explores a new approach to integrate BI systems with goal models. In
particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI
tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open
source graphical editor for the User Requirements Notation (URN), which includes the
Use Case Map notation for scenarios and processes and the Goal-oriented Requirement
Language for business objectives. URN was recently extended with the concept of Key
Performance Indicator (KPI) to enable performance assessment and monitoring of business
processes. In jUCMNav, KPIs are currently calculated or modified manually. The
new integration proposed in this thesis maps these KPIs to report elements that are generated
automatically by Cognos based on the model defined in jUCMNav at runtime, with
minimum effort. We are using IBM Cognos Mashup Service, which includes web services
that enable the retrieval of report elements at the most granular level. This transformation
provides managers and analysts with useful goal-oriented and process-oriented
monitoring views fed by just-in-time BI information. This new solution also automates
retrieving data from Cognos servers, which helps reducing the high costs usually caused
by the amount of manual work required otherwise.
The novel approach presented in this thesis avoids manual report generation and
minimizes any contract with respect to the location of manually created reports, hence
leading to better usability and performance. The approach and its tool support are illustrated
with an ongoing example, validated with a case study, and verified through testing.
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Combining Business Intelligence, Indicators, and the User Requirements Notation for Performance MonitoringJohari Shirazi, Iman January 2012 (has links)
Organizations use Business Intelligence (BI) systems to monitor how well they are meeting
their goals and objectives. Yet, very often BI systems do not include clear models of
the organization’s goals or of how to measure whether they are satisfied or not. Several
researchers now attempt to integrate goal models into BI systems, but there are still major
challenges related to how to get access to the BI data to populate the part of the goal
model (often indicators) used to assess goal satisfaction.
This thesis explores a new approach to integrate BI systems with goal models. In
particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI
tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open
source graphical editor for the User Requirements Notation (URN), which includes the
Use Case Map notation for scenarios and processes and the Goal-oriented Requirement
Language for business objectives. URN was recently extended with the concept of Key
Performance Indicator (KPI) to enable performance assessment and monitoring of business
processes. In jUCMNav, KPIs are currently calculated or modified manually. The
new integration proposed in this thesis maps these KPIs to report elements that are generated
automatically by Cognos based on the model defined in jUCMNav at runtime, with
minimum effort. We are using IBM Cognos Mashup Service, which includes web services
that enable the retrieval of report elements at the most granular level. This transformation
provides managers and analysts with useful goal-oriented and process-oriented
monitoring views fed by just-in-time BI information. This new solution also automates
retrieving data from Cognos servers, which helps reducing the high costs usually caused
by the amount of manual work required otherwise.
The novel approach presented in this thesis avoids manual report generation and
minimizes any contract with respect to the location of manually created reports, hence
leading to better usability and performance. The approach and its tool support are illustrated
with an ongoing example, validated with a case study, and verified through testing.
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