Kroak: A metadata collection system for long term microbial community monitoring

Amplytica is start-up company whose software, called the Amplytica Cloud Platform, helps organizations determine how microbes influence their bioprocesses. Examples of such bioprocesses include anaerobic digestion, wastewater treatment and mine site reclamation. The Amplytica Cloud Platform does this by integrating and analyzing metagenomically derived microbial community data (species composition, diversity, and abundance) and industrial bioprocess data (e.g. temperature, pH, nutrients). To achieve data integration, industrial bioprocess data is considered metadata to the microbial community information and describes the environmental conditions where the microbial community is found. The capture of this industrial metadata requires a robust metadata capture system. Kroak is a metadata capture system for the Amplytica Cloud Platform that facilitates tagging per-sample microbial community information with industrial environmental metadata. It uses a modern web interface for easy deployment, Office Open XML Workbook (XLSX) template files for easy metadata capture, and metadata classes to ensure data consistency and type identification for follow on automated statistics and machine learning. Kroak is a functional metadata capture system which will be iteratively improved upon by Amplytica. Potential improvements include changes to Kroak’s data model, increasing the reliability of its metadata parsing and the expansion of its existing web application programming interface

Kroak: A metadata collection system for long term microbial community monitoring

Amplytica is start-up company whose software, called the Amplytica Cloud Platform, helps organizations determine how microbes influence their bioprocesses. Examples of such bioprocesses include anaerobic digestion, wastewater treatment and mine site reclamation. The Amplytica Cloud Platform does this by integrating and analyzing metagenomically derived microbial community data (species composition, diversity, and abundance) and industrial bioprocess data (e.g. temperature, pH, nutrients). To achieve data integration, industrial bioprocess data is considered metadata to the microbial community information and describes the environmental conditions where the microbial community is found. The capture of this industrial metadata requires a robust metadata capture system. Kroak is a metadata capture system for the Amplytica Cloud Platform that facilitates tagging per-sample microbial community information with industrial environmental metadata. It uses a modern web interface for easy deployment, Office Open XML Workbook (XLSX) template files for easy metadata capture, and metadata classes to ensure data consistency and type identification for follow on automated statistics and machine learning. Kroak is a functional metadata capture system which will be iteratively improved upon by Amplytica. Potential improvements include changes to Kroak’s data model, increasing the reliability of its metadata parsing and the expansion of its existing web application programming interface

Canonical queries as a query answering device (Information Science)

Issued as Annual reports [nos. 1-2], and Final report, Project no. G-36-60

A new formal and analytical process to product modeling (PPM) method and its application to the precast concrete industry

The current standard product (data) modeling process relies on the experience and subjectivity of data modelers who use their experience to eliminate redundancies and identify omissions. As a result, product modeling becomes a social activity that involves iterative review processes of committees. This study aims to develop a new, formal method for deriving product models from data collected in process models of companies within an industry sector. The theoretical goals of this study are to provide a scientific foundation to bridge the requirements collection phase and the logical modeling phase of product modeling and to formalize the derivation and normalization of a product model from the processes it supports. To achieve these goals, a new and formal method, Georgia Tech Process to Product Modeling (GTPPM), has been proposed. GTPPM consists of two modules. The first module is called the Requirements Collection and Modeling (RCM) module. It provides semantics and a mechanism to define a process model, information items used by each activity, and information flow between activities. The logic to dynamically check the consistency of information flow within a process also has been developed. The second module is called the Logical Product Modeling (LPM) module. It integrates, decomposes, and normalizes information constructs collected from a process model into a preliminary product model. Nine design patterns are defined to resolve conflicts between information constructs (ICs) and to normalize the resultant model. These two modules have been implemented as a Microsoft Visio ™ add-on. The tool has been registered and is also called GTPPM ™. The method has been tested and evaluated in the precast concrete sector of the construction industry through several GTPPM modeling efforts. By using GTPPM, a complete set of information items required for product modeling for a medium or a large industry can be collected without generalizing each company's unique process into one unified high-level model. However, the use of GTPPM is not limited to product modeling. It can be deployed in several other areas including: workflow management system or MIS (Management Information System) development software specification development business process re-engineering.Ph.D.Committee Chair: Eastman, Charles M.; Committee Co-Chair: Augenbroe, Godfried; Committee Co-Chair: Navathe, Shamkant B.; Committee Member: Hardwick, Martin; Committee Member: Sacks, Rafae

The semantic database model as a basis for an automated database design tool

Bibliography: p.257-80.The automatic database design system is a design aid for network database creation. It obtains a requirements specification from a user and generates a prototype database. This database is compatible with the Data Definition Language of DMS 1100, the database system on the Univac 1108 at the University of Cape Town. The user interface has been constructed in such a way that a computer-naive user can submit a description of his organisation to the system. Thus it constitutes a powerful database design tool, which should greatly alleviate the designer's tasks of communicating with users, and of creating an initial database definition. The requirements are formulated using the semantic database model, and semantic information in this model is incorporated into the database as integrity constraints. A relation scheme is also generated from the specification. As a result of this research, insight has been gained into the advantages and shortcomings of the semantic database model, and some principles for 'good' data models and database design methodologies have emerged