PHPGMS PHP Interface for TJGXMLCMS

TJGXMLCMS - PHPGMS

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Initial Project Plan

TJGXMLCMS

Data Translation Interface

Oct 2020

 

 

 

 

 

 

 

 

 

 

 

 

 

Introduction

TJG Web Services has developed TJGXMLCMS, a suite of tools that facilitate management of presentation and content.  The development of relational databases and NoSQL databases has created new opportunities for research design (Xu et al., 2016).  TJG Web Services embarked on the development of content management tools that integrate NoSQL databases with SQL databases.  The ability to query datasets within SQL and store the data in NoSQL provides data analysts with the ability to access data for the needs of data analysis (Berger, Berlak, & Reinhart, 2016).  The addition of XML provides the ability to store content and configuration in a business domain format.  The NoSQL datasets provide a simple data store where data exports into various programming applications for programming and analysis.  Three primary features of the interface are the ability to query SQL data, the ability to convert the results to XML format, and the ability to store the XML results in a web interface.  The SQL data can be queried in a number of SQL formats including various relational database management system engines and standard SQL (Schweinsberg & Wegner, 2016).   

Scope

The scope of this project was to develop interfaces between SQL, XML and CSV.  XML and CSV were developed for the web interface layer (Berger et al., 2016).  The interfaces are modular to be able to update to the latest specifications and suit different purposes.  The designs of the interfaces have abstracted business domain logic from presentation to support modularity.  Data management included testing of various data formats for their ease of use.  Data management also included test data formats for extracting, transforming, and loading data.  The application has an assortment of user and application interfaces for the exchanging data between layers.

Purpose

The purpose of the TJGXMLCMS was to develop functional interfaces for the exchange data between various formats: SQL, XML, and CSV (Schweinsberg & Wegner, 2016).  Three stages of TJGXMLCMS development included data management, application management, and research and design.  The stages were coordinated for incremental development of the application.

Supporting Forces

TJGXMLCMS facilitates presenting data from a number of sources.  Supporting forces include an increasing demand for data analysis tools, an increasing amount of data being stored, and an increasing variety of data formats available for data analysis (Kroon-Batenburg, Helliwell, McMahon, & Terwilliger, 2017).  Data scientists require a variety of tools that can provide ease of use and functionality for a variety of purposes.  Organizations are able to store more information with flash storage and cloud services.  More data formats are available with new database management systems.  TJGXMLCMS supports content management of emerging data management systems.

Methods

The design of the TJGXMLCMS application included an analysis of requirements from industry and research in the field to be able to gather and analyze needs  (Memon et al., 2016).  TJGXMLCMS supports facilitation of ongoing validity and reliability of the requirements with ongoing quality assurance measures.  Maintenance also includes testing the interface with new database systems.

The Nominal Group Technique (NGT) is a possible technique for identifying project requirements.  The Nominal Group Technique involves the steps of generating, recording, ranking, voting on, and prioritizing ideas (Rankin et al., 2016).  The nominal group technique ensures that all members of the group get a fair chance at presenting their ideas.  Each member of the group writes down their ideas privately and the moderator can display the ideas on a story board.  The members vote on the ideas and prioritize the ideas.  The group can take action on the ideas with the highest priority.  The Nominal Group Technique facilitates the process in software development for identifying which feature of the application to develop next.  The modularity of TJGXMLCMS allows for rapid development of new features. 

Models

The models designed for this interface include a conceptual diagram, a logical diagram, and a physical diagram.  Figures 1-3 explain the models designed in the interface.  The physical diagram also explains the query information and various style sheets for formatting the XML.

Figure 1 Logical Diagram




 

Figure 2 Logical Diagram




Figure 3 Physical Diagram


 







The XML structure for TJGXMLCMS provides for the management of text and image content in the presentation of the content management system.  The XML populates the features of the presentation layer.  The structure for the xml files for TJGXMLCMS is displayed in Figure 4:



Figure 4 TJGXMLCMS XML structure

<?xml version="1.0" encoding="UTF-8"?>

<catalog>

<heading></heading>

<headingtitle></headingtitle>

<headingdescription></headingdescription>

<links>

                <link></link>

</links>

<additionallinks>

                <link></link>

</additionallinks>

<sitelinks>

                <link></link>

</sitelinks>

<figures>

<figure>

                <title></title>

                <description></description>

                                <list>

                                                <element></element>

                                                <element></element>

                                                <element></element>

                                </list>

<figure>

                <title></title>

                <description></description>

                                <list>

                                                <element></element>

                                                <element></element>

                                                <element></element>

                                </list>

</figure>

<figure>

                <title></title>

                <description></description>

                                <list>

                                                <element></element>

                                                <element></element>

                                                <element></element>

                                </list>

</figure>

</figures>

<articles>

<article>

                <title></title>

                <section></section>

                <image></image>

</article>

</catalog>

 

 

Analytical Plan

The analytical plan provides an outline of the project.  The analytical plan includes forecasting and scenario planning for the project (Hoch, 2016).  Forecasting methods will assist in determining the success of the project by identifying trends in the demand for these tools.  Forecasting examines trends in data management, the amount of data being stored, and the types of data being stored.   Forecasting also examines the various types of DBMS available and their popularity.  Scenario planning will guide the project for different implementations for the final project such as comparing industries and sizes of organizations.  Scenario planning will also be a tool for arranging long term planning of the project.  TJGXMLCMS development employs both forecasting and scenario planning to further advance the capabilities of the application.

Anticipated Results, Conclusion, and Further Research

TJGXMLCMS development included a set of performance benchmarks that guided the efficiency of the application.  The anticipated results of the project were to provide a product that was easy to learn, adapt for a variety of situations, and modifiable to meet future requirements (Gao, Xie, & Tao, 2016).  The final product should be able to meet the demands of a competitive market and provide data scientists with a toolset, capable of meeting increasing demands of big data and data analysis.  TJG Web Services should deliver the toolset within certain constraints of the project such as cost, time, and personnel.  The final product should be low in cost, delivered within a short time frame, and requiring a small number of personnel from the organization.  The final product should meet the demands of the growing market of data science personnel.

Factors that affect the success of the project include increases in market competition, changes in application development methodologies, and the difficulty in creating a unique product that is usable and reliable (Memon et al., 2016).  The various needs of data science personnel across different industries, and different types of organizations are also potential limitations.  TJG Web Services mitigates the risks of potential limitations of TJGXMLCMS with the design of data quality assurance (Gao et al., 2016). Data quality assurance provides oversight on the design and development of the final product.  Data quality assurance also provides guidance on product development by implementing various testing strategies such as quality development.

Other societal factors that can influence the success of the product can include the internationalization of the final product and the ability to market the product to different industries and different types of organizations (Memon et al., 2016).  The product should be able to translate to different languages and should be scalable to handle datasets for large organizations that have demands in terabytes or petabytes of storage.  The storage demands should not limit the functionality of the application in speed and performance and the final product should be from errors.  The product should also provide a command line interface that allows data science personnel to perform the same actions from within the application on the command line.  The final product should also be available on a variety of operating systems. 

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References

 

Berger, C., Berlak, J., & Reinhart, G. (2016). Service-based Production Planning and Control of Cyber-Physical Production Systems.

Gao, J., Xie, C., & Tao, C. (2016). Big Data Validation and Quality Assurance--Issuses, Challenges, and Needs. Paper presented at the 2016 IEEE Symposium on Service-Oriented System Engineering (SOSE).

Hoch, C. (2016). Utopia, scenario and plan: A pragmatic integration. Planning Theory, 15(1), 6-22.

Kroon-Batenburg, L. M., Helliwell, J. R., McMahon, B., & Terwilliger, T. (2017). Raw diffraction data preservation and reuse: overview, update on practicalities and metadata requirements. IUCrJ, 4(1).

Memon, S., Riedel, M., Memon, S., Koeritz, C., Grimshaw, A., & Neukirchen, H. (2016). Enabling Scalable Data Processing and Management through Standards-based Job Execution and the Global Federated File System. Scalable Computing: Practice and Experience, 17(2), 115-128.

Rankin, N. M., McGregor, D., Butow, P. N., White, K., Phillips, J. L., Young, J. M., . . . Shaw, T. (2016). Adapting the nominal group technique for priority setting of evidence-practice gaps in implementation science. BMC medical research methodology, 16(1), 110.

Schweinsberg, K., & Wegner, L. (2016). Advantages of complex SQL types in storing XML documents. Future Generation Computer Systems.

Xu, J., Shi, M., Chen, C., Zhang, Z., Fu, J., & Liu, C. H. (2016). ZQL: A Unified Middleware Bridging Both Relational and NoSQL Databases. Paper presented at the Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech), 2016 IEEE 14th Intl C.

 

 

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