Supervisor:Dr. Rania El-GoharyDr. Ibrahaim fathy

Team Leader: Jihen Amara

Members:Kareem Soliman Ahmed El-Sayed

Rana AbdelhaleemYoussef EssamSara Roushdy

Eslam ShaabanAhmed Adel

The seasonal fluctations of tomato insect pests on two cultivars during

two seasons

Agenda ● Problem definit ion

● Project Object ives

● Data Planning

● Data Collect ion

● Data Quality

● Data Descript ion

• Data Integrat ion

• Developed Ontology

• Data Analysis - Correlat ion

• Correlat ion Visualizat ion

• Conclusion

• Recommendations for Future work

Problem Definition

Project Objectives & Aims● Ident ifying based on the fluctuat ions the opt imum cult ivars that has the least

numbers of insects pests

● Collaborat ion between Biodiversity Students and Computer Science Students

● Following the Data Management Life cycle steps

● Applicat ion of the covered materials of the Summer School

Data Life Cycle

● The data life cycle consists of eight main phases

● All phases were accomplished throughout the project

Data Planning

● What Data will be Produced?

● How will the Data be Documented and Described?

● What are the plans for data sharing and access after submission of the thesis?

● What are the plans for long-term archiving of the digital data supporting the thesis?

Data collection Methodology

● Tomato seedlings were sown on 4 April, 2012 and 23 March, 2013.

● The different stages of the previously mentioned insect pests were counted weekly on 60 tomato leaflets.

● Counts were recorded weekly during the period from 8 May to 10 July, 2013 and during 23 April to 2 July, 2013

Data Quality - Assurance

● Four steps of Data Quality

● The six Key Data quality Dimensions

● Data Quality Rules : Validity and Completeness are fulfilled within the data after its pre-processing which achieved the data Assurance.

Data Quality - Steps

Data Profiling Data Quality Rules Resolve DQ Issues Monitor and Control

Data Profiling- Step 1

Data Profiling- Step 1

Data Profiling- Step 1

Data Profiling- Step 1

Data Quality - Steps

Data Profiling Data Quality Rules Resolve DQ Issues Monitor and

Control

Data Quality Rules- Step 2

Accuracy Validity Timeliness

ConsistencyUniquenessCompleteness

Data Quality - Steps

Data Profiling Data Quality Rules

Resolve DQ Issues

Monitor and Control

Resolving DQ issues- Step 3

Accuracy Validity Timeliness

ConsistencyUniquenessCompleteness

Re-formated Lang & Sep.

Date

Put average

Data Quality - Steps

Data Profiling Data Quality Rules

Resolve DQ Issues

Monitor and Control

Data Description

● Data is represented in two separate excel spreadsheets consists of the reading of the fluctuations

● Fluctuations are taken weekly for each of the four kinds of insects pests ( B. tabaci, Aphids, E. decipiens, Tuta absoluta ) on leaflets of 2 types of tomatoes ( hybrid super and crystal HYB )

● The data itself is the actual number of insect pests on the leaflets collected by human observation.

Data of summer 2012

Data of summer 2013

Data Integration

Data Integration

Semantic Data Integration (Ontology)

Semantic Data Integration (Ontology)

Semantic Data Integration (Ontology)

Data Analysis - Correlation2012

T1

Data Analysis - Correlation2012

T2

Data Analysis - Correlation2013

T1

Data Analysis - Correlation2013

T2

Correlation Visualization

Conclusion

● Cultivar 2 has less insect infection therefore it is more defensive Therefore it is more recommended to be cultivated than cultivar 1

● There is a correlation between the increase of the B. tabaci and aphids pests

● A good opportunity for colllaboration between biodiversity and computer science students

Recommendations for Future work ● Focus on the insects enter relationships and climate change

● Focus on the correlation between the date of planting and the number of pests

● More studies has to be conducted to predict any epidemic occurrences

● The effect of the increasing of the B. tabaci and Aphids on the actual crop production

Thank You