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Requirement Analyses and a Database Model for the Project : EGERFOOD Food Safety Knowledge Center

Requirement Analyses and a Database Model for the Project : EGERFOOD Food Safety Knowledge Center. Tibor Radványi Gábor Kusper Eszterházy Károly College. Outline. Motivation Background: Regional Knowledge Centers The EgerFood Project: Food Safety Knowledge Center

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Requirement Analyses and a Database Model for the Project : EGERFOOD Food Safety Knowledge Center

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  1. Requirement Analyses and a Database Model for the Project:EGERFOODFood Safety Knowledge Center Tibor RadványiGábor KusperEszterházy Károly College

  2. Outline • Motivation • Background: • Regional Knowledge Centers • The EgerFood Project:Food Safety Knowledge Center • R+D (Research and Development) • Requirements • a Database Model

  3. Motivation • To Build an Information System • Which is Working • Which is a Real One • Use techniques known from teaching • Compare practical and theoretical Information System Development • It is a big challenge!

  4. Background • Regional Knowledge Centers • In North-Hungary • ’05, Eszterhazy Karoly College: Food Safety • ’04, University of Miskolc: Logistics • Egerfood:Consumer focused complex food tracking systems, new food safety parameters and tools witha novel info-communication system

  5. The Consortium • Eszterhazy Karoly College + Research Lab • SzinvaNET Kft. • 1., Hesi Rt. • 2., Egri Bormímes Kft. • 3., Detki Keksz Kft. • 4., Fish and Food Kft. • 5., Quality Champignons Kft. • 6., Pásztor-Hús Kft. • Merchantmen Chamber of District Heves

  6. The analyzed products: • Egri Bikavér wine, • Detki household biscuit, • Chilled fresh strudel-sheet, • Tóth pungent sausage, • Csiperke canned mushroom, • Canned fish.

  7. 1. Task: Requirement Analyses • We have gathered information about the products and about the procedure of the production • First round: Questionnaire • Second round: Personal meetings • Some questions: • Which parameters are measured, How? • How are the products identified?

  8. Requirements • Use existing hardware • Easy to adopt • Collected data must be transferred encrypted • Be able to serve quickly and cost effectively the costumers • Be able to query old data to see the trends

  9. A consequent of the requirements • There must be a central data warehouse, which has to: • store the data, • serve the queries of the displaying modules (Web, WAP, fat clients).

  10. The Goal of the IT System Sending information in a fast, cost effective, and reliable way to the Costumers Effected authorities Food producers

  11. 2. Task: Functional Specification • At the moment we are now at stage • Done: • Data transmission model • The database model of the food tracking database • ToDo: • Select a cryptography algorithm • Develop the protocol of data transmission • Develop a product identification code system • Specify the GUIs

  12. Data Transmission Safe & Encrypted Data redundancy Cryptography

  13. Transmission model: 3-Tire Storage A Food Safety System

  14. Risk of data-loss is minimized • How we save data in the 3-Tire Storage: • The PCs at the data source save the data immediately after it is inserted. • The Buffer Servers save the data before sending it. • The Central Data Warehouse saves the data as it receives it. • This data redundancy guarantees the data safety! • We have a lots of redundant data. Therefore, we have to make an archive time to time at all the 3 levels. Therefore, we need a suitable archive making policy. This is not done yet.

  15. Question about the database • What is the best solution?: • To create a database model which can store any important data (regarding food safety) of any considered products (or possibly later introduced). OR • To make a specialized database model for each considered products and take the union of them. A Food Safety System

  16. The Pencil & Notebook solution • At 6 (out of 6) food producer companies they use pencil and notebook to store measured parameters. • They use worksheets. • Is this solution good enough? Competitors may use even ERP systems!

  17. The universal solution • It seems that the Pencil & Notebook solution is universal. • Can be used to store the measured parameters of any • Product and • Production process. • Idea: Use this universal solution, but on a computer.

  18. Data Model

  19. Companies • Company: basic information about the company, meanly to display for the users. • Products: basic product information. A company may have more products.

  20. Attributes • Attribute: describes a parameter, which is measured during the production. • Attribute_Type: the unit of the parameter, this information is needed for data conversion.

  21. Logs • Log: data of a work-period. • Log_Row: the unit of data insertion.Example: Mary Smith on 15.12.2006 in the 2nd work-period in the 10th tent harvested 3 kg of mushroom. • Row_Element: stores the elementary data. Any elementary data should have an attribute.

  22. Example • Mary Smith on 15.12.2006 in the 2nd work-period in the 10th tent harvested 3 kg of mushroom.

  23. Conclusion • We have created a robust data transformation model which minimize the risk of data-loss. • We have created a data model based on the Pencil & Notebook solution. • Advantages: • Employee can adopt easily to it. • Easier application development. • Disadvantages: • Data conversion cannot be done automatically.

  24. Thank you for your attention! Tibor Radványi dream@aries.ektf.hu Gábor Kusper gkusper@aries.ektf.hu

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