1. Requirement Analyses and a Database Model for the Project: EGERFOOD Food Safety Knowledge Center Tibor Radványi Gábor Kusper Eszterházy 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 with a 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 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 Food producers Effected authorities

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 CryptographyData redundancy

13. Eszterházy Károly CollegeA Food Safety System13 Transmission model: 3-Tire Storage

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. Eszterházy Károly CollegeA Food Safety System15 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.

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