1. A short summary about Theories and Practical work
Documenting PGR
A short summary about
Theories
and
Practical work

2. How do you store your data?
In MS Excel spreadsheet?
Handwritten cards?
In a database (like MS Access)?
In you head?
In another database format?

3. What is a database?
Databases are designed to offer an organized mechanism for storing, managing and retrieving information. They do so through the use of tables. If you’re familiar with spreadsheets like Microsoft Excel, you’re probably already accustomed to storing data in tabular form. It’s not much of a stretch to make the leap from spreadsheets to databases.
The ability to link tables is a very powerful resource

4. So why not use a spreadsheet?
Databases are actually much more powerful than spreadsheets in the way you’re able to manipulate data . Just a few actions you can perform on a database:
Retrieve all records that match certain criteria
Update records in bulk
Cross-reference records in different tables
Perform complex aggregate calculations

5. What is a database? In other words:
I have data!
Me too!
In other words:
A well-organized set of interrelated data held in one or more files which are capable of being managed by a software.
Me too!
Me too!
Me also!
Me too!
Think of it like tables connected to eachother.
Instead of having one very big table You use many different tables and link them together. You create a relationship between them.
Relational databases.
Me too!

6. Step by step Analysis Design Implementation
of gene bank activities to determine information and documentation needs
Design
of the manual and/or computerized system based on documentation and information needs
Implementation
of the system that has been developed
Only a few years ago the documentation of PGR collections consisted of hand written records on cards stored in drawers. Computers have greatly increased the quantity and quality of documentation, but different gene banks tend to use different systems to organize their databases.
Implementation: get the system started, accomplish to execute the program or information system.

7. Quantitative, dealing with numbers 94 g, 34 mm, 67%
Data
Quantitative
Qualitative
Qualitative, description of the object being examined. Blue, horizontal ..
Quantitative, dealing with numbers 94 g, 34 mm, 67%
You can also store pictures, links url-addresses, maps, scanned material..

8. Name Address Telephone Filip Lund 12345 Peter Malmö 23456 Victoria
A relation can be seen as a table that stores information.
Attributes or columns
Person
Name
Address
Telephone
Filip
Lund
12345
Peter
Malmö
23456
Victoria
34567
Rows
Records

9. But every table is not an relation.
There can not exist two rows in a table that are exactly the same
Every column in the table has a unique name
There is only one value in every cell.
All values in one column belongs to the same domain or are undefined (null)

10. Redundant data Name Address Tel Course
Data in just one table repeat information…
Students taking courses in a school
Name
Address
Tel
Course
Filip
Lund
12345
Math
Peter
Malmö
23456
Victoria
34567
English
History
Göra tabell med kursare och en med kurser och koppla ihop dem.
You already know that Sven is living in Malmö with that tel. number
What if Peter wants to take a course in English?

11. C2 Math Engl C4 History C3 1 Filip Lund 12345 12 Peter Malmö 23456 123
Example: Students taking courses in a University
Person_id
Name
Adress
Tel 1
Filip
Lund
12345 12
Peter
Malmö
23456
123
Victoria
34567
Person_id
Course_id 1 C2 12 C4
123 C3
Course_id
Study C2
Math C3
Engl C4
History
Instead, store person data in a table and course data in another.
The linking table only needs the the two id that identifies the rows.
How do I store information if Peter wants to take a course in English?

12. Primary key A primary key can identify the data row It must be unique
Cant be null
Can be a ID
The easiest way is to let the program hold track of the rows and automatically increase the key.
Remember the primary key must be unique!

13. genebank_institute_name
Table of accessions, data of seedsample
accession_number
Scientific name
accession_name
genebank_institute_name
origin_country
culton_type
acqusition_date
NGB1
Triticum aestivum ssp. aestivum
IDUNA
Nordic Gene Bank
Sweden CV
NGB2
STANDARD
NGB3
JARL
NGB4
ANKAR
Denmark
NGB5
SAXO
The id’s are the primary key, because they identify the rest of the rows

14. But how store data in a good and reliable way?
Just to put everything in a file, in one big table is not a good idea.
Use a relational database (think of the db as several tables that are connected to each other)
Normalize it!
Split up information into different tables and give the record an identifier!
Save related information in one table. (For instance all personal data in a table called “person”)
Link different tables together so you can retrieve all information you need

15. Normalization
Normalization is the process of efficiently organizing data in a database. There are two goals of the normalization process:
eliminating redundant data (for example, storing the same data in more than one table) and
ensuring data dependencies make sense (only storing related data in a table). Both of these are worthy goals as they reduce the amount of space a database consumes and ensure that data is logically stored.

16. This database is poorly normalized.
In fact, it is not normalized at all. Everything is stored in one big table. Imagine how many things you have to repeat if you test the same accession three times!

17. Person id
Name
Address
Zipcode/city
countr
Title
Institute
Ins_street
Inst_City
Telephone
Cou
123
Magdalena Svärdh
Bondev 21
Lund
Swe
IT staff
Nordic Genetic Resource center
Smedjev 3
Alnarp
124
Louise Bondo
Danske vej
Farum
Den
Section leader
125
Pia Ohlsson
Blentarp
123 45
Lab
126
Johan Bäckman
Dag H. vg
Lund
IT boss
127
Jonas Nordling
S Hans gr
Lund
128
Slatan Ibrahim
Long Street
02 Copenhagen
Apple expert
Pometet LIFE Institute for Agricultural Science
Short Street
2630 Taastrup
DNK
129
Per Person
A street
123 45Malmö
swe
Seed store
130
Sven Svensson
B street
131
Karl Krlssn
C street
Information about the institute where people work is repeated several times!
Imagine how boring it will be to add the same information for all staff members in NordGen!

18. Person Institutes Much better!id
Name
Address
Zipcode/city
countr
Title
Inst_id
123
Magdalena Svärdh
Bondev 21
Lund
Swe
IT staff 45
124
Louise Bondo
Danske vej
Farum
Den
Section leader
125
Pia Ohlsson
Blentarp
123 45
Lab
126
Johan Bäckman
Dag H. vg
Lund
IT boss
127
Jonas Nordling
S Hans gr
Lund
128
Slatan Ibrahim
Long Street
02 Copenhagen
Apple expert 46
129
Per Person
A street
123 45Malmö
swe
Seed store
130
Sven Svensson
B street
131
Karl Krlssn
C street
Much better!
If the Institute changes telephone number you just have to change it once!
Institutes
Inst_id
Institute
Ins_street
Inst_City
Telephone
Cou 45
Nordic Genetic Resource center
Smedjev 3
Alnarp
Swe 46
Pometet LIFE Institute for Agricultural Science
Short Street
2630 Taastrup
DNK

19. Relational Database Managers
By linking files or information together, a relationship is produced between the tables.
The shared field is only stored once, it is not duplicated in each file

20. You often visualize a table like this:
person id
name
address
zipcode/city
countr
title
inst_id
123
Magdalena Svärdh
Bondev 21
Lund
Swe
IT staff 45
124
Louise Bondo
Danske vej
Farum
Den
Section leader
125
Pia Ohlsson
Blentarp
123 45
Lab
126
Johan Bäckman
Dag H. vg
Lund
IT boss
127
Jonas Nordling
S Hans gr
Lund
128
Slatan Ibrahim
Long Street
02 Copenhagen
Apple expert 46
129
Per Person
A street
123 45Malmö
swe
Seed store
130
Sven Svensson
B street
131
Karl Krlssn
C street
person id
name
adress
zipcode/city
country
title
inst_id

21. another example… Seed info
Fields which have a logical relation to each other and to the identifying field, should be grouped together in a relation.
Seed info
Accession_id
Accession name
Species
Date of acquisition
DonorInstituteName
Street Address
City Address
Other fields…
This is not a good example!
If the gene bank receives another accession at a later date , the entire address would need to be entered again in a different record. It would be better to store information about the donors in a separate table.

22. … this would be better Donor Seed info AccDon_id Accession_id
Accession name
Species
Date of acquisition
Amount of seeds
AccDon_id
Other fields…
AccDon_id
donPer_id
donInst_id
donAccname
Don_info
Information about the donated material, from which institute, person who donated it, what the accession has been called in the donating institute and other information about the donated material

23. …yet another example Registration Passport Storage Accession name
Scientific name
Original country
Other fields…
Accession name
Collecting institute
Collector
Date of collection
Other fields…
Accession name
Freezer_number
Box_number
Storage_date
Other fields…
You might have the following separate files for a particular crop:
Here the Accession name is the same in all for the plants or seeds.
What happens if you have to change the name? You have to change it in all three otherwise data will be lost.
The best thing is to store a link to the accession and store all the information about the accession elsewhere.
What happens if you have to change the name? You have to change it in all three otherwise data will be lost.
The best thing is to store a link to the accession and store all the information about the accession elsewhere.

24. Accession Passport Storage Accession_id Accession name Scientific name
Original country
Other fields…
Accession_id
Collecting institute
Collector
Date of collection
Other fields…
Accession_id
Freezer_number
Box_number
Storage_date
Other fields…
What happens if you have to change the name? You have to change it in all three otherwise data will be lost.
The best thing is to store a link to the accession and store all the information about the accession elsewhere.
If you misspelled the accession name, you just have to change it once

25. Visualized in a ER-model (Entity-Relationship model) it looks like this:
Seed sending info
Gene Bank
1:N
Our institute (Gene Bank) can receive many seeds (with seed sending information)

26. One species can have many accessions.
Visualized in a ER-model (Entity-Relationship model) it looks like this:
species
accessions 1 * 1
teacher
0..5
students
One species can have many accessions.
One accession belongs to just one species
One teacher can have up to five students to teach

27. Different categories for data modeling
Object oriented model
Relational model
Objekt orienterad with inheritance. Klassen bil ärver bilmärke, antal dörrar osv. Klassen bil har allt som alla bilar har. Dvs som är gemensamt med alla bilar.
Relationsmodellen kopplar tabeller till relationer för att undvika att data lagras på onödigt många ställen och i flera tabeller. Ex studenter tar kurser på olika universitet.
Andra data modeller finns som nätverk och excelblad…

28. Data modeling- how to get started
To start – find the object
Let the object become a relation
Each object or relation should have its own information and descriptive attributes
The object becomes the table, the attributes columns and the identifying attribute becomes the primary key
An object could be
Persons
Places
Objects (like Accessions, institutes…)
Events (like seed drying, germination tests..)
Things you want to store information about

29. Data modeling
A data model makes it easier to understand the meaning of the data
A common and popular data model used in database design is based on the concepts of the Entity – Relationship (ER) model
Conceptual
logical structure on databases. Designed by experts, information users, those who know and are familiar with the information. Identification of important entity and relationship types
Physical structure
designed by experts, database developers. How the logical structure is to be physically implemented (as tables) on the target DBMS
Conceptual: The person who knows where to put where, which information goes with what and how to organize the data.
Important with the teamwork

30. Data modeling:
Should represent reality and the information that need to be stored
Help us to visualize our task and clarify rules and restrictions and relations between objects
Gives the staff a chance to participate early in the development
Is a established way of developing information systems
Is a way to document and explain the IT-system

31. Accession and collecting information
Start to gather related information into tables and link them together
Accession number
Scientific name
Pedigree name
Donor name
Acquisition name
And more…
Collecting organization
Collecting date
Country of collection
And more…
You could have everything in one file or table, but this will be a large and slow system to work with.
Better is to organise related information in different tables.

32. A model of accession descriptors and collecting descriptors:
Accession_id
Accession name
Scientific name
Cultivar name
Donor
Acquisition date
More…
Accession_id
Collection organization
Collecting date
Country of collecting
Province/state
Location of collecting site
Type of sample…
The accession relation gather all the information about the accession.
The collecting relation describe all the information about the specific collecting event

33. Example of relations Collect collect_id accession_id person_id
latitude
longitude
site_name
country_id 1
Accession
accession_id
taxon_id
accession_name
country_id
acc_mandate 1
Taxon
taxon_id
sci_name
eng_name
mandate
grin_no
thgw 1 1 N
Seedstore
batch_id
accession_id
batch_no
collection
box_no
harvest_year N 1
germin_test
test_id
accession_id
batch_id
grm_pct
test_date
person_id N N

34. Wow
Instead of repeating a lot of information, You store the accession once and link to other tables with other information!
By linking files or information together, a relationship is produced between the tables.
Smart!
And effective!

35. Part 2
Maybe a short brake?

36. DBMS A software system that enables users to define, create, maintain and control access to the database.
The DBMS is the software that interacts with the users’ application programs and the database.
Typically a DBMS provides the following facilities…
Data base management system

37. It provides controlled access to the database.
It allows users to define the database with types and structures and the constraints on the data to be stored in the database. (DDL)
It allows users to insert, update, delete and retrieve data from the database. (DML)
It provides controlled access to the database.
DDL= data definition language
DML= data manipuation language
Controlled access, security system, integrity system, concurrency system, recovery system if server failure.
Concurrency så fler kan använda databasen.

38. Example of DML and DDL Data manipulating language (DML)
Select * from Person;
Insert into Person (Name, Address, tel) values (‘John Book’, ‘California’, )
Data Definition language (DDL) (Changes in structure)
Create table Person (
Name varchar(40) NotNull,
Address char(10),
tel int)

39. DBMS environment Data Procedures People Hardware Software Bridge Human
Machine

40. Users with software and questions
Web site, For instance SESTO. Question: List all accessions
User1
User2
DBMS
Interpretation of question
Data base language (SQL)
DDL & DML
All communication goes by the DBMS
Data bases with information and meta data

41. Features in SESTO e.g. project archive and pictures archive
Entry levels with seed store data: Genus, Taxons, Cultivars and Accessions.
To list all Taxons in your gene bank, click the button and information about the taxons and their accessions will be presented.
The SADC entrance

42. To see the accession list of this taxon (Arachis hypogaea) click the [select]-link

43. To see detailed information about this accession click [select]

44. The accession name SWZ1 from Zea mays gives this information
To see all the information from stored material click this link

45. To edit accession information and storage information, click the [edit] links and a pop up window will be presented
Two batches with 10 distribution bags are stored in the Active Storage in freezer 15 in boxes 10 and 8.

46. To add and edit information about an accession.
The information goes to the database and will be stored there

47. A documentation system should be…
Reliable
Retrieve information fast
User-friendly
Flexible, should anticipate changes

48. Things you will not regret!
Be organized and structured from the start!
Be sure you have a good data model Spend some time on normalization, it will be worth it later
Try to cooperate and work together with the documentation working group
(Documentation is far to important to be left alone with the IT-staff)

49. Have you heard about the new dataset…
Web services
Web services are standardized programs that send your data to databases automatically.
Your data will be published elsewhere
This makes your work recognized
And will give your gene bank credit and your material will be asked for
GBIF, Biocase
The Biological Collection Access Service for Europe, BioCASE
the Global Biodiversity Information Facility is a mega-science project with the aim "to make the world's primary data on biodiversity freely and universally available via the Internet" (
Have you heard about the new dataset…

50. Last but not least… Data is not information.
Information must be retrieved and understood.
Then knowledge is created.
"Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in information?"
T.S.Eliot
(Where is the information we have lost in data?)

51. Thank you for listening!