Opasnet base structure

This page is a knowledge crystal of subtype variable. The page identifier is Op_en1913
Moderator:Jouni (see all)
Citation of this page: Juha Villman, Einari Happonen, Jouni T. Tuomisto: Opasnet Base structure. Opasnet 2010. [1]. Accessed 21 Nov 2024.
Upload data {{#opasnet_base_link:Op_en1913}}

This page is about the structure of Opasnet Base. For a general description, see Opasnet base.

Scope

Structure and connections (lines) of the tables (boxes) in the Opasnet Base. All table identifiers are called id (so they can be called by like obj.id). When obj.id is referred to in another table such as actobj, it is called actobj.obj_id. The latter end of a one-to-many relationship is marked with a ring. Important substantive fields are listed inside table boxes.

Opasnet base is a storage and retrieval system for results of variable and data from studies. What is the structure of Opasnet base such that it enables the following functionalities?

1. Storage of results of variables with uncertainties when necessary, and as multidimensional arrays when necessary.R↻
2. Automatic retrieval of results when called from Opasnet wiki or other platforms or modelling systems.
3. Description and handling of the indicess that a variable may take.
4. It is possible to protect some results and data from reading by unauthorised persons.
5. If is possible to build user interfaces for easily entering observations into the Base.

Definition

Data

Software

Because Opasnet base will contain very large amounts of mostly numerical information, the state-of-the-art structure is a SQL database. Because of its flexibility, ease of use, and cost, MySQL is an optimal choice among SQL software. In addition to the database software, a variable transfer protocol is needed on top of that so that the results of variables can be retrieved and new results stored either automatically by a calculating software, or manually by the user. Fancy presenting software can be built on top of the database, but that is not the topic of this page.

Storage and retrieval of results of variables

The most important functionality is to store and retrieve the results of variables. Because variables may take very different forms (from a single value such as natural constant to an uncertain spatio-temporal concentration field over the whole Europe), the database must be very flexible. The basic solution is described in the variable page, and it is only briefly summarised here. The result is described as

  P(R|x1,x2,...) 

where P(R) is the probability distribution of the result and x₁ and x₂ are defining locations of an index where a particular P(R) applies. Typically locations are operationalised as discrete indices. A variable must have at least one index. Uncertainty about the true value of the variable is operationalised as a random sample from the probability distribution, in such a way that the samples are located along an index Sample, which is a list of integers 1,2,3...n, where n=number of samples.

• Old description of the structure

Dependencies

• Opasnet structure
• Open assessment

Result

Opasnet base is a MySQL database located at http://base.opasnet.org.

Data structure

All data should be convertible into the following format:

			Personal measurements
Year	Sex	Age	Height	Weight
2009	Male	20	178	70
2009	Male	30	174	79
2010	Male	25	183	84
2010	Female	22	168	65

where

Name for explanation column(s).

Explanation data. These are determined or decided before the the actual observations are done.

Observation index. Common name for all observations

Name for observation column(s). These are the parameters studied.

Observation data. These are the actual measurements.

This is the "Standard data" that is entered as a Data table. The observation index is given separately in Object info and does not yet show up in the table.

Year	Sex	Age	Height	Weight
2009	Male	20	178	70
2009	Male	30	174	79
2010	Male	25	183	84
2010	Female	22	168	65

This is Object information. It slightly varies depending the format you use for uploading data.

Info_table

ident	Op_en2693
name	Testvariable
unit	#
# explanation cols	3
observation index	health impact
probabilistic?	No

This is the indexified table where all observations have been put into a single column. The next step is to replace all explanatory data text (columns 1-4) with identifiers (from the Loc table in the Opasnet Base).

Year	Sex	Age	Personal measurements	result
2009	Male	20	Height	178
2009	Male	30	Height	174
2010	Male	25	Height	183
2010	Female	22	Height	168
2009	Male	20	Weight	70
2009	Male	30	Weight	79
2010	Male	25	Weight	84
2010	Female	22	Weight	65

(The tables above have been created with File:Opasnet base explanation.ods.)

Table structure in the database

All tables

act Uploads, updates, and other actions Field Type Null Extra Key id int(10) unsigned NO auto_increment PRI acttype_id tinyint(3) unsigned NO MUL who varchar(50) NO comments varchar(250) YES time timestamp NO temp_id int(10) unsigned NO MUL	actloc Locations of an act Field Type Null Extra Key actobj_id int(10) unsigned NO PRI loc_id int(10) unsigned NO PRI	actobj Acts of an object Field Type Null Extra Key id int(10) unsigned NO auto_increment PRI act_id int(10) unsigned NO MUL obj_id int(10) unsigned NO MUL series_id int(10) unsigned NO MUL unit varchar(64) YES
acttype List of action types Field Type Null Extra Key id int(10) unsigned NO auto_increment PRI acttype varchar(250) NO UNI	cell Cells of an object Field Type Null Extra Key id int(12) unsigned NO auto_increment PRI actobj_id int(10) unsigned NO MUL mean float YES sd float NO n int(10) NO sip varchar(2000) YES	loc Location information Field Type Null Extra Key id int(10) unsigned NO auto_increment PRI std_id int(10) unsigned NO MUL obj_id_i int(10) unsigned NO MUL location varchar(100) NO roww mediumint(8) unsigned NO description varchar(150) NO
loccell Locations of a cell Field Type Null Extra Key cell_id int(10) unsigned NO PRI loc_id int(10) unsigned NO PRI	obj Object information (all objects) Field Type Null Extra Key id int(10) unsigned NO auto_increment PRI ident varchar(20) NO UNI name varchar(200) NO objtype_id tinyint(3) unsigned NO MUL page int(10) unsigned NO wiki_id tinyint(3) unsigned NO	objtype Types of objects Field Type Null Extra Key id tinyint(3) NO PRI objtype varchar(30) NO
res Result distribution (actual values) Field Type Null Extra Key id bigint(20) unsigned NO auto_increment PRI cell_id int(12) unsigned NO MUL obs int(10) unsigned NO result float NO restext varchar(250) YES implausible binary(1) YES	wiki Wiki information Field Type Null Extra Key id tinyint(3) NO PRI url varchar(255) NO wname varchar(20) NO

Contents of selected tables

Table objtype id objtype 1 Variable 2 Study 3 Method 4 Assessment 5 Class 6 Index 7 Nugget 8 Encyclopedia article 9 Run

Table acttype id acttype 1 Start object 2 Finish assessment 3 Update formula 4 Upload data (replace) 5 Upload data (append) 6 Review scope 7 Review definition 8 Add object info

Replacing some cells

It is possible that there is a large data, where there is a need to update only a few cells while all others remain the same. How should this be done? There are a few potential alternatives.

1. Use the current replace functionality. Replace all cells but most of them with the original value.
2. Use a new act_type that is similar to the current append functionality. This should be understood in a way that if there are two (or more) identical cells (based on cell indices and locations), then the newest result is used and all older ones are discarded. (If the old append is used, then new info is just seen as a new row in the data table, not a replacement of an existing row.
3. Add a new field into the cell (?) table with an updated cell_id (in a similar way than act_id and series_id are used in the actobj table). This way, the new cell can automatically inherit all locations of the old cell.

Formula structure

Now it has become clear that it is not enough to have samples of the result distributions. It must be possible to completely recalculate the result based on the information in the Opasnet Base. There are different approaches:

• Calculate the result based on a formula that may refer to other variables called parents. This is a deterministic approach.
• Calculate the result based on the marginal distribution and (conditional) rank correlations with parent variables. This is a probabilistic approach.

This approach requires new tables, namely Formula and Language.

----11: . Do we need tables DIF and DIP like Uninet? --Jouni 21:50, 30 December 2009 (UTC) (type: truth; paradigms: science: comment)

• DIP
  • DIP_node_id
  • DIP_parent_node_id
  • DIP_corr_coeff
  • DIP_parent_index
• DIF
  • DIF_node_id
  • DIF_formula
  • DIF_varnames_in_formula

Universal Opasnet Base

The idea of universal Opasnet Base says that it should be possible to store results in such a way that the results themselves are public but their interpretation is limited. For example, patient symptoms and clinical test results should be openly available for research, but information about whose results they are should be private. This can be achieved with the following database structure.

Universal Opasnet Base has some parts that exist in different versions depending on the privacy level. The yellow areas are e.g. a public area and a private area. The parts that are white are public.

Let's say that it is enough to have two security levels, public and private. A person wants to record personal health information into the database. She logs in with her personal user name. The private profile gives the name (say, Liisa) and social security number of the person, while the public profile says only "30-40-year-old woman in Finland". Liisa writes down her symptoms or medical information and saves them. This is what is stored in the databases:

Information stored in the public and private databases. The private database can read tables from the public one but not vice versa.

Table, field	Private database	Public database
act.who	Liisa, 010175-1024	Woman, 30-40 a
act.when	2011-03-09 22:09:10	2011-03
obj.name	N/A. Data is taken from public side.	Pregnancy test
loccell.loc_id (locations and indices explained)	Person = 010175-1024 Time = 2011-03-09 Test = Clearblue digital test	Age = 30-40 Sex = Female Country = Finland Time = 2011-03 Test = Clearblue digital test
res.restext	N/A. Data is taken from public side.	Pregnant 1-2 weeks.

Based on the information, anyone can see that there is a woman in Finland who has used a Clearblue pregnancy test and the result was positive. But there is no way an outsider could connect this information to any particular person, because all information that could be used for linking is located in the private website. However, an authorised person from health case could see the data in the private database and connect Liisa and the test result.

See also

• A previous discussion about the structure
• A previous structure and related discussions
• Previous tasks performed

A basic query for retrieving the full result of a variable upload (an example)

{{#sql-query: SELECT obj.ident, obj.name, obj.unit, obj.page, obj.wiki_id, comments, mean, sd, n, location, ind.ident, obs, result, restext FROM obj LEFT JOIN actobj ON actobj.obj_id = obj.id LEFT JOIN act ON actobj.act_id = act.id LEFT JOIN cell ON cell.actobj_id = actobj.id LEFT JOIN loccell ON loccell.cell_id = cell.id LEFT JOIN loc on loccell.loc_id = loc.id LEFT JOIN obj AS ind ON loc.obj_id_i = ind.id LEFT JOIN res ON res.cell_id = cell.id WHERE obj.ident = "Op_en1912" AND actobj.series_id = 190 LIMIT 0,100 }}

Some useful syntax

• http://www.baycongroup.com/sql_join.htm
• Opasnet base connection.ANA for Analytica: for writing and reading variable results into and from the database. Writing requires a password. For SQL used in the model, see the model page.
• Some historical queries
• Some historical queries 2