Opasnet base structure: Difference between revisions

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[[Category:Open assessment]]
[[Category:Open assessment]]
[[Category:Tool]]
[[Category:Tool]]
{{variable}}
{{variable|moderator = Jouni
| reference = {{publication
| authors        = Juha Villman, Einari Happonen, Jouni T. Tuomisto
| page          = Opasnet Base structure
| explanation    =
| publishingyear = 2010
| urn            =
| elsewhere      =
}}
}}


==Scope==
:''This page is about the '''old structure of Opasnet Base''' used in ca. 2008-2011. For a description about the current database, see [[Opasnet base 2]].


'''Opasnet base''' is a storage and retrieval system for [[variable]] [[result]]s and [[nugget]] [[data]]. What is the structure of [[Opasnet base]] such that it enables the following functionalities?
==Question==
 
[[image:Opasnet Base structure.png|thumb|400px|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 [[result]]s of [[variable]] and [[data]] from [[study|studies]]. What is the structure of [[Opasnet Base]] such that it enables the following functionalities?
# Storage of results of variables with uncertainties when necessary, and as multidimensional arrays when necessary.{{reslink|Should all variables go to result distribution database?}}
# Storage of results of variables with uncertainties when necessary, and as multidimensional arrays when necessary.{{reslink|Should all variables go to result distribution database?}}
# Automatic retrieval of results when called from [[Opasnet wiki]] or other platforms or modelling systems.
# Automatic retrieval of results when called from [[Opasnet wiki]] or other platforms or modelling systems.
# Description and handling of the [[dimension]]s that a [[variable]] may take.
# Description and handling of the [[index|indices]]s that a [[variable]] may take.
# It is possible to protect some results and data from reading by unauthorised persons.
# It is possible to protect some results and data from reading by unauthorised persons.
# If is possible to build user interfaces for easily entering observations into the Base.
# If is possible to build user interfaces for easily entering observations into the Base.


==Answer==


==Definition==
Opasnet base is a [[:en:MySQL|MySQL]] database located at http://base.opasnet.org.


===Data===
===Data structure===


====Software====
:''Main article: '''[[Data structures in Opasnet]]'''''


Because Opasnet base will contain very large amounts of mostly numerical information, the state-of-the-art structure is a [[:en:SQL|SQL]] database. Because of its flexibility, ease of use, and cost, [[:en:MySQL|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.
All data should be convertible into the following format:


====Storage and retrieval of results of variables====
{| {{prettytable}}
! colspan="3"| || colspan="3"  style="background-color: #FFD8F0;"|Observation
|-----
!  style="background-color: #CCDFC8;"|Year ||  style="background-color: #CCDFC8;"|Sex ||  style="background-color: #CCDFC8;"|Age ||  style="background-color: #DFB8D0;"|Height ||  style="background-color: #DFB8D0;"|Weight ||  style="background-color: #DFB8D0;"|Description
|-----
|  style="background-color: #ECFFE8;"|2009 ||  style="background-color: #ECFFE8;"|Male ||  style="background-color: #ECFFE8;"|20 ||  style="background-color: #ECDFE8;"|178 ||  style="background-color: #ECDFE8;"|70 ||  style="background-color: #ECDFE8;"|An optional column for descriptive text about each row.
|-----
|  style="background-color: #ECFFE8;"|2009 ||  style="background-color: #ECFFE8;"|Male ||  style="background-color: #ECFFE8;"|30 ||  style="background-color: #ECDFE8;"|174 ||  style="background-color: #ECDFE8;"|79 ||  style="background-color: #ECDFE8;"|
|-----
|  style="background-color: #ECFFE8;"|2010 ||  style="background-color: #ECFFE8;"|Male ||  style="background-color: #ECFFE8;"|25 ||  style="background-color: #ECDFE8;"|183 ||  style="background-color: #ECDFE8;"|84 ||  style="background-color: #ECDFE8;"|
|-----
|  style="background-color: #ECFFE8;"|2010 ||  style="background-color: #ECFFE8;"|Female ||  style="background-color: #ECFFE8;"|22 ||  style="background-color: #ECDFE8;"|168 ||  style="background-color: #ECDFE8;"|65 ||  style="background-color: #ECDFE8;"|
|}


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
where


  P(R|x<sub>1</sub>,x<sub>2</sub>,...)
{| {{prettytable}}
|  style="background-color: #CCDFC8;"|Names of explanation columns, also known as indices.
|-----
|  style="background-color: #ECFFE8;"|Explanation data, also known as locations. You can use these columns as search criteria.
|-----
|  style="background-color: #FFD8F0;"|Observation index, typically called "Observation". Common name for all observation columns
|-----
|  style="background-color: #DFB8D0;"|Names of observation columns. These are the parameters of interest.
|-----
|  style="background-color: #ECDFE8;"|Observation data. These are the actual measurements.
|-----
|}


where P(R) is the probability distribution of the result and x<sub>1</sub> and x<sub>2</sub> are defining [[location]]s of a [[dimension]] where a particular P(R) applies. Typically locations are operationalised as discrete [[Index|indices]]. A variable must have at least one dimension. [[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.
===Table structure in the database===


 
==== All tables ====
* [http://en.opasnet.org/en-opwiki/index.php?title=Opasnet_base&oldid=7856 Old description of the structure]
 
===Dependencies===
 
* [[Opasnet structure]]
* [[Open assessment]]
 
==Result==
 
Opasnet base is a [[:en:MySQL|MySQL]] database located at http://base.opasnet.org.
 
===Table structure===
 
* We need '''Ressec''' (Result secure) and '''Resinfosec''' (Result info secure) tables for secure information. All other tables are openly readable except these two. They have the same structure as Res and Resinfo tables, respectively.


{| VALIGN="top" BORDER="0"
{| VALIGN="top" BORDER="0"
|-
|-
|
|VALIGN="top"|
{| WIDTH="250px" {{prettytable}}
{| {{prettytable}}
|----
|colspan=5|'''act'''
|COLSPAN="3"|'''Obj'''
|-
|colspan=5|'''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||||
|-
|-
|COLSPAN="3"|''Describes all objects''
|time||timestamp||NO||||
|----
| '''FIELD'''
| '''TYPE'''
| '''EXTRA'''
|----
| id
| int(10)
| primary
|----
| Ident
| varchar(20)
| unique
|----
| Name
| varchar(200)
|
|----
| Unit
| varchar(16)
|
|----
| Objtype_id
| tinyint(3)
|
|----
| Page
| int(10)
|
|-
|-
| Wiki_id
|temp_id||int(10) unsigned||NO||||MUL
| tinyint(3)
|  
|----
|}
|}
|VALIGN="top"|
|VALIGN="top"|
{| WIDTH="250px" {{prettytable}}
{| {{prettytable}}
|COLSPAN="3"|'''Cell''' (previously Res)
|colspan=5|'''actloc'''
|-
|colspan=5|'''Locations of an act'''
|-
|Field||Type||Null||Extra||Key
|-
|-
|COLSPAN="3"|''Cells of an object''
|actobj_id||int(10) unsigned||NO||||PRI
|-
|-
| '''FIELD'''
|loc_id||int(10) unsigned||NO||||PRI
| '''TYPE'''
| '''EXTRA'''
|----
| id
| int(12)
| primary
|----
| Obj_id_v (variable id)
| int(10)
|
|----
| Obj_id_r (run id)
| int(10)
|  
|----
| Mean (mean of the cell)
| float
|  
|----
| N (samplesize)
| int(10)
|  
|----
|}
|}
|VALIGN="top"|
|VALIGN="top"|
{| WIDTH="250px" {{prettytable}}
{| {{prettytable}}
|COLSPAN="3"|'''Loc'''
|colspan=5|'''actobj'''
|-
|colspan=5|'''Acts of an object'''
|-
|-
|COLSPAN="3"|''Location information''
|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||||
|}
 
|-
|-
| '''FIELD'''
| '''TYPE'''
| '''EXTRA'''
|----
| id
| int(10)
| primary
|----
| Obj_id_i (index id)
| int(10)
|
|----
| Location
| varchar(1000)
|
|----
| Roww (row # of index)
| Mediumint(8)
|
|
|----
{| {{prettytable}}
| Description
|colspan=5|'''acttype'''
| varchar(150)
|-
|  
|colspan=5|'''List of action types'''
|----
|}
|-
|-
|VALIGN="top"|
|Field||Type||Null||Extra||Key
{| WIDTH="250px" {{prettytable}}
|COLSPAN="3"|'''Item'''
|-
|-
|COLSPAN="3"|''Items of a set''
|id||int(10) unsigned||NO||auto_increment||PRI
|-
|-
| '''FIELD'''
|acttype||varchar(250)||NO||||UNI
| '''TYPE'''
| '''EXTRA'''
|----
| id
| int(10)
| primary
|----
| Sett_id (set to which the item belongs)
| int(10)
|  
|----
| Obj_id (item id)
| int(10)
|
|----
| Fail (membership not valid?)
| tinyint(1)
|  
|----
|}
|}
|VALIGN="top"|
|VALIGN="top"|
{| WIDTH="250px" {{prettytable}}
{| {{prettytable}}
|COLSPAN="3"|'''Loccell''' (previously Locres)
|colspan=5|'''cell'''
|-
|-
|COLSPAN="3"|''Locations of a cell''
|colspan=5|'''Cells of an object'''
|-
|-
| '''FIELD'''
|Field||Type||Null||Extra||Key
| '''TYPE'''
|-
| '''EXTRA'''
|id||int(12) unsigned||NO||auto_increment||PRI
|----
|-
| id
|actobj_id||int(10) unsigned||NO||||MUL
| int(10)
|-
| primary
|mean||float||YES||||
|----
|-
| Cell_id
|sd||float||NO||||
| int(10)
|-
|  
|n||int(10)||NO||||
|----
|-
| Loc_id
|sip||varchar(2000)||YES||||
| int(10)
|  
|----
|}
|}
|VALIGN="top"|
|VALIGN="top"|
{| WIDTH="250px" {{prettytable}}
{| {{prettytable}}
|COLSPAN="3"|'''Res''' (previously Sam)
|colspan=5|'''loc'''
|-
|colspan=5|'''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
|-
|-
|COLSPAN="3"|''Result distribution (actual values)''
|location||varchar(100)||NO||||
|-
|-
| '''FIELD'''
|roww||mediumint(8) unsigned||NO||||
| '''TYPE'''
|-
| '''EXTRA'''
|description||varchar(150)||NO||||
|----
| id
| bigint(20)
| primary
|----
| Cell_id
| int(12)
|
|----
| Obs (previously Sample)
| int(10)
|  
|----
| Result
| float
|  
|----
|}
|}
|-
|
{| {{prettytable}}
|colspan=5|'''loccell'''
|-
|colspan=5|'''Locations of a cell'''
|-
|-
|VALIGN="top"|
|Field||Type||Null||Extra||Key
{| WIDTH="250px" {{prettytable}}
|COLSPAN="3"|'''Sett'''
|-
|-
|COLSPAN="3"|''List of sets''
|cell_id||int(10) unsigned||NO||||PRI
|-
|-
| '''FIELD'''
|loc_id||int(10) unsigned||NO||||PRI
| '''TYPE'''
| '''EXTRA'''
|----
| id
| int(10)
| primary
|----
| Obj_id
| int(10)
|
|----
| Settype_id
| tinyint(3)
|  
|----
|}
|}
|VALIGN="top"|
|VALIGN="top"|
{| WIDTH="250px" {{prettytable}}
{| {{prettytable}}
|COLSPAN="3"|'''Settype''' (previously Sty)
|colspan=5|'''obj'''
|-
|colspan=5|'''Object information (all objects)'''
|-
|Field||Type||Null||Extra||Key
|-
|id||int(10) unsigned||NO||auto_increment||PRI
|-
|-
|COLSPAN="3"|''Types of set-item memberships''
|ident||varchar(20)||NO||||UNI
|-
|-
| '''FIELD'''
|name||varchar(200)||NO||||
| '''TYPE'''
|-
| '''EXTRA'''
|objtype_id||tinyint(3) unsigned||NO||||MUL
|----
|-
| id
|page||int(10) unsigned||NO||||
| tinyint(3)
|-
|  
|wiki_id||tinyint(3) unsigned||NO||||
|----
| Settype (previously Stype)
| varchar(30)
|  
|----
|}
|}
|VALIGN="top"|
|VALIGN="top"|
{| WIDTH="250px" {{prettytable}}
{| {{prettytable}}
|COLSPAN="3"|'''Objtype''' (previously Typ)
|colspan=5|'''objtype'''
|-
|colspan=5|'''Types of objects'''
|-
|Field||Type||Null||Extra||Key
|-
|-
|COLSPAN="3"|''Types of objects''
|id||tinyint(3)||NO||||PRI
|-
|-
| '''FIELD'''
|objtype||varchar(30)||NO||||
| '''TYPE'''
| '''EXTRA'''
|----
| id
| tinyint(3)
| primary
|----
| Objtype (previously Type)
| varchar(30)
|  
|----
|}
|}
|-
|-
|
{| {{prettytable}}
|colspan=5|'''res'''
|-
|colspan=5|'''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||||
|}
|VALIGN="top"|
|VALIGN="top"|
{| WIDTH="250px" {{prettytable}}
{| {{prettytable}}
|COLSPAN="3"|'''Wiki''' (previously Wik)
|colspan=5|'''wiki'''
|-
|colspan=5|'''Wiki information'''
|-
|Field||Type||Null||Extra||Key
|-
|id||tinyint(3)||NO||||PRI
|-
|-
|COLSPAN="3"|''Wiki information''
|url||varchar(255)||NO||||
|-
|-
| '''FIELD'''
|wname||varchar(20)||NO||||
| '''TYPE'''
|}
| '''EXTRA'''
|}
 
====Contents of selected tables====
 
{|
|
{| {{prettytable}}
|+ Table objtype
! id!! objtype
|----
|| 1|| Variable
|----
|| 2|| Study
|----
|| 3|| Method
|----
|| 4|| Assessment
|----
|----
| id
|| 5|| Class
| tinyint(3)
| primary
|----
|----
| Url
|| 6|| Index
| varchar(255)
|  
|----
|----
| Wname
|| 7|| Nugget
| varchar(20)
|
|}
|VALIGN="top"|
{| WIDTH="250px" {{prettytable}}
|COLSPAN="3"|'''Resinfo''' (previously Descr)
|-
|COLSPAN="3"|''Additional description of the result''
|-
| '''FIELD'''
| '''TYPE'''
| '''EXTRA'''
|----
|----
| id
|| 8|| Encyclopedia article
| bigint(20)
| primary
|----
|----
| Restext (previously Description)
|| 9|| Run
| varchar(250)
|  
|----
|----
| Who
|}
| varchar(50)
 
|
|
{| {{prettytable}}
|+ Table acttype
! id|| acttype
|----
|----
| When
|| 1|| Start object
| timestamp
|----
|
|| 2|| Finish assessment
|}
|----
|VALIGN="top"|
|| 3|| Update formula
{| WIDTH="250px" {{prettytable}}
|COLSPAN="3"|'''Objinfo''' (previously Inf)
|-
|COLSPAN="3"|''Additional information about the object''
|-
| '''FIELD'''
| '''TYPE'''
| '''EXTRA'''
|----
|----
| id
|| 4|| Upload data (replace)
| int(10)
| primary
|----
|----
| Begin
|| 5|| Upload data (append)
| date
|  
|----
|----
| End
|| 6|| Review scope
| date
|  
|----
|----
| Who
|| 7|| Review definition
| varchar(50)
|  
|----
|----
| Url
|| 8|| Add object info
| varchar(250)
|  
|----
|----
|}
|}
|}
|}


==See also==
==Rationale==
 
===Data===
 
====Software====
 
Because Opasnet base will contain very large amounts of mostly numerical information, the state-of-the-art structure is a [[:en:SQL|SQL]] database. Because of its flexibility, ease of use, and cost, [[:en:MySQL|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|x<sub>1</sub>,x<sub>2</sub>,...)
 
where P(R) is the probability distribution of the result and x<sub>1</sub> and x<sub>2</sub> are defining [[location]]s of an [[index]] where a particular P(R) applies. Typically locations are operationalised as discrete [[Index|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.


These texts could be moved to separate pages.


===Opasnet Data===
* [http://en.opasnet.org/en-opwiki/index.php?title=Opasnet_base&oldid=7856 Old description of the structure]


'''Opasnet Data''' is a database that is designed to collect observation data from [[study|studies]]. A study can be a traditional research study, which is documented in Opasnet Data afterwards, or it can be an Opasnet study where the data is collected on a particular page of Opasnet using a web form. There are several purposes:
===Dependencies===
* To collect observation data to be directly usable in interpretations of [[variable]]s and other [[object]]s.
* To collectively collect information about specific cases, and based on these data conditionalise a generalised assessment model with data specific to a particular case.


The structure of the Opasnet Data is the same as that of Opasnet Base. Actually, they are physically in the same database. However, there are some things that should be understood:
* [[Opasnet structure]]
* The object for a collection of observations is called a [[study]], while the object of interpretations is called a [[variable]]. As an example, a study can collect information about a population group by a questionnaire and by taking a blood sample. The study identifier is the Obj.id in the Opasnet Base.
* [[Open assessment]]
* The object may be divided into smaller pieces along one or more [[index|indices]]. For example, the questionnaire may have 30 questions, and therefore the questionnaire data can be indexed by an index with 30 columns (or rows, depending on which way you think), one row for each question. Each column of the study object has one cell, i.e. an answer to one question. In this study, ten blood markers will be studied, and therefore the study object will have 40 cells, and the index 40 columns (30 from the questionnaire, 10 from the blood sample). The cell identifier is the Res.id in the Opasnet Base.
* For each individual patient, there is one row of observations, each 40 cells. The observation row identifier is Sam.Sample in Opasnet Base.
* The actual result of a particular cell of a particular patient is located in Sam.Result in Opasnet Base (or in Descr.Description in the case where the result is text, i.e. non-numeric).
* Each study may be multidimensional just like a variable and have indices along e.g. space, time, or sex.
* If the data is collected using an Opasnet web form, then the timestamp and username or IP will be recorded for each entry into Descr.When and Descr.Who fields, respectively. This is not needed, if the data comes from a previously performed study (which is static data in the eyes of Opasnet).
* In some cases, it  might be useful to restrict the number of entries per user to one. However, this is done only at the interpretation phase where only the last entry is counted. There are no restrictions to enter new data, and therefore a user may change his/her previous entry by simply making a new entry.


===Making value-of-information analyses in [[Opasnet base]]===
====Replacing some cells====


[[:en:Value of information|Value of information]] (VOI) is a [[:en:decision analysis|decision analysis]] tool for estimating the importance of remaining uncertainty for decision-making. Result database can be used to perform a large number of VOI analyses, because all variables are in the right format for that: as random samples from uncertain variables. The analysis is done by optimising an [[indicator]] variable by adjusting a [[decision variable]] so that the variable under analysis is conditionalised to different values. All this can in theory be done in the result database by just listing the indicator, the decision variable, and the variable of interest. Practical tools should be developed for this. After that, systematic VOI analyses can be made over a wide range of environmental health issues.
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.
# Use the current replace functionality. Replace all cells but most of them with the original value.
# 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.
# 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.


===Analysing the change in the quality of a variable result in [[Opasnet base]]===
===Formula structure===


All results that have once been stored in the result database remain there. Old results can be very interesting for some purposes:
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:
* The time trend of [[informativeness]] and [[calibration]] (see [[performance]]) can be evaluated for a single variable against the newest information.
* Calculate the result based on a formula that may refer to other variables called parents. This is a deterministic approach.
* Critical pieces of information that had a major impact on the informativeness and calibration can be identified afterwards.
* Calculate the result based on the marginal distribution and (conditional) rank correlations with parent variables. This is a probabilistic approach.
* Large number of variables can be assessed and e.g. following questions can be asked:
** How much work is needed to make a variable with reasonable performance for practical applications?
** What are the critical steps after which the variable performance is saturated, i.e., does not improve much despite additional effort?


===Some useful syntax===
This approach requires new tables, namely Formula and Language.


* http://www.baycongroup.com/sql_join.htm
* [[:image:Opasnet base connection.ANA|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.
* [http://en.opasnet.org/en-opwiki/index.php?title=Opasnet_base&oldid=7181#Other_queries Some historical queries]


: {{comment|11|Do we need tables DIF and DIP like Uninet?|--[[User:Jouni|Jouni]] 21:50, 30 December 2009 (UTC)}}
* DIP
** DIP_node_id
** DIP_parent_node_id
** DIP_corr_coeff
** DIP_parent_index
* DIF
** DIF_node_id
** DIF_formula
** DIF_varnames_in_formula


{{#sql-query:
===Universal Opasnet Base===
SELECT Var.Ident, Var.Name, Var.Unit, Run.Ident, Begin, Who, Run.Name as Method
FROM Obj as Var, Obj as Run, Cell, Objinfo
WHERE Var.Ident = "Op_en{{PAGEID}}"
AND Var.id = Cell.Obj_id_v
AND Run.id = Cell.Obj_id_r
AND Run.id = Objinfo.id
GROUP BY Var.id, Run.id
|Runs}}


{{#sql-query:
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.
SELECT Var.Ident, Var.Name, Cell.id, N, Begin, Mean, Var.Unit
FROM Obj as Var, Obj as Run, Cell, Objinfo
WHERE Var.Ident = "Op_en{{PAGEID}}"
AND Var.id = Cell.Obj_id_v
AND Run.id = Cell.Obj_id_r
AND Run.id = Objinfo.id
GROUP BY Cell.id
ORDER BY Run.id DESC, Var.Ident
|Means and samplesizes (N)}}
{{#sql-query:
SELECT Var.Ident, Cell.id, Cell.Obj_id_r as Run, Obs, Result, Var.Unit
FROM Obj as Var, Cell, Res
WHERE Var.Ident = "Op_en{{PAGEID}}"
AND Var.id = Cell.Obj_id_v
AND Cell.id = Res.Cell_id
ORDER BY Cell.Obj_id_r, Var.Ident, Cell.id
|Full sample}}


[[File:Universal Opasnet Base structure.png|thumb|400px|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.]]


'''List all dimensions that have indices, and the indices concatenated:
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:


<sql-query display="1">
{| {{prettytable}}
Select Dim_name, dim_title, dim_unit, Group_concat(Ind_name order by ind_name separator ', ') as Indices
|+ '''Information stored in the public and private databases. The private database can read tables from the public one but not vice versa.
from Dimension, `Index`
! Table, field
where Dimension.dim_id = `Index`.Dim_id
! Private database
group by Dim_name
! Public database
order by Dimension.dim_id
|----
</sql-query>
| 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 <br>Time = 2011-03-09 <br>Test = Clearblue digital test
| Age = 30-40 <br>Sex = Female <br>Country = Finland <br>Time = 2011-03 <br>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.


'''List all indices, and their locations concatenated:
==See also==


<sql-query display="1">
* [http://en.opasnet.org/en-opwiki/index.php?title=Opasnet_base_structure&oldid=18900#All_tables:_Overview A previous discussion about the structure]
Select Dim_name, Dim_title, Dim_unit, Ind_name, Group_concat(Location order by row_number separator ', ') as Locations
* [http://en.opasnet.org/en-opwiki/index.php?title=Opasnet_base_structure&oldid=18900#Main_tables A previous structure and related discussions]
from `Index`, Location, Rows, Dimension
* [http://en.opasnet.org/en-opwiki/index.php?title=Opasnet_base_structure&oldid=18900#Tasks_performed Previous tasks performed]
where `Index`.ind_id= Rows.ind_id and Rows.loc_id = Location.loc_id and `Index`.dim_id = Dimension.dim_id
group by Ind_name
order by Dim_name, `Index`.ind_name
</sql-query>


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


'''List all variables and their runs, and also list all dimensions (concatenated) used for each variable for each run.
{{#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
}}


<sql-query display="1">
;Some useful syntax
SELECT Var_id, Run_id, Var_name, Var_title, GROUP_CONCAT(Dim_name SEPARATOR ', ') as Dimensions, n, Run_method
* http://www.baycongroup.com/sql_join.htm
FROM
* [[:image:Opasnet base connection.ANA|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.
    (SELECT Loc_of_result.Var_id, Run_list.Run_id, Var_name, Var_title, Dim_name, n, Run_method
* [http://en.opasnet.org/en-opwiki/index.php?title=Opasnet_base&oldid=7181#Other_queries Some historical queries]
    FROM Loc_of_result, Run_list, Run, Variable, Location, Dimension
* [http://en.opasnet.org/en-opwiki/index.php?title=Opasnet_base_structure&oldid=14214#Some_useful_syntax Some historical queries 2]
    WHERE Loc_of_result.Result_id = Run_list.Result_id
[[Category:Opasnet Base]]
    AND Run_list.Run_id = Run.Run_id
[[Category:Data]]
    AND Loc_of_result.Var_id = Variable.Var_id
[[Category:Opasnet]]
    AND Loc_of_result.Loc_id = Location.Loc_id
    AND Location.Dim_id = Dimension.Dim_id
    GROUP BY Dimension.Dim_id, Loc_of_result.Var_id, Run_list.Run_id
    ORDER BY Loc_of_result.Var_id, Run_list.Run_id) as temp1
GROUP BY Var_id, Run_id
</sql-query>

Latest revision as of 12:01, 10 January 2014



This page is about the old structure of Opasnet Base used in ca. 2008-2011. For a description about the current database, see Opasnet base 2.

Question

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.

Answer

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

Data structure

Main article: Data structures in Opasnet

All data should be convertible into the following format:

Observation
Year Sex Age Height Weight Description
2009 Male 20 178 70 An optional column for descriptive text about each row.
2009 Male 30 174 79
2010 Male 25 183 84
2010 Female 22 168 65

where

Names of explanation columns, also known as indices.
Explanation data, also known as locations. You can use these columns as search criteria.
Observation index, typically called "Observation". Common name for all observation columns
Names of observation columns. These are the parameters of interest.
Observation data. These are the actual measurements.

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

Rationale

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.


Dependencies

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 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