Message-ID: <1987931402.139.1418906287198.JavaMail.confluence@ece-vmapps> Subject: Exported From Confluence MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_Part_138_495367082.1418906287197" ------=_Part_138_495367082.1418906287197 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Content-Location: file:///C:/exported.html
58.In this appendix, a worke= d example for all object types and most attributes, based mainly on the Sta= ndard Industrial Classification (SIC 2007), is provided to facilitate under= standing.
59. Attributes or terms used in the descriptions which are underlined, r= efer to an object type listed and described elsewhere in the model.
60. A Classification Family is a gro= up of Classification Series related from a particular point of view. The Cl= assification Family is related by being based on a common Concept (e.g. eco= nomic activity).
61. Different classification databases may use different types of Classi=
fication Families and have different names for the families, as no standard=
has been agreed upon.
Identifier: A Classification Family is identified by a =
Name: A Classification Family has a name.
E.g.: Industrial activities
Classification<= /span> Series<= /span>: A Classification Family may refer to a number of Classific= ation Series.
E.g.: Standard Industrial Classificati= on, Classification of CPA codes
See als= o: Classification Series
62. For a practical example, see: http://stabas.ssb.no/MainFr= ames.asp?Language=3Den
63. A Classification Series is an en= semble of one or more Statistical Classifications, based on the same concep= t, and related to each other as versions or updates. Typically, these Stati= stical Classifications have the same name (for example ISIC or ISCO).
Identifier: A Classification Series is identified by a =
unique identifier, which may typically be an abbreviation of its name.
Na= me: A Classification Series has a name as provided by the owner. E.g.: Standard Industrial Classification
Description: Short general descrip= tion of the Classification Series, including its purpose, its main subject = areas etc.
E.g.: SIC is primarily a statistical stan= dard. The standard will be the basis for coding units according to principa= l activity in e.g. a business register. The SIC is one of the most importan= t standards of economic statistics, and it will make it possible to compare= and analyze statistical data both at the national/international level and = over time. SIC is also used for administrative purposes.
Context: A Classification Series can be = designed in a specific context.
E.g.: Not relevant <= br class=3D"atl-forced-newline" /> Objects/units c= lassified: A Classification Series is designed to classify a speci= fic type of object/unit according to a specific attribute.
E.= g.: Economic activities
E.g.: Nationa= l accounts, Energy and manufacturing
Owners: The statistical office or other authority, which cre=
ated and maintains the Statistical Classification(s) related to the Classif=
ication Series. A Classification Series may have several owners.
Keywords: A Classification Ser= ies can be associated with one or a number of keywords.
E.g.:= Industry, business, legal units
Classification Family: Classification Series may be grouped into Classification Famili= es. Shows which Classification Family the Classification Series belongs.
E.g.: Industrial activities
Statistical= span> Classifi= cation: A Classification Series has at least one Statistica= l Classification.
E.g.: SIC94, SIC 2002, SIC 2007 Current Statisti= cal Classification: If there are several Statisti= cal Classifications related to a Classification Series, one Statistical Cla= ssification may be assigned as the currently valid Statis= tical Classification.
E.g.: SIC 2007
64. For a practical example, see: http://www.ssb.no/= metadata/classification/stabas/342101/en
65. A Statistical Classification is = a set of categories which may be assigned to one or more variables register= ed in statistical surveys or administrative files, and used in the producti= on and dissemination of statistics. The categories at each level of the cla= ssification structure must be mutually exclusive and jointly exhaustive of = all objects/units in the population of interest.
66. The categories are defined with reference to one or more characteris=
tics of a particular population of units of observation. A Statistical Clas=
sification may have a flat, linear structure or may be hierarchically struc=
tured, such that all categories at lower Levels are sub-categories of categ=
ories at the next Level up. Categories in Statistical Classifications are r=
epresented in the information model as Classification Items.
Identifier: A Statistical Classification is identified =
by a unique identifier. The identifier of a Statistical Classification prin=
cipally considered to be a version or update is typically an abbreviation o=
f its name. It is often distinguished from other versions/updates of the sa=
me Classification Series by reference to a revision number or to the year w=
hen it came into force. The identifier of a Statistical Classification that=
is considered to be variant typically refers to (contains) the identifier =
of its base Statistical Classification.
E.g.: SIC200= 7
Name: A Statistical = Classification has a name as provided by the owner or maintenance unit.
E.g.: Standard Industrial Classification (SIC 2007)
Introduction: The introdu= ction provides a detailed description of the Statistical Classification, th= e background for its creation, the classification variable and objects/unit= s classified, classification rules etc. See Appendix 2 for a checklist of p= ossible topics to be included in the introduction.
E.g.: Standard Industrial Classification is primarily a statistical standard= . In practice, this means the standard will be the basis for coding units a= ccording to the most important activities in Statistics Norway's Business r= egister and in the Central Coordinating Register for Legal Entities. SIC200= 7 is one of the most important standards of economic statistics, and it mak= es it possible to compare and analyze statistical data at the national/inte= rnational level and over time. =
Release date:<= /strong> Date on which the Statistical Classification was released.
<= strong>E.g.: 01.01.2009
Current: I= ndicates whether or not the Statistical Classification is currently valid.<= br /> E.g.: Yes
E.g.:= strong> 810 - Division for statistical populations
Contact persons: Person(s) wh= o may be contacted for additional information about the Statistical Classif= ication.
E.g.: Ida Skogvoll, email@example.com
Legal base: Indic= ates that the Statistical Classification version is covered by a legal act = or by some other formal agreement.
E.g.: Council Reg= ulation (EEC) No. 1893/2006
Pub= lications: A list of the publications, including print, PDF, HTML = and other electronic formats, in which the Statistical Classification has b= een published.
E.g.: http://www= .ssb.no/a/publikasjoner/pdf/nos_d383/nos_d383.pdf
Name types: A list of the = defined types of alternative item names available for the Statistical Class= ification. Each name type refers to a list of alternative item names.
= E.g.: Short titles (for use in our dissemination tables) =
Languages avai= lable: A Statistical Classification can exist in one or several la= nguages. Indicates the languages available, whether the version is complete= ly or partially translated, and which part is available in which language.<= br /> E.g.: Norwegian (bokmål), Norwegian (nynorsk),= English
Copyright: St= atistical Classifications may have restricted copyrights. Such Statistical = Classifications might be excluded from downloading. Notes the copyright sta= tement that should be displayed in official publications to indicate the co= pyright owner.
E.g.: Not relevant
Dissemination allowed: = Indicates whether or not the Statistical Classification may be published or= otherwise disseminated (e.g. electronic dissemination).
E.g.= : Yes
Classification Series: A Statistical C= lassification is a version or update of one specific Classification Series<= br /> E.g.: Standard Industrial Classification
Levels: The structure of a Statistical Classification i= s defined by its Levels (classification levels). Include here links to the = relevant Levels.
E.g.: Section, Division, Group, Cla= ss, Subclass
Classification Items: A Statistical Clas= sification is composed of categories structured in one or more Levels. Each= category is represented by a Classification Item, which defines the conten= t and the borders of the category.
E.g.: 01.= 24 Growing of pome fruits and stone fruits
Correspond= ence Ta= bles: A Statistical Classification may be linked to other c= lassification versions or classification variants through Correspondence Ta= bles. Include here links to any relevant Correspondence Tables.
Class= ification Indexes: A Statistical Classification can be associated = with one or a number of Classification Indexes in which Index Entries are l= inked to the appropriate Classification Item. Include here links to any rel= evant Classification Indexes.
Version: Indicates if the S= tatistical Classification is a version.
E.g.: Yes Update: Indicates if the= Statistical Classification is an update.
Floating: Indicates= if the Statistical Classification is a floating Statistical Classification= . In a floating Statistical Classification, a validity period should be def= ined for all Classification Items which will allow the display of the item = structure and content at different points of time.
Predecessor: = For those Statistical Classifications that are versions or updates, notes t= he preceding Statistical Classification of which the actual Statistical Cla= ssification is the successor. .
E.g.: SIC 2002
Successor: Notes the Statis= tical Classification that superseded the actual Statistical Classification.=
Derived from:= A Statistical Classification can be derived from one of the class= ification versions of another Classification Series. The derived Statistica= l Classification can either inherit the structure of the classification ver= sion from which it is derived, usually adding more detail, or use a large p= art of its Classification Items, rearranging them in a different structure.= Indicates the classification version from which the actual Statistical Cla= ssification is derived.
E.g.: NACE Rev.2
Changes from <= strong>previous version or
E.g.: = Information presented in Publications and in Correspondenc= e Table
= E.g.: No
Updates: Summary description of changes which have occurred since the most rece= nt classification version or classification update came into force.
<= strong>E.g.: Not relevant:
E.g.: Variant of SIC -= Environmental accounts (SIC2007)
Changes = from base Statistical Cl= assification: Describe= s the relationship between the variant and its base Statistical Classificat= ion, including regroupings, aggregations added and extensions.
See also: Classification Series, Level, Classification Item, Corre= spondence Tables, Classification Index.
67. For a practical example, see: http://www.ssb.no/m= etadata/classversion/stabas/8118001/en
68. A Statistical Classification has= a structure which is is composed of one or several Levels. A Level often i= s associated with a Concept, which defines it. In a hierarchical Statistica= l Classification the Classification Items of each Level but the highest are= aggregated to the nearest higher Level. A linear Statistical Classificatio= n has only one Level.
Identifier: A Level is identified by a unique identifie=
Level number: The number associated wi= th the Level. Levels are numbered consecutively starting with Level 1 at th= e highest (most aggregated) Level.
Level name: Th= e name given to the Level.
Description: Text describing th= e content and particular purpose of the Level.
E.g.:= Subclass is the most detailed level and describes the national level in SI= C.
Number of= strong> Classification Items: The number = of Classification Items (Categories) at the Level.
Code = type: Indicates whether the code at the Level is alphabetical, num= erical or alphanumerical.
Code structure: Indicates how the code at the Level is constructed of numbers, letters an= d separators.
Dummy code: Rule for the const= ruction of dummy codes from the codes of the next higher Level (used when o= ne or several Categories are the same in two consecutive Levels).
E.g.: Not relevant
E.g.: http://www.ssb.no/metadata/= codelist/stabas/8118013/en
See also= : Statistical Classification, Classification Item
69. A Correspondence Table expresses= the relationship between two Statistical Classifications. These are typica= lly: two versions from the same Classification Series; Statistical Classifi= cations from different Classification Series; a variant and the version on = which it is based; different versions of a variant. In the first and last e= xamples, the Correspondence Table facilitates comparability over time. Corr= espondence relationships are shown in both directions.
Identifier: A Correspondence Table is identified by a u=
nique identifier, which may typically include the identifiers of the versio=
ns or variants involved.
Name: A Correspondence Table ha= s a name as provided by the owner.
E.g.: SN2007, SN2= 002
Description: The d= escription contains information about the scope and aim of the Corresponden= ce Table and the principles on which it is based.
E.g.: The Correspondence Table shows the changes between SIC versions 2002 an= d 2007 and makes comparability over time possible.
Owners: The statistical office, other authorit= y or section that created and maintains the Correspondence Table. A Corresp= ondence Table may have several owners.
E.g.: Statist= ics Norway
Maintenance= unit: The unit or group of persons who are responsible fo= r the Correspondence Table, i.e. for maintaining and updating it.
Contact persons: = The person(s) who may be contacted for additional information about the Cor= respondence Table.
E.g.: Ida Skogvoll, firstname.lastname@example.org Publications: A list of = the publications in which the Correspondence Table has been published.
E.g.: The Correspondence Table is only published in the = classification database
Source:= The Statistical Classification from wh= ich the correspondence is made.
E.g.: SIC 2007
Target: The Statistical classification(s) to which the correspondence is di= rected. There may be multiple target Statistical Classifications associated= with the Correspondence Table.
E.g.: SIC 2002
Source level: The correspondence is normally restricted to a certain Level in the source Statistical Classifi= cation. In this case target Classification Items are assigned only to sourc= e Classification Items on the given Level. If no Level is indicated target = Classification Items can be assigned to any Level of the source Statistical= Classification.
E.g.: Level 5
Target level: The correspo= ndence is normally restricted to a certain Level in the target Statistical Classification. In this = case source Classification Items are assigned only to target Classification= Items on the given Level. If no Level is indicated, source Classification = Items can be assigned to any Level of the target Statistical Classification= .
E.g.: Level 5
= Relationship type: A correspondence can d= efine a 1:1, 1:N, N:1 or M:N relationship between source and target Classif= ication Items.
Floating: If the source and/or target Statistical= Classifications of a Correspondence Table are floating Statistical Classif= ications, the date of the Correspondence must be noted. The Correspondence = Table expresses the relationships between the two Statistical Classificatio= ns as they existed on the date specified in the Correspondence Table.
See also St= atistical Classification, Classification Item, Level, Map
70. For a practical example, see: http://= stabas.ssb.no/CorrTabFrames.asp?ID=3D8364101&Language=3Den
71. A Classification Index is an ord= ered list (alphabetical, in code order etc.) of Classification Index Entrie= s. A Classification Index can relate to one particular or to several Statis= tical Classifications. A Classification Index shows the relationship betwee= n text found in statistical data sources (responses to survey questionnaire= s, administrative records) and one or more statistical classifications. A C= lassification Index may be used to assign the codes for Classification Item= s to observations in statistical collections.
Identifier: A Classification Index is identified by a n=
ame. If there are several Classification Indexes in different languages, th=
e language should be part of the Classification Index name. If there are se=
veral Classification Indexes for different purposes, the purpose should be =
part of the Classification Index name.. If there are several Classification=
Indexes that differ by languages and by purpose, the language and the purp=
ose should be part of the Classification Index name.
Release date: Date when the current version of the Classificat= ion Index was released.
Maintenance unit: The unit or group of persons within the organisation responsible for th= e Classification Index, i.e. for adding, changing or deleting Classificatio= n Index entries.
E.g.: 810 - Division for statistica= l populations
Contact = persons: Person(s) who may be contacted for additional inf= ormation about the Classification Index.
E.g.: Ida S= kogvoll, email@example.com
Publication= s: A list of the publications in which the classification index ha= s been published.
Languages: A classification index can exist in several languages. Indicates the= languages available. If an Classification Index exists in several language= s, the number of entries in each language may be different, as the number o= f terms describing the same phenomenon can change from one language to anot= her. However the same phenomena should be described in each language.
= E.g.: Norwegian (bokmål), English
Corrections: Verbal summary description= of corrections, which have occurred within the Classification Index. Corre= ctions include changing the item code associated with an index entry.
Coding instructions= : Additional information which drives the coding process for all e= ntries in a Classification Index.
E.g.: SIC 2007
72. A classification item represents= a Category at a certain Level within a Statistical Classification. It defi= nes the content and the borders of the Category. A statistical object/unit = can be classified to one and only one Classification Item at each level of = a Statistical Classification.
Code: A Classification Item is identified by an alphabe=
tical, numerical or alphanumerical
code, which is in line with the co= de structure of the Level. The code is unique
within the Statistical = Classification to which the Classification Item belongs.
E.g.= : 01.620
Official name= : A Classification Item has a name as provided by the owner or mai= ntenance unit. The name describes the content of the Category. The name is = unique within the Statistical Classification to which the Classification It= em belongs, except for Categories that are identical at more than one Level= in a hierarchical Statistical Classification.
E.g.:= Support activities for animal production
Alternative names: A Classification Item can be express= ed in terms of one or several alternative names. Each alternative name is a= ssociated with a name type.
E.g.: Short text: Suppor= t activities to agriculture
Exp= lanatory notes: A Classification Item may be asso= ciated with explanatory notes, which further describe and clarify the conte= nts of the category. Explanatory notes consist of:
General note: Contains either= additional information about the Category, or a general description of the= Category, which is not structured according to the "includes", &= quot;includes also", "excludes" pattern.
E.g.:= Not relevant
Includes= : Specifies the contents of the Category.
E.g.: Includes services, associated with the keeping of farm animals, in act= ivities that increase reproduction, growth and performance in farm animals,= testing of farm animals (control), maintenance of grazing areas, castratio= n, cleaning of barns, insemination and covering, clipping of sheep, housing= and care of farm animals.
E.g.: Includes activitie= s in connection with agriculture carried out on a contract basis
Includes also:= A list of borderline cases, which belong to the described Category.
= E.g.: Includes also: Includes also shoeing of horses.
Excludes: A list of border= line cases, which do not belong to the described Category. Excluded cases m= ay contain a reference to the Classification Items to which the excluded ca= ses belong.
E.g.: Excludes: Renting out of areas exc= lusively for housing of farm animals is grouped under Other letting of real= estate. Veterinary services is grouped under 75.000 Veterinary activities,= Vaccination of farm animals is grouped under 75.000 Veterinary activities.= Renting out of farm animals (e.g. cattle) is grouped under 77.390 Renting = and leasing of other machinery, equipment and tangible goods n.e.c. Housing= of domestic pets is grouped under 96.09 Other personal service activities = n.e.c.
Level n= umber: The number of the Level to which the Classification Item belongs.
E.g= .: 5
Generated: Indicates whether or not the Classification Item has been generated to m= ake the Level to which it belongs complete.
Currently val= id: If updates are allowed in the Statistical Classification, a Cl= assification Item may be restricted in its validity, i.e. it may become val= id or invalid after the Statistical Classification has been released. Indic= ates whether or not the Classification Item is currently valid.
= Valid from: Date from which the Classification It= em became valid. The date must be defined if the Classification Item belong= s to a floating Statistical Classification.
E.g.: Valid to: Date at which the Classification Item became invalid. The date must be d= efined if the Classification Item belongs to a floating Statistical Classif= ication and is no longer valid.
Future events: The = future events describe a change (or a number of changes) related to an inva= lid Classification Item. These changes may e.g. have turned the now invalid= Classification Item into one or several successor Classification Items. In= describing these changes, terminology from the Typology of item changes, f= ound in Appendix (1) should be used. This allows the possibility to follow = successors of the Classification Item in the future.
E.g.: Not relevant
Changes fro= m previous version of the Statistical Classification: Describes th= e changes, which the Classification Item has been subject to from the previ= ous to the actual Statistical Classification. In describing these changes, = terminology from the Typology of item changes, found in Appendix (1), shoul= d be used.
E.g.: Name and Code change. In SIC2002 this item was called " 01.420 Animal husbandry service = activities, except veterinary activities". The history of the item is = also documented in the Correspondence Table.
Updates: Describes the changes, which the Classifica= tion Item has been subject to during the life time of the actual Statistica= l Classification.
E.g.: Not relevant
St= atistical Classification: The Statistical Classification to which = the Classification Item belongs.
E.g.: SIC 2007
Parent item: The Classification Item at the next higher Level of the Statistical Cla= ssification of which the actual Classification Item is a sub item.
E.g.: 01.62 Support activities for animal production
= Sub items: Each Classification Item, whic= h is not at the lowest Level of the Statistical Classification, might conta= in one or a number of sub items, i.e. Classification Items at the next lowe= r Level of the Statistical Classification.
E.g.: Not= relevant
E.g.: 01.420 Animal h= usbandry service activities, except veterinary activities (SIC2002)
Case law: Re= fers to identifiers of one or more case law rulings related to the Classifi= cation Item.
E.g.: Not relevant
Case law descript= ions: Case law descriptions refers to descriptions of the above ca= se laws.
E.g.: Not relevant
Case law dates: Refers to dates of above case laws.
E.g.: Not re= levant
See also Level, Classification I= ndex Entry, Correspondence Item, Statistical Classification
73. A map is an expression of the re= lation between a Classification Item in a source Statistical Classification= and a corresponding Classification Item in the target Statistical Classifi= cation. The Map should specify whether the relationship between the two Cla= ssification Items is partial or complete. Depending on the relationship typ= e of the Correspondence Table, there may be several maps for a single sourc= e or target Classification Item.
Source item: The source item refers to=
E.g.: 01.620 Support activities = for animal production
Target item: The target item refers to the Classification Item in the target Statistical Classification. E.g.: 01.420 Animal husbandry service activities, exc= ept veterinary activities
Parti= al/complete: specifies whether the relationship between the two Cl= assification Items is partial or complete
E.g.: Comp= lete
Valid fro= m: Date from which the Map became valid. The date must be defined = if the Map belongs to a floating Correspondence Table.
Valid to: Date at which t= he Map became invalid. The date must be defined if the Map belongs to a flo= ating Correspondence Table and is no longer valid.
See also Statistical Classification, Classification Item, Corre= spondence Table
74. A Classification Index Entry is = a word or a short text (e.g. the name of a locality, an economic activity o= r an occupational title) describing a type of object/unit or object propert= y to which a Classification Item applies, together with the code of the cor= responding Classification Item. Each Classification Index Entry typically r= efers to one item of the Statistical Classification. Although a Classificat= ion Index Entry may be associated with a Classification Item at any level o= f the Statistical Classification, Classification Index Entries are normally= associated with Classification Items at the lowest Level.
Text: Text describing the type of object/unit or object=
E.g.: Animal husbandry
Stati= stical = Classification: Identifies the Statistical Classification(s= ) to which the Classification Index Entry is associated.
E.g.= : SIC2007
Codes: For each Statistical Classification to which the Classification Index E= ntry is associated, enter the code of the Classification Item in that Stati= stical Classification with which the Classification Index Entry is associat= ed.
E.g.: 01.620 Support activities for animal produ= ction
Valid fr= om: Date from which the Classification Index Entry became valid. T= he date must be defined if the Classification Index Entry belongs to a floa= ting Classification Index.
Vali= d to: Date at which the Classification Index Entr= y became invalid. The date must be defined if the Classification Index Entr= y belongs to a floating Classification Index and is no longer valid.
Coding instructions:= Additional information which drives the coding process. Required = when coding is dependent upon one or many other factors.
See also Classification Item, Classification Index, Stati= stical Classification