Message-ID: <1024826104.3446.1495481343155.JavaMail.confluence@ece-vmapps> Subject: Exported From Confluence MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_Part_3445_854096836.1495481343155" ------=_Part_3445_854096836.1495481343155 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Content-Location: file:///C:/exported.html 4. System and Design Issues (Finland)

4. System and Design Issues (Finland)

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4.1 IT Arc= hitecture

Statistics Finland's common metadata system is implemented according to = the principles of service-based architecture.

Services meeting the needs of different us= er groups and client systems have a key role in the service-based architect= ure. The picture below shows the service interface to be built on top of th= e metadata warehouse, whose services produce the required data from the doc= uments in the metadata warehouse, and also attend to storing of data to the= warehouse.

The content of the metadata warehouse is maintained and it can be made a= vailable in client systems by ordering services through the service interfa= ce from the metadata warehouse. The service interface is implemented in lin= e with the REST architecture (Representational State Transfer). The basic s= tructures of the application are carried out according to the layer style. = The business logic layer is formed of REST service interfaces, their proces= sing logics and data transfer modules offered by the interfaces to client s= oftware. The function of data transfer modules is to offer data from the XM= L data warehouse to client software with an easy-to-use entity structure.

<= span style=3D"color: black;"> 4.2 Metadata Management Tools

 See Section 2.2.

4.3 S= tandards and formats

Statistics Finland has developed a Common Structure of Statistical Infor= mation (CoSSI) based on xml. It is a modular data model for describing stat= istical tables, classifications, concepts, variables, general information o= n statistical documents, quality descriptions, etc. CoSSI was designed in a= ccordance with international standards such as the Dublin Core and CALS. If= needed, CoSSI can be expanded; new elements, e.g. for data descriptions ha= ve already been integrated into it.  In its ITC strategy, Statistics F= inland has provided guidelines for the use of the CoSSI model. The data mod= els of the classifications and concepts in use have been developed in the 1= 990s, and the elements they contain are presently part of CoSSI.

The basic structure and content of statistical inform= ation is defined in the CoSSI data model. It describes the information stru= cture of the statistical data to be produced. The way in which data are pro= duced, that is, the production steering system, is not described in the CoS= SI data model. The definition of the data and content required by the produ= ction steering system was left to the future development phase of the model= .

The data model comprises a description of basic infor= mation of data sets for the production and editing of statistical data and = distribution of statistical information. At the moment, the model's parts t= o be extended and checked due to changed content requirements are as follow= s:

Preliminary examinations indicate that the CoSSI data= model offers an adequate basis for producing content description data of s= tatistical information following the GSIM data model (Generic Statistical I= nformation Model, version 0.4/ 5.2012). A preliminary outline has been made= to the CoSSI model of the structure that would cover the needs of Eurostat= 's different quality reports.

CoSSI documentation on the web: http://www.stat.fi/org/= tut/dthemes/drafts/cossi_en.html

4.4 Version control and revisions

The versioning of the classifications can be seen as a 4-level hierarchy= :

Level 1 (the highest level) is the classification name. It is a logical = element in a hierarchy and its purpose is to aggregate all the statistical = versions of a classification. In the classification database the classifica= tion name is expressed as a short technical name.

Level 2 consists of the statistical versions of a classification. There = can be one or more statistical versions per classification. For example, st= atistical versions for the classification name =E2=80=9CIndustrial classifi= cation=E2=80=9D are, for example, the Finnish Standard Industrial Classific= ation TOL and the Industrial Classification for business services statistic= s. In the classification database the statistical versions are separated fr= om one another by version number.

Level 3 contains the time versions of a classification. In the classific= ation database the time versions are separated from one another by period o= f validity. When a classification changes, a new time version is made on th= e classification database. The old versions remain in the database and they= can be used, e.g. in archiving.

Level 4 includes the language versions of a classification. The language= versions (Finnish, Swedish and English) share the basic information with t= heir mother classification or concept.

The concepts are being versioned in the same way as the classifications.= The concepts usually stay the same for a long time but sometimes modificat= ions take place, for example, due to amendments to legislation.

A configuration on the versioning of the classifications (see picture be= low).



 

 

 

(click on the thumbnail to view full size image)

 

4.5 Outsourcing versus in-house development

The user interfaces and the applications f= or the databases have been mainly developed and built in-house.The applicat= ions developed at Statistics Finland can in principle be shared free of cha= rge with other statistical organizations. Where necessary, details r= egarding test use and access to more precise descriptions etc. may be agree= d upon separately.

4.6 Sharing software components of tools

4.7 Additional materials Links to add= itional materials such as data models.

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