DPM2MDM

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CEN Workshop Agreement

CEN WS XBRL Experts: Ignacio Santos (Bank of Spain)

Foreword

This document has been prepared by CEN/WS XBRL, the secretariat of which is held by NEN. CWA XBRL 001 consists of the following parts, under the general title Improving transparency in financial and business reporting — Harmonisation topics:

Part 5: Mapping between DPM and MDM

General

The purpose of this document is to present and explain the mapping between the Data Point Model (DPM) and the Multidimensional Data Model (MDM) [1] [2] [3] [4] [5], through the Relational Model using ROLAP analytic tool. This document is based in a work presented in Banca D’Italia, Rome, in September 2011 [20]. ROLAP is defined as Relational Online Analytical Processing. The DPM is a semantic model (Logical Model). Experts in the supervision in Europe have created the DPM, and as they are not software Engineers, they have important difficulties, especially with the XBRL specification [6]. XBRL taxonomies are metadata that provide a formal description of the data requirements to be used as data format in this case in the European reporting process. This document intends also to supply a description for IT experts about the linkage between a DPM as source and a relational data base as target of a transformation process.

The objective of the European XBRL Taxonomy Architecture (EXTA), is to set a framework or set of architecture guidelines that enables a Discoverable Taxonomy Set (DTS) author to create an XBRL taxonomy. However in this document expect to help to design the taxonomy through the DPM and in turn, it can implement the DPM in a Database. But, moreover, to help to Information System (IS) to have a better comprehension of the metadata. Comment-01

This project is funded by the EU commission to support the standardization process for supervisory reporting in Europe.

Objective

The objective of the EXTA is to define a set of architecture guidelines that transform a European DPM without a loss in quality in a XBRL format. The taxonomy architecture provides a set of rules for this transformation to enable the creation of consistent and predicable XBRL meta definitions in an automated process. On the other hand CEN WS has built a guidelines for mapping the DPM in the MDM. In such a way that the architect of IS can understand and/or mapping the DPM to ROLAP.

Target Audience

EXTA is targeted at taxonomy authors. Initially organizations like European Banking Authority (EBA), European Insurance and Occupational Pensions Authority (EIOPA), European Securities and Markets Authority (ESMA), European Central Bank (ECB) are the authors of these taxonomies. As a spin-off of these taxonomies, local (national) initiatives will emerge, hosted by National Supervisory Agencies (NSA’s). The audience of this document are financial or economic institutions, agencies, companies, or Universities that they want to implement the taxonomies in a relational model.

Relationship to other work

The reader of this EXTA is expected to be familiar with the principles of data modelling and have an understanding of the XBRL family of the specification. But, also, it is necessary to have a knowledge in the relational model and in the MDM.

1 Scope
2 Terms and definitions
3 Mapping from Data Point Model to Multidimensional Data Model
4 ANNEX A. Metamodel defined by the EBA (FINREP and COREP) mapped to MDM.
5 Bibliography

Scope

The DPM has been defined for the creation of Data Point Models in the context of European supervisory reporting. Data Point Model by an European supervisory authority. To reflect the defined structures in a machine-readable from the can be accompanied by an XBRL taxonomy. It is also possible to extend the described methodology to other environments as Database. Comment-02

Terms and definitions

For the purposes of this document, the following terms and definitions apply. The terms definitions used in the mapping with Data Point Model are inspired by vocabulary already known through their use for describing multidimensional databases and data warehouses. IT specialists originally introduced these terms. However, for an understanding and creation of Data Point Models they are established in the language of business specialists as well.

In this section are shown the set of definitions necessaries for mapping the DPM in ROLAP. The majority of the definitions are obtained of [6] [7] [8] [9] [10]. When the definition is in the area of CEN WS XBRL (Main Page) [11] [22] only is shown a hyperlink to definition.

The terms used directly or indirectly in the mapping of DPM in the MDM are:

Concept.

Data Point Model.

Dimension.

Domain.

Family.

Framework.

Item.

(Domain) member.

Metric.

Namespace.

Owner.

Perspective.

Public elements.

TableGroup.

DataPoint.

DataCube.

Module.

Hypercube.

A hypercube is an abstract item declaration in the xbrldt:hypercubeItem substitution group. A Hypercube is an ordered list of dimensions, defined by the set of zero or more dimension declarations linked to the hypercube by hypercube-dimension relationships in a dimension relationship set, and ordered according to the order of this relationship [10].

In the DPM a hypercube is reflect in the DataCube. A DataCube is a set of DataPoints with its appropriate Dimensions and Members.

A hypercube in the MDM is a set of pairs <dimension, attributes of dimension> and calculated attributes defining one or more facts [19].

Taxonomy.

Context.

The context element contains information about the entity being described, the reporting period and the reporting scenario, all of which are necessary for understanding a business fact captured as an XBRL item [6].

In the MDM, the context is defined as a set of dimension of a fact or group of facts. A context belongs to an entity or financial institution, for a period, a meaning for the business (segment), and a scenario. The scenario shows the specific pairs of dimension and the dimension attribute of business logic [9].

Mapping from Data Point Model to Multidimensional Data Model

Comment-03

Introduction

This section presents the mapping between the DPM and the Relational model through ROLAP. In this mapping is not expected the transformation to XBRL taxonomies, however is possible its conversion [20]. Moreover, also, in this transformation is not established any process of validation. It is only mapped the DPM structure in the Relational model. However, it is expected that the reader of this document can understand better the DPM or even that the reader can store the DPM in a RDBMS (Relational Database Management System), using the MDM.

There are a lot of bibliography about the mapping from different sources to a relational database especially from XML [12] [13] [15] [21], and about query in heterogeneous sources is interesting the paper of Levi et al. [14]. Nevertheless, the process of transformation of this section is based in Taentzer et al. [15}. This section will go step to step with the different constructors that they are corresponding in the DPM.

In this section the process of conversion is analysed. Normally, in a first step is to study the DPM element or element to transform. After, the mapping between the DPM element and the Relational elements. The transformation process in the figures show the DPM UML graph on the left hand side to UML class diagram to display the Relational model (ROLAP) from MDM. The black arrows between both UML language but customized extensions which are used to describe the graph transformation. The square between two black arrows contains an abbreviation what is begin mapped. In this document are distinguished the next different types of mappings rules between the two graphs [15]:

C2C is the automatic transformation between concepts.
C2F is the automatic transformation between concepts and frameworks.
C2T is the automatic transformation between concepts and taxonomy.
A2T is the automatic transformation between attributes to taxonomy.
T2T is the automatic transformation between taxonomies.
A2A is the automatic transformation between attributes to attributes.
C2D is the automatic transformation between classes of dimensions to dimensions.
C2DA is the automatic transformation between classes to attributes of dimension.
C2CTx is the automatic transformation between classes to contexts.
C2CTxDM is the automatic transformation between classes to Contexts, dimensions, and attributes of dimension.
C2Fact is the automatic transformation between classes and the fact table.

Framework

The figure 1 shows the perspective Structural of the framework. The Data Point Model has from 1 to N public elements. From a public element inherits different classes, as element of the dictionary or frameworks [11] [22].

Figure 1. Structural perspective of the framework

The figure 2 show the transformation of the class public element and framework. The aim is to obtain the constructor Framework. For this publicElement is mapped in a constructor concept and the framework in relational model, as the constructor. In figure 2 can be omitted the mapping of publicElement to concept, if the class framework has inherited the necessary element of publicElement. However, the figure 2 maintains it for comprehension.

Figure 2. Mapping for the framework

Taxonomy

In the same way the class taxonomy inherits of public element [11] [22], as figure 3 shows.

Figure 3. Structural perspective of the taxonomy

In figure 4 is shown the mapping between the class Taxonomy of the DPM and the constructor Taxonomy and the RM (Relational Model). However, in this figure are add details as the breakdown of some attributes of the class taxonomy, for clarifying better to reader of this document. On the other hand in the RM a taxonomy inherits from a taxonomy.

Figure 4. Mapping for the constructor taxonomy

Dimensions

In this section is defined the mapping of the constructor dimension. The figure 5 shows a perspective of the structure of the dimension [11] [22].

Figure 5. Structural perspective of the dimension.

This figure shows two types of dimensions [9] [10], the implicit and the typed dimension. But in an upper level is the family or group of dimensions and they belong to a same domain. If the dimension is explicit then this contains a set of members. Each domain has one and only one member by default. An explicit dimension consists of a number of members, called domain-member, and therefore is enumerable. On the other hand, a typed dimension is not enumerable because its member are not known in advance.

The figure 6 shows only the mapping of the explicit dimension. Where the transformation between DictonaryElement (DPM) and Concept (RM) is detailed a little more, for comprehension of the reader.

Figure 6. Mapping for explicit dimensión.

However, in the Relational model both constructors are one, explicit and typed. The entity Dimension entity will have an attribute for showing if the dimension is typed or explicit and another attribute with the data type.

The figure 7 depicts the transformation of the DPM to ROLAP, and the reverse mapping of the typed and explicit dimensions. In this figure is added the union between the explicit dimension and the typed dimension.

Figure 7. Mapping of transformations for dimensions.

On the other hand, from the members defined or not are obtained the dimension attributes of the dimension. But in both cases they will defined in this constructor, although they are filled out when the taxonomy is defined or in run time of the document instance. The figure 8 shows the mapping of the dimension attributes with the members.

Figure 8. Mapping of members defined or not to dimension attributes.

The figure 9 shows the mapping of Dimensions and domain-members and Dimensions/Dimension attributes in the Relational data model (ROLAP).This figure really is an artifice, because is not necessary the mapping from the DPM.

Figure 9. Mapping of the Relations.

Context

The figure 10 shows the mapping of DPM to the Relational Model. There are two Context and another for the context with the dimensions and the domains-members. In the relational model the dimensions can be explicit or typed.

In the mapping is obtained two constructor for the RM, the Context_taxonomy, and Context_Dim_Member. A context in the DPM is a DataCubes with the same set of dimensions but in different taxonomies. This makes that this context has meaning different depending on the taxonomy. For this the context is shared by the taxonomy. Moreover, each context has a set of dimensions (explicit or typed) with its domain-member (if is explicit). Then, it is defined another constructor contex_Dim_Member. Each object of this constructor is a dimension/member/context.

Figure 10. Mapping of the context.

Primary Items

The primary item could be a domain-member of a dimension, however, is a little special, because is associated with this concept two attributes, the type of the data and the time period type. The figure 11 shows the mapping with the relational model. The set of primary items are grouped in the base dimension, in this figure is called the constructor PrimaryItem.

Figure 11. Mapping for the Base Dimension.

Fact table or Data points

The figure 12 shows the mapping between the DPM and the Relational model. This mapping is to make to point put the DataPoint in the DPM and the constructor FactTable, that is the same.

Figure 12. Mapping DPM to ROLAP of the fact table.

Star Model

In the next graphic is presented the star diagram of the DPM in the relational model (ROLAP), figure 13.

The object FactTable is the DataPoint, in the MDM is the fact table. It is a star model, because, to fact table goes in three dimensions, BaseDomain (set of primary items), Taxonomy and Context. To dimension Taxonomy goes in the dimension Framework. To the context goes into the dimension Context_Dimension_DimensionAttributes.To the last dimension the set of dimension/attributes of dimension. And, to the set dimension/attributes of dimensions the dimensions end DimensionAttributes. Also, it is possible to add the dimension familie to Dimensions, that it is not drawn, according to not complicate the drawing.

Figure 13. Star model of the DPM using ROLAP tool.

ANNEX A. Metamodel defined by the EBA (FINREP and COREP) mapped to MDM.

Introduction.

This annex maps the relational model of the DPM supplied by the EBA in the MDM, using ROLAP tool.

The EBA published on 15 March 2013, and after a modification on 27 March 2013 the updated version of the templates, instruction, validation rules, and data point model for implementing technical standards (ITS) on supervisory reporting (COREP and FINREP [16]. On the other hand, in that date EBA published the DPM Database 0.1.1 as Meta model structure used as the repository all the metadata defined in the DPM from which the XBRL taxonomies will be derived. This annex will map this structure of the EBA to the relational data model [18]. The database is built from this document and with the help of a paper under review [19]. For a better understanding the implementation is done in MS SQLServer, version 2012, Sp1. However its move to other RDBMS is easy, because SQL is a standard. In a first step is created the structure of the DPM in the RDBMS (Relational Data Base Management System), SQL Server. And the second step is to populate the DPM in database with the datamodel of the EBA (DPM Database 0.1.1) through a tool ETL (Extract, transformation, and load).

The EBA in this example don’t provide any XBRL Document Instance, then it is not possible to fill out the fact table with an example, but the structure of the DPM is complete. However, in this model is considered a difference with this datamodel propose, the base dimension is a normal explicit dimension, therefore the table base dimension is empty.

Creation of the structure and load the DPM of the EBA in a RDBMS.

In the annex B is shown the creation of the structure of the DPM in RDBMS using the MDM, hosted by CWA1.

On the other hand, from the EBA webpage [16] is possible to download the zip file with the Metadata model structure, DPM Database 0.1.1. After the structure and data will be move to RDBMS. In this document is used MS SQL Server (there free edition). However, it is possible to use other RDBMs, as oracle, DB2, etc.. From Access to SQL Server in this document is used Integration Services IS of MS SQL Server (there is free edition). Through IS (Information Systems) is implemented the importation of the metadata. In this toll, the origin is the Access (The used driver is Microsoft Access (Microsoft Set Database Engine), and the target the client, SQL Server Native client 11.0 and the database, in this document the name is DPM_EBA. After, all tables have to be selected, and the packet is submitted. The figure 14 shows a general view of the load of the Access in a RDBMS and the mapping to DPM in a Relational Database.

Figure 14. General view of Access and RDBMS of the EBA and the DPM in ROLAP.

Loading DPM_ROLAP from DPM_EBA.

This section makes a mapping from DPM_EBA to DPM_ROLAP, both database. The DPM_EBA is loaded in the above section. And DPM_ROLAP is created using the annex B of this document.

As first step, the table Framework_DPM is loaded from ReportingFramework. This load is shown in the figure 15, through its design and after the code. In the code of this document the dates are simulated.

Figure 15. Mapping of the framework.

The code of M1 is:

use DPM_ROLAP
--
--	M1 CODE
--
--truncate table framework_DPM
delete from Framework_DPM 
go
insert into Framework_DPM (ID_Framework, nameFramework, valid_from, userID_created)
select	FrameworkID as ID_Framework,
       FrameworkCode as nameFramework,
       convert(datetime, '20130327', 112),
       'EBA'
FROM DPM_EBA..ReportingFramework
go
select * from Framework_DPM
go

If the framework is loaded, next table is Taxonomy_DPM, that is loaded from the database DPM_EBA..Taxonomy. The figure 16 shows the mapping M2.

Figure 16. Mapping of the taxonomy.

The code of the mapping M2 is:

use DPM_ROLAP
--
-- code M2
--
--truncate table taxonomy_DPM
delete from Taxonomy_DPM
go
insert into Taxonomy_DPM(ID_Taxonomy, ID_Framework, nameTaxonomy, 
			labelTaxonomy, valid_from, versionTax,
			date_created, userid_created)
select TaxonomyID as ID_Taxonomy, FrameworkID, TaxonomyCode, 
		TaxonomyLabel, convert(datetime, '20130327', 112), '0',
		convert(datetime, '20130327', 112), 'EBA'
from [DPM_EBA].[dbo].[Taxonomy]
go
select * from Taxonomy_DPM
go

The next step is to obtain dimensions from the EBA, and it is shown in the figure 17.

Figure 17. The mapping of dimensions.

The code of the mapping M3 is:

--
-- code M3
--
insert into Dimension_DPM (dimensionID, dimensionCode,  
	dimensiondescr, domainID, 
	typedDim, 
	typeData, 
	valid_from)
select a.DimensionID, a.DimensionCode, 
	a.DimensionLabel as dimensiondescr, a.DomainID, 
	a.IsTyped as typedDim, 
	cast(b.DataTypeID as nvarchar(30)) as typeData, 
	convert(datetime, '20130327', 112) as valid_from 
from DPM_EBA.dbo.Dimension a inner join DPM_EBA.dbo.Domain b
	on a.DomainID=b.DomainID
go
select dimensionID, dimensionCode, 
	dimensiondescr, domainID, 
	typedDim, 
	typeData,
	valid_from
from dimension_DPM
go

After, it is obtained the dimension attributes, as it is shown in the figure 18.

Figure 18.- Mapping of the attributes of dimensión (ROLAP).

The code of the mapping M4 is:

---
--- Code M4
---
insert into Domain_Member_DPM(memberID, domainID, memberCode,
		memberDescr, byDefault, createFrom,
		valid_from)
Select MemberID, DomainID, MemberCode, 
		MemberLabel as memberDescr, IsDefaultMember as byDefault,
		convert(datetime, '20130327', 112) as createFrom,
		convert(datetime, '20130327', 112) as valid_from
from DPM_EBA.dbo.Member
go
select memberID, domainID, memberCode, memberDescr,
		byDefault, createFrom, valid_from,
		valid_to
from Domain_Member_DPM
go

The relations between dimensions and attributes of dimension is shown in the figure 19.

Figure 19. Relationship between dimensions and attributes of dimension.

The code of the mapping M5 is:

---
--- Code M5
---
insert into Dimension_Domain_Member_DPM(
	dimensionID, memberID)
select DimensionID, MemberID 
from DPM_EBA.dbo.DimensionalCoordinate
go
select dimensionID, memberID
from Dimension_Domain_Member_DPM
go

The next table is the context and the figure 20 shows the mapping. As a data point (a fact) can be referenced by a context, but this context belongs to a taxonomy, the context needs of the taxonomy (module is named by the EBA).

Figure 20. Mapping of the context from DPM_EBA.

End modification -----------------------

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