1. Supporting the use of administrative data in official statistics.
The System of Integrated Microdata – SIM and the Quality Report Card of Administrative data - QRCA
Marina Venturi
Grazia Di Bella
Italian National Institute of Statistics - Istat
NTTS 2017
Brussels, March 2017
NTTS 2017

2. New Istat modernization process
Innovation of the statistical production system.
Use of AdminData
The overall Istat modernization process is focused on the new System of Integrated Registries based mainly on AdminData:
Business Register
Population Register
Places Register
Activities Register
A single Directorate deals with all aspects of the data collection, survey and AdminData, and the first data treatment process.
Brussels, March 2017
NTTS 2017

3. Automation of processes for the management of the AdminData flows
Considering the complexity of the system and the need to process large amounts of data
Strategy
Use of IT tools to acquire, store, integrate and disseminate AdminData
Strengthening of the metadata system to automate procedures and to create an updated documentation for AdminData quality
Brussels, March 2017
NTTS 2017

4. AdminData centralized management
See 13C001 Istat presentation by Giacomi
AdminData management functions
IT TOOLS
A. Collection of AD requirements from Istat statistics producers
B. Formulation of AD requests ​​for each AD holder and for each AD source
C. AD acquisition and storing
D. Procedures to ensure data confidentiality
D. AD formal Concept Analysis/ identification of objects and relations
E. Data loading
F. AD Integration
G. Recoding
H. Dissemination to internal users
ARCAM
AD quality evaluation and documentation
SIM
EDI, SIM, ARCAM

5. SIM - The Integrated System of Administrative Microdata
SIM is the Istat Database of integrated Admin microdata built with the aim of supporting the Istat statistical production process.
Admin source subsets supplied (datasets) that contain microdata referred to statistical target units enter the system
Individuals
Economic units
Places

6. The SIM process: concept analysis
As AD comes from different sources -> different characteristics
To make data consistent with the integration system
data analysis, according to the entity-relationship model
standardized procedures for each dataset delivered periodically
data loading into relational tables (object/entity its attributes)
SIM integrates 70 different AdminData subsets each year from 2011 and is going to integrate other AdminData subsets in 2017

7. The SIM process: data loading
Aministrative objects/entities recognized as statistical target units of type k, with k=1,2,3 feed the three main
subsystems
Individuals
Economic units
Places
AdminDatasets may contain in the same instance more basic units
Individuals (families relationships)
Economic units (local units)
SIM
relations subsystems:
Individuals and Economic units (i.e. Workers Leed, Students- Schools)
Places and economic units
Places and individuals
Statistical Registers: Population/Business/Places/Activities/

8. The SIM process: integrating data [1]
The stage of Integration is incremental: as the datasets are acquired they are progressively integrated in SIM with the data already present.
Operationally, the integration of the i-th dataset is made through a series of record linkage procedures between the input dataset and the corresponding Base Bk (k=1,2,3).
Depending on the type of unit and on the AD domain defined by several criteria, a suitable integration strategy and a set of algorithms are applied.

9. The SIM process: integrating data [2]
The integration of a dataset provides many integration processes as are the types of units.
The integration stage ends with the attribution of an unique identification code (the SIM code) within the respective Base Bk, and each instance becomes part of the Base.
Units that the integration procedures do not match with others already recorded in the Base will received a new code.

10. The Base for Integration B1
YEAR
Last year of inclusion in the Base instance
ID_ADMINDATASET
Identifies the supply of the subset of an AdminSource, together with time reference, identifies the input administrative datasets.
PROGRESSIVE (OF THE ACQUIRED ADMIN_DATASET)
In hierarchy with ID_ADMINDATASET, enables connection with other data on it (other specific attributes of the units).
SIM CODE
SIM CODE derived from the integration procedures
TAX CODE
Linkage variables (Individual representation)
LAST NAME
NAME
SEX
DATE OF BIRTH
CODCAT BIRTH
PROVINCE BIRTH
MUNICIPALY BIRTH
COUNTRY BIRTH
ENTRY DATE
DEATH DATE
A2009
Reference year (dummy variables)
A2010
...
A2018
STEP
Step at which the unit is integrated into the base, as part of the integration strategy adopted for dataset
SUBSET
In case of Provisional/Final data

11. The SIM process: a step for data security
Identification variables of the individuals are stored in a separate table.
Integrated anonymized data are made available to internal users who have requested them and who are authorized to use them.
The advantage of centrally integrate data is twofold:
To allow users to link datasets simply using the SIM codes (no use of identification variables) avoiding duplicate work
To comply with legislation on data privacy

12. About AdminData quality - What is useful and for whom
 AD usability analysis function
Information on AD availability and usability
 AD monitoring function
To identify possible regulatory changes that may induce discontinuity and that are not notify in advance;
To detect the presence of unexpected lack of quality
For Istat users
Support the collection of AD requirements
Reporting on AdminData usability
AD supply monitoring function
To promptly check AD compliance with respect to data requests
For the AD acquisition process unit
Now somenthing on AdminData quality: what is useful and for whom
 Feedback to improving AD quality
To share data quality with suppliers in specified manner defined case by case.
For AD holders
NTTS 2017

13. Implementation using metadata
How to MAKE and UPDATE efficiently and timely
AD quality evaluation and documentation in a generalized way for all about 300 datasets acquired yearly by Istat corresponding to about a terabyte of data
In the context of Istat modernization – metadata-driven production paradigm
Istat IT systems contain many useful metadata
NTTS 2017

14. Useful metadata [1] DB supporting AdminData acquisition - ARCAM
Metadata to identify ADsets
Agreements for delivery with the AD holders
AD Internal Users
List of Admin datasets available (source, data holder, dataset name, periodicity)
Quality measures
Admin dataset Relevance (users, related EU regulations)
For each delivery (reference time, period)
Punctuality
Timeliness

15. Useful metadata [2] DB Oracle of the Integrated AdminMicrodata - SIM
Metadata supporting ETL and integration procedures - SISME
Variables list
Categories for categorical variables (classifications)
Kind of target units and kind of relationships available

16. Useful metadata [2] DB Oracle of the Integrated AdminMicrodata - SIM
With the aim of supporting data quality evaluation in the acquisition process (compliance analysis) a parameterized table contains for each file:
n. of records
NOT NULL values
frequency distribution for categorical variables
Technical checks for the data compliance (variables, units), quality monitoring: comparisons of the quality measures with the previous datasets delivered - to promptly contact supplier in case of serious problem
Percentage of missing values for each relevant variable (also in time series)
Metadata Completeness for Categories descriptions …

17. Record linkage quality indicators
DB Oracle of the Integrated AdminMicrodata - SIM
Metadata of the record linkage process
Bk data
Measures of Linkage variables quality (which variables are available and their quality)
Measures for monitoring quality of the integration procedures (deterministic measures)
Record linkage quality indicators (false positive and false negative) to estimate for certain values of the monitoring quality measures

18. Other useful information/metadata
ARCAM
SIM
and also
The DB that manages the National Statistical Programme, the legislative measure that define statistics production for the NSS. It holds information on AD that statistical processes can use
Measures for compliance with the rules on confidentiality)
SIQual is the information system on quality for Istat surveys (users statistics – oriented)
Measures of the response burden reduction using AD, output quality documentation about the use of AD…
SUM the Unified System of Metadata related to statistical data and processes, modelled according to GSIM. Very useful to standardize metadata and supporting the modernization process, to now used for the statistics dissemination.
Admin variables conceptual comparability (comparing input and output)

19. A critical point is Systems interoperability
Each system is designed with a specific functionality and it is necessary to define a line that connects the information
From the conceptual point of view
From the technical point of view
If possible it could be useful to share objectives among IT specialists and statisticians from the beginning, in order to standardize procedures and make metadata reusable

20. Steps and progress a. Adoption of a AdminData quality framework
b. Definition of measures within the framework
c. Deep analysis of existing processes, metadata and data flows
d. Classification of measures including
implementable in the short-term with metadata already available
implementable in the medium-term with metadata available but still not accessible
implementable in the long-term with information to acquire
Propose and support the interoperability of systems
f. Measures implementation
g. Prototype by the use of IT generalized systems – BI (Microstrategy) to produce the Quality Report

21. Metadata and Measures by dimension and implementation level
HYPERDIMENSIONS
Implementation
Total
short-term
mid-term
long-term
SOURCE 12 7 13 32
AD source definition 1 3 4
Metadata to identify dataset to acquire 5 6
Metadata to identify dataset supplied 2
Data Privacy procedure
AD source Relevance
Feedback with AD holder
METADATA 8 15
Clarity for units and variables
Comparability for units and variables
Change of Metadata over time
Data treatment by the source holder
DATA 26 29 62
Technical Checks
Accuracy  1  8  9
Completness  4
 12
Integrability/Integration 16 23
Time-related dimension 14 19 41 49
109
NTTS 2017

22. Objectives to achieve Quality report card of administrative data
For each ADset (about 300 datasets, of which 100 integrated in SIM)
A Report automatically generated using metadata and data from existing DB and periodically updated +
Other quality measures carried out by the users to share with others (coverage indicators, accuracy indicators)
Further development
First quality check of the Integrated System (Activities Register)

23. Prospects and challenges
 Improve efficiency
Improve quality
Manage complexity
Interaction with many actors
Need to comply with the processes timeliness
NTTS 2017