Emily Witt (INEXDA, ECB) 14 November 2018 International Network for Exchanging Experience on Statistical Handling of Granular Data (INEXDA) Emily Witt (INEXDA, ECB) 14 November 2018

INEXDA‘s General Mission INEXDA is an open network to exchange experiences on statistical handling of granular data for central banks, national statistical institutes and international organisations INEXDA aims at investigating possibilities to harmonise access procedures and metadata structures developing comparable structures of existing data and further fostering efficiency of statistical work with granular data Ultimately, in line with G20 Data Gaps Initiative, INEXDA aims to facilitate use of granular data for analytical, research and comparative purposes by users within and outside the participating institutions, within the limits set by the applicable confidentiality regimes.

INEXDA: The Granular Data Network founded by 5 central banks on 6 January 2017 others joined: guests: Central banks of AT, CH, MX, RU BIS, Eurostat NSIs of DE, UK

Work Programme for the first two Years 1. Inventory of data in all member institutions 2. Inventory of existing data access procedures 3. Dissemination of INEXDA results Agreement on unified metadata schema Setup of a platform to collect and exchange metadata Start harmonising metadata across INEXDA members ECB pilot collection of information on access for researchers ADRF for INEXDA proposed by Julia Lane (NYU) Workshop on data access in Q1 2019 Presentations at conferences Website

How to join INEXDA Participation in INEXDA is open to other central banks, statistical institutes and international organisations. INEXDA is governed by an MoU, that every member has to sign. Sharing of granular data between INEXDA members not part of this MoU. Interested institutions can join as guests before becoming a member.

Thank you for your attention! Contact: INEXDA.secretary@bundesbank.de

References INEXDA is governed by a Memorandum of Understanding Ninth IFC Conference "Are post-crisis statistical initiatives completed?“ – INEXDA papers Presentation: INEXDA - The granular data network Presentation: An introduction to INEXDA's metadata schema Working Paper: INEXDA - the Granular Data Network IFC reports on data-sharing: issues and good practices the sharing of micro data – a central bank perspective Recommendation # II.20 of the G20 Data Gaps Initiative http://www.fsb.org/wp-content/uploads/Second-phase-of-the-G20-Data-Gaps-Initiative-DGI-2-First-Progress-Report.pdf (page 40) http://www.bundesfinanzministerium.de/Content/EN/Standardartikel/Topics/Featured/G20/g20-communique.pdf;jsessionid=CF74A1983810F30E7D6EECA63397797E?__blob=publicationFile&v=3 (page 5, bullet point 15) Proceedings of the G20 Workshop on Data Sharing (January 31-February 1, 2017) and related IAG report http://www.principalglobalindicators.org/?sk=E30FAADE-77D0-4F8E-953C-C48DD9D14735&sId=1433357451568

INEXDA is gaining momentum… 1st INEXDA meeting in Lisbon 2nd INEXDA meeting in London 3rd INEXDA meeting in Paris 4th INEXDA meeting in Basel INEXDA members (+CL, ECB, ES, TR) Guests: AT, CH, BIS, DE (NSI), Eurostat, MX, RU, UK (NSI) INEXDA members (DE, FR, IT, PT, UK) Guests: BIS INEXDA members (DE, FR, IT, PT, UK) Guests: BIS, ECB, ES INEXDA members (+ECB, ES) Guests: AT, BIS, CL, MX, TR, UK (NSI) Jan 2017 Jul 2017 Jan 2018 Aug 2018 Memorandum of Understanding Signing and publication INEXDA Metadata Tool by GESIS Working groups Dissemination Metadata ADRF Modes of accreditation Contracts for research projects/bodies Modes of data provision Output control Risk management for published results

INEXDA’s Metadata Schema 1 Resource Type 2 Resource Identifier 3 Name of Dataset 4 Creator 5 DOI Proposal 6 URL 7 Language of Resource 8 Publication Date 9 Availability 10 Sampled Universe 11 Sampling 12 Temporal Coverage 13 Time Dimension 14 Collection Mode 15 Unit Descriptions 16 Descriptions 17 Geographical Coverage 18 Keywords 19 Alternative Identifiers 20 Relations 21 Publications Purpose is to foster harmonisation between INEXDA members and broaden metadata sharing within INEXDA and possibly outside Based on the GESIS DOI registration service da|ra (GESIS is cooperating with DataCite). https://www.da-ra.de/en/home Name of metadata items closely follows da|ra conventions to enable seamless DOI registration, if desired later in the project. Basis for INEXDA metadata database that was established to store and view metadata from INEXDA members.

Digital Object Identifier (DOI) DOIs are permanent and persistent identifier which is unique and cannot be deleted. DOIs are a simple character string which provides a link to a resource. In Germany DOIs are provided by the GESIS DOI registration service da|ra (GESIS is cooperating with DataCite). https://www.da-ra.de/en/home

Part 1: Basic Information Resource Type 2 Resource Identifier 3 Name of Dataset 4 Creator 5 DOI Proposal 6 URL 7 Language of Resource 8 Publication Date 9 Availability 10 Sampled Universe 11 Sampling 12 Temporal Coverage 13 Time Dimension 14 Collection Mode 15 Unit Descriptions 16 Descriptions 17 Geographical Coverage 18 Keywords 19 Alternative Identifiers 20 Relations 21 Publications Creator is a mandatory item in da|ra. May be used to provide more granular information on the data compiler URL refers to the webpage which displays information about the dataset Availability (controlled) describes the procedure under which the data can be accessed (eg download or on-site) DOI Proposal provides the suggested DOI name of the dataset. A Digital Object Identifier (DOI) is a permanent, persistent identifier used for citing and tracking datasets

Part 2: Methods 1 Resource Type 2 Resource Identifier 3 Name of Dataset 4 Creator 5 DOI Proposal 6 URL 7 Language of Resource 8 Publication Date 9 Availability 10 Sampled Universe 11 Sampling 12 Temporal Coverage 13 Time Dimension 14 Collection Mode 15 Unit Descriptions 16 Descriptions 17 Geographical Coverage 18 Keywords 19 Alternative Identifiers 20 Relations 21 Publications Sampling displays the type of sample design used to select the observations to present the population Time Dimension provides information on frequency of observations. whether dataset structure is panel, time-series or cross-sectional Structural breaks are defined as major events and revisions that have impacted the dataset Examples of structural breaks include: changes to the time frequency with which data is collected changes to the set of collected variables changes in the population or sampling

Part 3: Descriptions 1 Resource Type 2 Resource Identifier 3 Name of Dataset 4 Creator 5 DOI Proposal 6 URL 7 Language of Resource 8 Publication Date 9 Availability 10 Sampled Universe 11 Sampling 12 Temporal Coverage 13 Time Dimension 14 Collection Mode 15 Unit Descriptions 16 Descriptions 17 Geographical Coverage 18 Keywords 19 Alternative Identifiers 20 Relations 21 Publications Unit Description provides information on the entities that are being observed in the dataset Datasets may contain more than one unit of observation. For example, in a credit register information on the following units are collected: Banks Companies Governments Loans Descriptions also contains detailed information on structural breaks in the dataset

Part 4: Relations and Publications 1 Resource Type 2 Resource Identifier 3 Name of Dataset 4 Creator 5 DOI Proposal 6 URL 7 Language of Resource 8 Publication Date 9 Availability 10 Sampled Universe 11 Sampling 12 Temporal Coverage 13 Time Dimension 14 Collection Mode 15 Unit Descriptions 16 Descriptions 17 Geographical Coverage 18 Keywords 19 Alternative Identifiers 20 Relations 21 Publications Describes relations between datasets and databases in the INEXDA metadata database… … in a given country … across countries Examples of use cases in INEXDA context Relation between datasets containing similar units (in different countries). Dataset feeds into a ECB dataset. Publications provides information on scientific publications related to the dataset.

ADRF for INEXDA proposed by Julia Lane (New York University) – The five modules (1|2) 1 ADRF Documentation Module Provides metadata incl. data catalogue, ownership & access Shows missing / distribution values Links users, authors, research products, codes and tools and data producers Allows researchers to annotate datasets and provide codes to read in and reuse data ADRF Collaboration Module Collaboration and resource sharing via shared project workspaces and social tools (e.g. interactive chat, questions and answers, code sharing) Supports analysis workflows with self-documenting, sharable code files 2 ADRF Security Module Security is implemented in three layers: Cloud infrastructure, operational security and application layer security (FedRAMP certified) Data security and confidentiality is enforced at the level of all 5 Safes: 3 People Projects Data Environment Results

The Administrative Data Research Facility (ADRF) holistic user centric data approach Security Module FedRAMP security certified Data in cloud Alternative: local servers Data producer Metadata Training Module Data Data analysis Code Collaboration Documentation Module Explorer links metadata, codes, tools, publications Collaboration Module Interactive chat and code sharing Workspace and tools Stewardship Module Approval workflow, monitoring, reporting Usage Feedback Data steward Access Workflows Monitoring Reporting Data user