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Cessda Experts meet (and eat well) CESSDA Council of European Social Science Data Archives CESSDACESSDA is an informal combination of the West European.

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Presentation on theme: "Cessda Experts meet (and eat well) CESSDA Council of European Social Science Data Archives CESSDACESSDA is an informal combination of the West European."— Presentation transcript:

1 Cessda Experts meet (and eat well) CESSDA Council of European Social Science Data Archives CESSDACESSDA is an informal combination of the West European data archives with the aim of a free and intensive exchange of data. CESSDA was established in 1976 by the then existing European data archives. The President is at present Kevin Schurer from UKDA and the secretariat is held by Hans Jørgen Marker from the Danish Data Archive. Participants from 14 archives, 36 people Alfredsson, Iris (SSD)[] Alvheim, Atle (NSD)[] Aparicio Galparsolo, Carmen (ARCES)[] Bischof, Christian (WISDOM)[] Breitenstein-Leuba, Christine (SIDOS)[] Campo Gan, Isabel do (ARCES)[] Campo Ladero, Mª Jesús (ARCES)[] Clausen, Nanna Floor (DDA)[] Esclapez Pizana, Ricardo (ARCES)[] Fredzu, Christina (GSDB)[] Garrido González, Beatriz (ARCES)[] Hadorn, Reto (SIDOS) [] Hidalgo Rodríguez, Miguel Ángel[] Jääskeläinen, Taina (FSD)[] Kastrun, Tomaz (WISDOM) [] Keckman-Koivuniemi, Hannele (FSD)[] Kleemola, Mari (FSD)[] Krone, Michael (DDA)[] Laseca Arellano, Jesús (ARCES)[] Linardis, Apostolos (GSDB)[] López Cabanas, Raquel (CIS)[] Marosi, Veronika (SSD)[] Mauer, Reiner (ZA)[] Miller, Kenneth P (UKDA)[] Moschner, Meinhard (ZA)[] Mykkeltvedt, Alette (NSD)[] Rey del Castillo, Pilar (ARCES)[] Richardson, Matthew (ICPSR)[] Rodríguez Chico, Nieves (ARCES)[] Sáez de Castro, Valentina (ARCES)[] Vipavc Brvar, Irena (ADP)[] Volchkina, Natalia (SSDA)[] Watteler, Oliver (ZA)[] Weatherall, Jo (UKDA)[] Wittenberg, Marion (DANS)[]

2 Small group vs wider community “Human endeavor is caught in an eternal tension between the effectiveness of small groups acting independently and the need to mesh with the wider community. A small group can innovate rapidly and efficiently, but this produces a subculture whose concepts are not understood by others. Coordinating actions across a large group, however, is painfully slow and takes an enormous amount of communication. The world works across the spectrum between these extremes, with a tendency to start small—from the personal idea—and move toward a wider understanding over time.” Tim Berners-Lee, James Hendler and Ora Lassila The Semantic Web, Scientific American, May 2001 Madiera  Cessda

3 History, as it is known to man …. Transistors UNIVAC 1 Integrated circuits Inter- net TCP/IP Micropro- cessors IBM PC Apple MacIntosh HTML WWW Mosaic Infrastructure for the social sciences Mainframe PCInternet/WWW Java XML 194519501955196019651970197519801985199019952000 Mini CESSDA COUNCIL OF EUROPEAN SOCIAL SCIENCE DATA ARCHIVES 1960 - ZA 1962 - ICPSR 1967 - UKDA 1972 - NSD

4 Tools for thought “Much more time went into finding or obtaining information than into digesting it. ” Dr. J.C.R. Licklider time spent on digesting and thinking time spent on finding and accessing ) ( Maximize

5 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 History Future Within the Cessda framework, we have been running a focused joint project for more than 10 years CESSDA Meeting 1994 CESSDA IDC NESSTAR project FASTER Nesstar ltd Limber DDI Cessda DDI Group MadieraIDC2 = cCat Cessda MMG Group Metadater ELSST Thesaurus eSSENCE HASSET Thesaurus

6 A formulationtion of the long term ambition became the ”Point of Departure” for ”the Social Science Dream Machine” all existing empirical data available online one integrated resource discovery gateway in order to identify and locate relevant resources extensive amounts of metadata available integrated with the data data should be available in any format...and in any language the ability to carry out simple browsing, visualisation and analysis of the data on-line comparable data should easily be identified hyperlinks from the metadata to every relevant report or publication an efficient feedback system to the body of metadata allowing the user to add to the collective memory of a data source (Jostein Ryssevik/Simon Musgrave)

7 From IDC to IDC II Integrated Data Catalogue I D C Some Meta- data Meta-dataData Knowledge Knowledge IDC II= cCat

8 What is actually data ? Data is a representation of an object or a process in the “real world”. “The real World” Representation of “the real world”. DataInformationKnowledge Metadata Analysis

9 What comes out as specified MADIERA Objectives ? The development of an integrated and effective distributed social science portal to facilitate access to a range of data archives and disparate resources. WP3 The development of specific add-ons to existing virtual data library technologies, in particular data location technology WP4 The employment of a multi-lingual thesaurus to break the language barriers to the discovery of key resources. WP5 An extensive programme to add content, both at the data/information and knowledge levels. WP6 Extensive training of data providers and users to encourage the continuos growth of the infrastructure WP7 The gradual integration of the emerging national infrastructures of the new candidate countries to the EU into the European Research Area

10 A C O M M O N G A T E W A Y D A T A A R C H I V E S D A T A U S E R S Global Access - Local Support

11 Madiera portal: A second layer on top of allready existing data infrastructures Data Providers Publish data Publish metadata Add documents End User Locate data Multilingual access On-line data analysis Downloading data Browsing metadata Browsing documents Uploading “knowledge” Adding comments to metadata Adding links to publications The Madiera Infrastructure Data, + Metadata standards Multilingual thesaurus Access control User added information Publications

12 Madiera: Some keywords Timely and convenient Technology –Ease of location –Ease of access Standards Instruments Searching in text Drill-down via topical classifications Geo-referencing, geographical search Look up comparable data Online analysis Downloading possibilities DDI Implementations Nesstar Publisher, or XML editors Content requires “Politics” Access rules, legal requirements, Documentation of activity From Madiera to IDC2, inclusion of data

13 Do we tend to forget or take for granted the most important things ? Quality data is the key to quality research Standardization is the key to common solutions Success is measured through use

14 Implementations of the DDI on “The European Scene”

15 An example: A list of mandatory, recommended or optional elements DDI Codebook Outline - FieldsCommentRecommedation 2.0 stdyDscr+(ATT == access)The Study Description consists of information about the data collection, study, or compilation that the DDI-compliant documentation file describes. 2.1 citation+(ATT == MARCURI)Citation for the data collection described by the marked-up documentation. If dataproducer is not the documentation producer, then the "source" attribute should be used to distinguish. 2.1.1 titlStmt(ATT == ) titl(ATT == ) Mandatory in the original language subTitl*(ATT == ) altTitl*(ATT == ) parTitl*(ATT == ) Mandatory at least in English (UK) IDNo*(ATT == agency) (M) Mandatory 2.1.2 rspStmt?(ATT == ) AuthEnty* (ATT == affiliation) (R)The person, corporate body, or agency responsible for the data collection's substantive and intellectual content. Repeat the element for each author, and use the affiliation attribute if available Mandatory (recommended in English) othId*(ATT == type, role, affiliation) 2.1.3 prodStmt?(ATT == ) producer* (ATT == abbr, affilation, role)The producer of the data collection is the person or organization with the financial or administrative responsibility for the physical processes whereby the data collection was brought into existence. Use the role attribute to distinguish different stages of involvement in the production process. Recommended copyright? (ATT == )Copyright statement for the data collection.Recommended prodDate* (ATT == date)

16 Another example: A Common Topical Classification of Studies across Archives ECONOMICS- Economic Conditions and Indicators - Consumption/Consumer Behaviour - Economic Policy (including budget and fiscal policy, public expenditure and public revenue) - Income, Property and Investment/Saving - Rural economics - Economic Systems and Development LABOUR AND EMPLOYMENT- employment - unemployment - retirement - (in-job) training - labour relations/conflict - working conditions POLITICS- Mass political behaviour, attitudes/opinion - elections - political ideology - domestic political issues - government, political systems and organisations - international politics and organisations - conflict, security and peace

17 Multilingual Thesaurus Produced a Thesaurus for Social Science use Produced Guidelines for Thesaurus construction and translation Translations to several European languages Set up an administrative framework for additions of concepts and local extensions and future maintenance of the thesaurus

18 Content Provision Guidelines for content provision Training packs and user guides Workshops A common template for documentation work

19 Instruments: The NESSTAR Publisher or similar products

20 Technology: A somewhat expanded NESSTAR Data location technology expanded, in addition to ordinary searching in free text Searching in text in certain specific DDI elements Drill down via TopcClas or ELSST Geo-referencing, geographic search Look up comparable data

21 The present Madiera Portal 1892 datasets

22 The Madiera Portal, drill-down

23 The Madiera Portal, ELSST based


25 Expanding data availability We might find things we are not able to interpret or understand With keywords it is easier to interpret or translate Standarized keywords are better that home-made solutions

26 Geography

27 Looking up comparable data The DDI-related work on how to document comparative data has shown that this is a complicated problem Some studies are comparaTIVE by design, which means that the DDI-problem is to describe complex structures But much data open possibilities for comparison or analysis across 3.dimensions without being designed for that purpose Still it means that it is at the conceptual level we can establish the comparability, plain question wording is not enough We have to insert concepts at variable level, and we need a sophisticated but standardized vocabulary for doing it: that is – a thesaurus or ontology

28 How to pick concepts from ELSST and insert in your data documentation

29 More concepts – comparable data

30 A scheme A Finnish researcher A Swiss researcher An Irish researcher Attitudes towards immigrants (A problem area) Data on Finland (A geographic area) Eurobarometer (A data collection) AIM: Ideal end product A registration procedure, register with home archive Look up and access data across holdings

31 A ”Data-archive Political Context” for 20+ national archives I.It might be money involved  Is the data a free or commercial good ?  There are categories of users, what about non-academic use, non-CESSDA use ?  Who are to fix the prices ? II.Varying Access rules. The crossing of national borders  What laws apply. Who set the rules  Who is responsible ? What sanctions available ? III.There are some “Common good” data  Eurobarometers, Value studies, ISSP, ESS, Comparative collections  Could best be provided from one single point (?)  Charging ? Access Conditions ? Double Storage ? IV.It is a good thing to have national archives, enhances amount of data available and betters the accessibility.  Need justification and visibility

32 An integrated common data catalogue Archives formalise access policy Develop a user registration system Probably wise that archives try to standardise information collected in the user registration process Information on registered users and available data stored in a (local) user database An end user agreement with some legal status Archives accept authentication through other archives Nesstar write an extended log Every archive function as access point to the common catalogue, enhances visibility Make it possible to take out accurate statistics on use

33 A Web of Social Science Building on a distributed model where data and resources are stored and maintained locally For the end user the system will appear as a integrated system A virtual data library offering global access to locally supported data holdings End users Data providers

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