1 “Data from national surveys: access, analysis, and sharing”Professor Anthony C. Masi Provost Professor of Sociology McGill University 16 May 2007
2 Three perspectives on these issues and questionsResearcher Teacher Administrator 16 May 2007
3 Trained as a social demographer, so data sets are importantCensuses Labour force surveys Social survey Special surveys: Knowledge, Attitudes, and Practices World Fertility Survey National Demographic Surveys National Election Surveys 16 May 2007
4 Trained as a social demographer, so computers are importantIBM punch cards and card sorter various models of mainframe and mini-computers stand-alone personal computers networked personal computers various configurations of file servers with mass storage devices 16 May 2007
5 Trained as a social demographer, statistical programs are importantFortran SPSS and SAS for the mainframe Minitab, Gauss, STATA, S-plus, R-plus spreadsheets other specialised programs 16 May 2007
6 Trained as a social demographer, so I need (and expect to get) great assistance regardingData sets: How does one get the kind of data that can be turned into useful information to advance knowledge? Computers: Are there certain machines and/or configurations that best serve the needs of social scientists and data analysts? Application programs: What statistical software can be employed most efficiently to answer significant questions about the available data? 16 May 2007
7 Researcher Experiences with data sets from four countries: U.S.A.Italy Canada Sweden 16 May 2007
8 United States of AmericaCensus data Public use samples Current population survey General Social Survey Special surveys 16 May 2007
9 Italy Census data Labour force survey General social surveySpecial surveys European family panel data (Research Fellow at ISTAT) 16 May 2007
10 Canada Census data CANSIM Labour force survey General social surveySpecial surveys (StatCan with SCB) (member of the National Statistics Council) 16 May 2007
11 Sweden Labour force survey Special survey (SCB with StatCan)16 May 2007
12 By comparison Canada has the pick of the litter of this subset of world class statistical agencies: survey and sampling methodologies efficient data collection good analytics and partnerships with academia learning that access and confidentiality can go together 16 May 2007
13 Teacher: from concepts to operationalisationlearning objectives appropriate tools 16 May 2007
14 Learning objectives informed consumers capable producerscritical analysts know the difference between education and training 16 May 2007
15 Appropriate tools classroom and computer laboratory structuressocial statistics lab, faculty computer facilities, electronic data resource services software tools local, networked, server-based applications and appropriate site-licensing arrangements the right stuff: data on demand campus-based research data centre 16 May 2007
16 Administrator support alliances data issues training models16 May 2007
17 Support the right initiatives at the right timewith the right level of resources delivery of data services 16 May 2007
18 Alliances funding agencies statistical agenciesuniversities and research institutes 16 May 2007
19 Data issues infrastructure requirements repositoriesstoring and preserving data data preservation and distribution privacy, confidentiality, anonymity access complex survey designs and statistical analysis 16 May 2007
20 Training and support: professional best practiceslibraries and librarians data liberation initiative special purpose centres social statistics labs and RDCs special courses and instruction summer data and statistics programs on-line: any time, any where, any device CANSIM 16 May 2007
21 Models sharing and distributing “middleware” for identity managementICPSR example public opinion data archives institutional repositories “middleware” for identity management 16 May 2007
22 Canada’s Research data centre (RDC) initiative (1)promote and facilitate social science research provide secured access to Statistics Canada confidential micro-data survey files protect confidentiality of respondents disseminate findings of research to the policy community and the public costs and benefits balanced SSHRCC, CIHR, CFI, STATCAN, universities social research capacity 16 May 2007
23 Canada’s Research Data Centre (RDC) initiative: benefits (2)generate a wide perspective on Canada’s social landscape develop a network of research centres build on the data liberation initiative and expand collaboration train a new generation of Canadian data specialists 16 May 2007
24 Canada’s Research data centre (RDC) initiative: data sets (3)Aboriginal people’s survey Canadian community health survey Ethnic diversity survey General social survey Longitudinal survey of immigrants to Canada National graduates survey 16 May 2007
25 Canada’s Research data centre (RDC) initiative: data sets (4)National longitudinal survey of children and youth National population health survey Participation and activity limitation survey Survey of labour and income dynamics Workplace and employee survey Youth in transition survey 16 May 2007
26 The role of IASSIST (1) three communities advanced infrastructuresresearchers information specialists computer experts advanced infrastructures knowledge transfer 16 May 2007
27 The role of IASSIST (2) education outreach advocacyprofessional development opportunities Initiatives outreach partnerships advocacy access to data data documentation digital preservation 16 May 2007
28 Discussion progress and challenges information overloadwhat we have and how it compares data definitions content searching formats archives web-based initiatives quality assurance issues and metrics 16 May 2007
29 Have a productive and fun conference. Enjoy McGill and Montreal.Thank you. Have a productive and fun conference. Enjoy McGill and Montreal. 16 May 2007