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New Social Science Data Infrastructure for Ontario Libraries

July 25, 2007 in academia, Access, canada, datasets, infrastructure, Uncategorized by Tracey | Permalink

I met with Wendy Watkins at the Carleton University Data Library Carleton University Data Library yesterday. She is one of the founders and current co-chair of DLI and CAPDU (Canadian Association of Public Data Users), a member of the governing council of the International Association of Social Science Information Service and Technology (IASSIST) and a great advocate for data accessibility and whatever else you can think of in relation to data.

Wendy introduced me to a very interesting project that is happening between and among university libraries in Ontario called the Ontario Data Documentation, Extraction Service Infrastructure Initiative (ODESI). ODESI will make discovery, access and integration of social science data from a variety of databases much easier.

Administration of the Project:

Carleton University Data Library in cooperation with the University of Guelph. The portal will be hosted at the Scholar’s Portal at the University of Toronto which makes online journal discovering and access a dream. The project is partially funded by the Ontario Council of University Libraries (OCUL) and OntarioBuys operated out of the Ontario Ministry of Finance. It is a 3 year project with $1 040 000 in funding.

How it works:

ODESI operates on a distributed data access model, where servers that host data from a variety of organizations will be accessed via Scholars’ Portal. The metadata are written in the DDI standard which produces XML. DDI is the

Data Documentation Initiative [which] is an international effort to establish a standard for technical documentation describing social science data. A membership-based Alliance is developing the DDI specification, which is written in XML.

The standard has been adopted by several international organizations such as IASSIST, Interuniversity Consortium for Political and Social Research (ICPSR), Council of European Social Science Data Archives (CESSDA) and several governmental departments including Statistics Canada, Health Canada and HRSDC.

Collaboration:

This project will integrate with and is based on the existing and fully operational Council of European Social Science Data Archives (CESSDA), which is cross boundary data initiative. CESSDA

promotes the acquisition, archiving and distribution of electronic data for social science teaching and research in Europe. It encourages the exchange of data and technology and fosters the development of new organisations in sympathy with its aims. It associates and cooperates with other international organisations sharing similar objectives.

The CESSDA Trans-Border Agreement and Constitution are very interesting models of collaboration. CESSDA is the governing body of a group of national European Social Science Data Archives. The CESSDA data portal is accompanied by a multilingual thesaurus, currently 13 nations and 20 organizations are involved and data from thousands of studies are made available to students, faculty and researchers at participating institutions. The portal search mechanism is quite effective although not pretty!

In addition, CESSDA is associated with a series of National Data Archives, Wow! Canada does not have a data archive!

Users:

Users would come to the portal, search across the various servers on the metadata fields, access the data. Additionally, users will be provided with some tools to integrate myriad data sets and conduct analyses with the use of statistical tools that are part of the service. For some of the data, basic thematic maps can also be made.

Eventually the discovery tools will be integrated with the journal search tools of the Scholar’s Portal. You will be able to search for data, find the journals that have used that data or vice versa, find the journal and then the data. This will hugely simplify the search and integration process of data analysis. At the moment, any data intensive research endeavour or data based project needs to dedicate 80-95% of the job to find the data from a bunch of different databases, navigating the complex licensing and access regimes, maybe pay a large sum of money, organizing the data in such a way that it is statistically accurate then make those comparisons. Eventually one gets to talk about results!

Data Access:

Both the CESSDA data portal project and ODESI are groundbreaking initiatives that are making data accessible to the research community. These data however will only be available to students, faculty and researchers at participating institutions. Citizens who do not fall into those categories can only search the metadata elements, see what is available but will not get access to the data.

Comment:

It is promising that a social and physical infrastructure exists to make data discoverable and accessible between and among national and international institutions. What is needed is a massive cultural shift in our social science data creating and managing institutions that would make them amenable to the creation of policies to unlock these same public data assets, some of the private sector data assets (Polls, etc.) and make them freely (as in no cost) available to all citizens.

Cost Recovery Policies are NOT Synonymous with Data Quality

July 17, 2007 in academia, Access, datasets, infrastructure, policy, Uncategorized by Tracey | Permalink

One of the great data myths is that cost recovery policies are synonymous with higher data quality. Often the myth making stems from effective communications from nations with heavy cost recovery policies such as the UK who often argue that their data are of better quality than those of the US which have open access policies. Canada, depending on the data and the agencies they come from is at either end of this spectrum and often in between.

I just read an interesting study that examined open access versus cost recovery for two framework datasets. The researchers looked at the technical characteristics and use of datasets from nations of similar socio-economic, jurisdiction size, population density, and government type (Netherlands, Denmark, German State of the North Rhine Westfalia, US State of Massachusetts and the US Metropolitan region of Minneapolis-St. Paul). The study compared parcel and large scale topographic datasets typically found as framework datasets in geospatial data infrastructures (see SDI def. page 8). Some of these datasets were free, some were extremely expensive and all under different licensing regimes that defined use. They looked at both technical (e.g. data quality, metadata, coverage, etc.) and non-technical characteristics (e.g. legal access, financial access, acquisition procedures, etc.).

For Parcel Datasets the study discovered that datasets that were assembled from a centralized authority were judged to be technically more advanced while those that require assembly from multiple jurisdictions with standardized or a central institution integrating them were of higher quality while those of multiple jurisdictions without standards were of poor quality as the sets were not harmonized and/or coverage was inconsistent. Regarding non-technical characteristics many datasets came at a high cost, most were not easy to access from one location and there were a variety of access and use restrictions on the data.

For Topographic Information the technical averages were less than ideal while for non-technical criteria access was impeded in some cases due to involvement of utilities (tendency toward cost recovery) and in other cases multiple jurisdictions – over 50 for some – need to be contacted to acquire a complete coverage and in some cases coverage is just not complete.

The study’s hypothesis was:

that technically excellent datasets have restrictive-access policies and technically poor datasets have open access policies.

General conclusion:

All five jurisdictions had significant levels of primary and secondary uses but few value-adding activities, possibly because of restrictive-access and cost-recovery policies.

Specific Results:

The case studies yielded conflicting findings. We identified several technically advanced datasets with less advanced non-technical characteristics…We also identified technically insufficient datasets with restrictive-access policies…Thus cost recovery does not necessarily signify excellent quality.

Although the links between access policy and use and between quality and use are apparent, we did not find convincing evidence for a direct relation between the access policy and the quality of a dataset.

Conclusion:

The institutional setting of a jurisdiction affects the way data collection is organized (e.g. centralized versus decentralized control), the extent to which data collection and processing are incorporated in legislation, and the extent to which legislation requires use within government.

…We found a direct link between institutional setting and the characteristics of the datasets.

In jurisdictions where information collection was centralized in a single public organization, datasets (and access policies) were more homogenous than datasets that were not controlled centrally (such as those of local governments). Ensuring that data are prepared to a single consistent specification is more easily done by one organization than by many.

…The institutional setting can affect access policy, accessibility, technical quality, and consequently, the type and number of users.

My Observations:
It is really difficult to find solid studies like this one that systematically look at both technical and access issues related to data. It is easy to find off the cuff statements without sufficient backup proof though! While these studies are a bit of a dry read, they demonstrate the complexities of the issues, try to tease out the truth, and reveal that there is no one stop shopping for data at any given scale in any country when it comes to data. In other words, there is merit in pushing for some sort of centralized, standardized and interoperable way – which could also mean distributed – to discover and access public data assets. In addition, there is an argument to be made to make those data freely (no cost) accessible in formats we can readily use and reuse. This of course includes standardizing licensing policies!

Reference Institutions Matter: The Impact of Institutional Choices Relative to Access Policy and Data Quality on the Development of Geographic Information Infrastructures by Van Loenen and De Jong in Research and Theory in Advancing Data Infrastructure Concepts edited by Harlan Onsrud, 2007 published by ESRI Press.

If you have references to more studies send them along!

Fun with Taxpayer Dollars: Purchasing Census Data Many Times

July 13, 2007 in Access, canada, datasets, government by Tracey | 2 comments

What is the cost to taxpayers of public institutions purchasing public data? As citizens we do not like to pay for the same thing many times. So here is a real scenario and an estimated best guess of the #s on the cost to taxpayers for public data which they pay for many times via their public institutions whose job it is to work for the public interest and re-purchase data citizens have already paid for once in taxation:

a) Each Canadian municipality, city or town purchases demographic data from Statistics Canada. Lets suggest there are approximately 2000 of these entities. Lets say they each purchase a subset of the Census at varying scales, with a specialized geography to match their boundaries, so lets say they each spend conservatively $ 10 000 each (factoring that some small towns will buy less and others more).

2000 Towns/municipalities/cities * $ 10 000 = $ 20 000 000

b) Since many cities/towns/municipalities do not have efficient data infrastructures to manage their data assets, sometimes different departments purchase the same data twice or three times. So you may get planning, health and social welfare departments each purchasing the same data and not sharing as they are unaware and there is no central accessible repository they can mutually search. So lets pretend that the top 100 (conservative #) cities in Canada purchase the same/similar data 3 times each. We already included one purchase once above but we will keep to 3 as potentially some have purchased 4 times while the other 2900 units may have done so at least once.

100 Towns/municipalities/cities * 3 (duplicate copies of the same data) * $ 10 000 = $3 000 000

c) The best part, often each of these Towns/municipalities/cities are purchasing data for their entire respective provinces as they wish to do some cross comparisons. This means that each of these entities is paying each for the exact same/similar data set each time! Dam! Talk about a non-rivalrous good and how smart is StatCan? Dam we thought the public service did not have a corporate mindset!

d) The Provinces and Territories also each purchase Census data. They do not necessarily have a centralized data infrastructure either, they have bigger bureacracies, more departments, more specialized needs and bigger data requirements. So lets suggest that each Province and Territory spends $ 15 000 * 5 duplicate/similar sets, and an additional each $ 10 000 on multiple special orders between censuses.

13 Provinces/Territories * $ 15 000 * 5 = $ 975 000

13 Provinces/Territories * $ 10 000 = $ 130 000

d) Again many of the Provinces and Territories will purchase National scale datasets for comparison purposes, which like Towns/municipalities/cities are purchasing the exact same/similar copy of the exact same/similar data sets for the exact same geography numerous time. Recall the great part about information is its non-rivalrousness! We can each consume the same entity many times and none will suffer as a result. Unless of course you are a Canadian Tax Payer.

e) Then we have the Federal Government with approximately 350 departments and agencies and lets say each purchases some city data, some provincial data and a whole bunch of national data for $ 17 000 each. Then many, lets say 175 of these departments and agencies are purchasing special ordered data set to meet their particular needs, each at $ 7 500.

350 Federal Departments and Agencies * $ 17 000 = $ 5 950 000

175 Federal Departments and Agencies * $ 7 500 = $ 1 312 500

TOTAL:

  1. 2000 Towns/municipalities/cities * $ 10 000 = $ 20 000 000
  2. 100 Towns/municipalities/cities * 3 (duplicate copies of the same data) * $ 10 000 = $3 000 000
  3. 13 Provinces/Territories * $ 15 000 * 5 = $ 975 000
  4. 13 Provinces/Territories * $ 10 000 = $ 130 000
  5. 350 Federal Departments and Agencies * $ 17 000 = $ 5 950 000
  6. 175 Federal Departments and Agencies * $ 7 500 = $ 1 312 500

Grand Total of Census Data Expenditures by Taxpayers via Public Institutions in Canada: $ 31 367 500

The above is conservative number as it does not include the human resource expenditures like the following:

  1. Person hours associated for each public servant to negotiate and discuss their data needs
  2. Person hours for the StatCan officials to fill in the orders
  3. Person hours of the public servant lawyers to take care of licensing
  4. Person hours associated with all of the purchasing and accounting work to pay for, acquire and account for this money
  5. Person hours for each official who has to work the data in the same way to meet their needs
  6. Dunno if public agencies pay taxes on these! That would add insult to injury would it not?

It is also important to note, that hospitals, school boards, universities, crown corporations and a host of other quasi public institutions are doing the same thing. And that these numbers are only for census data, these do not include the cost of other datasets like road networks, water quality, maps, environment data and so on.

Would seem to me that we could spend a fraction of that cost to deliver the data online to all of these institutions, private sector, NGOs, and Citizens and we would all be better off financially. We would waive all the administration costs, and the license management costs, and we would all be smarter to! Further, we could reinvest that money into more research, air quality infrastructure, healthcare, waive recreation fees in municipalities etc. We could reinvest wisely in quality of life and know more how to do so at the same time.

PS-If anyone has:

  • come across any type of cost analysis reports etc.
  • has a better way to calculate this
  • knows of some real costs

Please pass them along! The more we have on this the better.

Canadians growing a little greener, StatsCan survey suggests

July 12, 2007 in Access, canada, datasets by Tracey | 1 comment

Looks like some of us are using less pesticides, purchasing a few more energy efficient and water conservation devices, composting only very slightly more than before, and it seems we dunno what to do with our toxic waste, we still throw out medicines and electronics in the regular curb pick up and we still commute to work one person per car which is too bad since

Passenger transportation accounts for about 12 per cent of Canada’s greenhouse gas emissions and efforts to improve efficiency are a high-profile part of the global warming debate.

Also, sadly we drink way more bottled water than is necessary in a country with an excellent drinking water infrastructure.

It would be great to get a hold of the raw data and play with it. It could be mapped and studied with other variables like income, city versus rural, ethnicity, mother tongue, population density, etc. This type of analysis could help target campaigns in certain under-performing areas and study why others are doing better.

Sources:

Statistical Data in Schools and Public Libraries

July 11, 2007 in Access, canada, datasets, infrastructure by Tracey | Permalink

Datalibre.ca received and excellent comment on the DLI post about access to some of the Statistics Canada data in schools and public libraries. Today I am looking at E-STAT online and am quite impressed – but alas I have not yet gone to a public library to check out what is actually there and what I can do. Nor do I know the limitations of CANSIM data. I did however speak on the phone with a fine librarian at the Main Ottawa Public Library this morning and look forward to digging for data later on today or tomorrow.

E-STAT is:

Statistics Canada’s interactive learning tool designed with the needs and interests of the education community in mind. E-STAT offers an enormous warehouse of reliable and timely statistics about Canada and its ever-changing people.

Using approximately 2,600 tables from CANSIM*, track trends in virtually every aspect of the lives of Canadians. Updated once a year during the summer, CANSIM contains more than 36 million time series.

Hundreds of schools across the country and Depository Service Program Libraries make these data accessible if you go in person to access them. You can get access to these data online only if you are registered with one of these institutions.

The E-STAT license on the data are quite restrictive.

The Government of Canada (Statistics Canada) is the owner or authorized licensee of all intellectual property rights (including copyright) in the data product referred to as E-STAT. Statistics Canada grants the educational institution a non-exclusive, non-assignable and non-transferable licence to use the data product subject to the terms below.

…

The data product supplied under this agreement shall at all times remain under the control of the institution. It may not be sold, rented, leased, lent, sub-licensed or transferred to any other institution or organization, and may not be traded or exchanged for any other product or service. The data product may not be used for the personal or commercial gain of any authorized user, nor to develop or derive for sale any other data product that incorporates or uses any part of this data product.

The data that are made available are Yearly updated Canadian Socio-economic Information Management System (CANSIM) data, the daily updates are sold for commercial purposes. I am also not sure how fine the geography is for E-STAT data, for instance if the data are available by Dissemination Blocks, Dissemination Area or, Census Tract, or Urban Areas (Note the cost associated with these and other maps). These make a difference, since DB is the finest granularity, DA is a larger neighbourhood level while CT covers a larger areas, while UAs are larger still. Each scale is for a different level of analysis and the boundaries if you aggregate any of these do not necessarily line up. Additionally, DB and DA are only for the 2006 Census while CT and UA are for others. I am guessing E-STAT is CT Scale data and larger.

E-STAT also has some census data, agricultural data, aboriginal survey data, some environmental data and health behaviour data for school aged children. Clearly not all the data are available and certainly not the specialized surveys such as business, waste management, household spending surveys, health, the survey of particular sectors etc. The data come with explanations, and teachers and users guides.

Lets see what we can get once I make a visit!

Why should government spatial data be free?

July 4, 2007 in Access, infrastructure, openmovement, Uncategorized by Tracey | 2 comments

I tripped over this yesterday while looking for some arguments for and against cost recovery. The arguments are quite good and comprehensive. If any of you can think of more send them to the civicacces.ca list or leave comments here.

This texte I believe was put together by Jo Walsh and colleagues as they were preparing positions for the INSPIRE Directive that became official May 7, 2007. Public Geo Data put together a great campaign, an online petition, a discussion list and superb material to lobby EUROGI for Free and Open Access to Geo Data. At the time the UK was pushing heavily for the Ordnance Survey‘s extreme cost recovery model for the EU while other European nations were working towards more open and free access models. You can read more about it by going through the archive of their mailing list.

Here is the full text for Why Should Government Spatial Data be Free?

The Data Liberation Initiative (DLI)

June 28, 2007 in Access, Uncategorized by Tracey | 5 comments

I’m going to feature some Canadian data access projects and people working with data in Canada that I find interesting and important on datalibre.ca . Here is my first go at it. Hope you like it! It is about a great program called the Data Liberation Initiative (DLI) that was formally instituted in 1996. I greatly benefited from the DLI as an undergraduate student studying Geomatics at Carleton University.

Tracey

************
Did you know that until the latter half of the 1990s students and faculty in Canadian Universities had to pay for Canadian Demographic Data that were collected with the use of their own tax dollars? Well it’s true! If students and faculty wanted access to Statistics Canada data to conduct any kind of demographic analysis, to study the labour market, or issues related to income and poverty, explore provincial migration patterns etc. they had to pay exorbitant amounts. What was the effect? Canadian students became US experts since their data were free and worse policy decisions for Canadians were based on US data! The real knowledge and social cost of Data Cost Recovery policies can never be recovered!

Why access to Canadian public data?

I think Professor Paul Bernard, Chair, Advisory Committee on Social Conditions (Statistics Canada) and member of the National Statistics Council said it well back in 1991:

…the genuine exercise of democracy increasingly requires that citizens get access to complex information and have the skills required to understand it.” While he realizes there are pressures on Statistics Canada to reduce costs and increase income, he feels the outcome has been the restriction of “…access to information only to groups that have the solid ability to pay.” Bernard feels that this may “…hamper the participation in public debates of groups whose contribution is not backed up by much money” as well as “those who have no prospect of turning a profit or reaping some tangible and relatively immediate benefit from using it.” This, he states, is “…likely to lead, in the long run, to suboptimal development and less than full-blown democracy.” (see Watkins).

Interestingly, since 1927 the Government of Canada did have a program to share Government information via the Depository Services Program (DSP) which is

an arrangement with some 680 public and academic libraries to house, catalogue and provide reference services for the federal government publications they acquire under the Program. These depositories must make their DSP collections available to all Canadians and for interlibrary loans. DSP also includes depositories such as Parliamentarians, central libraries of the federal government departments and press libraries.

The DSP however does not include the dissemination of public data files or databases collected and managed by the Government of Canada. Data users were and still are considered a special interest group. Odd! Numerate Canadian citizens a special interest group? Imagine literate Canadian citizens being considered a special interest group! Anyway, this meant that independent analysis on a variety of topics important to Canadians was left unquestioned, unstudied, ignored and unknown. Not the best scenario for a democracy or a knowledge based economy let alone for the promotion and growth of a numerate workforce and citizenry.

Fortunately, in 1993 we see the early formation of the Data Liberation Initiative (DLI). An early working group consisting of researchers, data librarians and representatives from Canadian Association of Research Libraries (CARL) and Canadian Association of Public Data Users (CAPDU) , Statistics Canada and the DSP as well as members of the Social Science Federation of Canada (SSFC) got together and held a series of meetings. In 1995 Statistics Canada gave the DLI its formal blessing and the DLI received Treasury Board approval in1996.

What is the Data Liberation Initiative?

The DLI a data purchasing consortium between Canadian Universities and Statistics Canada. Large universities pay $12,000 per year and smaller universities pay $3,000. The Treasury Board of Canada, Industry Canada, Health Canada, Human Resources Development Canada, Social Sciences and Humanities Research Council of Canada, Medical Research Council of Canada and Statistics Canada also financially contribute. These institutions subscribe to the service.

The DLI provides

affordable and equitable access to the standard data products listed in the Statistics Canada Catalogue through an annual subscription fee. The terms of agreement specified in the DLI license place conditions on the use of products disseminated through this program. These restrictions are directed at stopping the redistribution of data received through this channel and protecting against the loss of sales to non-educational markets for Statistics Canada, which is known within Statistics Canada as “leakage”. The license allows the use of DLI data for non-profit, academic research and instruction. Access to statistical information through DLI does require student or staff affiliation with a DLI member institution. While students and staff do not have to pay directly for access, DLI does require mediated services to disseminate statistical and data products on local campuses.

How does it works:

Students and Faculty go to their respective data libraries , consult with the data librarian, sign a use agreement in plain english a DLI Data Use License, access the data via a dedicated computer and download what they need.

The Infrastructure:

An elaborate organizational structure with very dedicated members is in place with a data delivery technical infrastructure that includes a web site, an FTP service, CDRom data delivery service and a special order process. In addition each participating university institutes a ‘data service’ which assumes responsibility for DLI at their site. The project is also glued together with two listserves. The data files are delivered in ASCII formats with associated metadata discoverable using StatCan Software at dedicated workstations in the Library.

Critical Note:

The DLI was and is the best possible reaction and compromise to the very restrictive data cost recovery policies initiated in 80s that remain alive and well with us today. It is important to repeat that these public data have already been paid for by taxation, they are re-paid for with tuition and DLI data access is restricted only to Canadians who are university students and faculty. The DLI solved one very important Canadian knowledge creation and dissemination issue in academic institutions but not the broader issue of access to data by Canadian citizens. They did set a precedent!

Statistics Canada data are still sold to Federal Departments, Provincial Governments and Municipal Governments who are not allowed to share between and among them due to very stringent licensing regimes. Our taxes have paid for many of the same datasets multiple times since these are government purchases and transactions. Just think of all the bureaucracy to manage these license regimes, royalties, the lawyers, purchasing and accounting services, storage, and so on. In addition civil society organizations such as Non Governmental Organizations, Non Profit Organizations, Community Based Researchers etc. who are not wealthy yet fulfill an important democratic function cannot afford these data while it is their role to keep government accountable on a variety of issues (e.g. Environment, Homelessness, Education etc.). Further citizens who want to learn about their communities, develop a community plan or start a new business want access to data but can only do so if they have a significant amount of cash to do so. The result – a lack of informed decision making.

Dream Idea:

It would be fantastic to have the knowledge, training and infrastructure of the DLI extended to all of our public libraries and community access points. Imagine knowledge one stop shopping – picking up a video, a music CD, a novel and some demographic data related to school closures in your neighbourhood – Wow! Of course, the data should be at no cost to the citizen nor the library. Also, imagine having a data librarian in every library that can help citizens find the data they need and helping them learn how to use them? Now that is a knowledge Society.

References:

You can access the documents I referred to here – my del.icio.us – tagged with datalibre civicaccess and DLI.

Continuum of Access, By Chuck Humphrey, University of Alberta.

Charles Humphrey (2005). Collaborative Training in Statistical and Data Library Services: Lessons from the Canadian Data Liberation Initiative. Resource Sharing & Information Networks, Vol. 18 (1/2), pp. 167-181.

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