My writings on eGovernment
Assessment is part of the
United Nations Public
Administration Network.
It is available as a
blog on eGovernment Assessment 
.
My writings on eGovernment
Assessment is part of the
United Nations Public
Administration Network.
It is available as a
blog on eGovernment Assessment .
The Web Content Accessibility Guidelines (WCAG 1.0) was launched in 1999 and was followed up by WCAG 2.0 in 2008. These guidelines have been the de facto standard for how to make web sites accessible for all people, including people with special needs.
During the 9 year period from 1999 from 2008, many measurement methodologies for WCAG 1.0 was created. Furthermore, many national and international surveys have benchmarked the accessibility of public web sites according to WCAG 1.0. Since WCAG 2.0 differ from WCAG 1.0 in significant ways, the existing measurement methodologies cannot easily be translated to WCAG 2.0. Thus, very few applications for evaluation according to WCAG2.0 has been produced. Only two tools claiming to be WCAG 2.0 compliant are known to the authors: AChecker and TAW. The details of these tools are not known.
A paper titled Evaluating Conformance to WCAG 2.0: Open Challenges (Alonso, Fuertes, Gonzalez, Martínez) presented the remaining challenges of measuring accessibility of public web sites according to WCAG 2.0. In this paper, the authors identify the main challenges with measuring measuring accessibility in web sites in accordance to WCAG 2.0. The lessons have been learned by applying WCAG 2.0 tests in practice by university students.
The paper identifies the following challenges. The described challenges are in the authors experience unclear parts WCAG 2.0, which often means that the testers need interpret the texts and take decisions of how it should be understood. This could easily lead to inconsistency among testers as the testers may understand the texts differently.
WCAG 2.0 describes that only accessibility supported technologies can be relied upon for accessibility. It further states that the technology is accessibility supported only when user’s assistive technology will work with it. Since no list of supported technologies is provided, nor any formal way to measure if a technology is supported or not, this causes a challenge. There are no established method of saying that using one technology is accessibility, while using another is not.
WCAG 2.0 consists of testable techniques. A technique is testable if it can be tested ether with machine or by human judgment. It is believed that around 80% of the criteria are testable by humans. However, the authors show that some of the description of the techniques for testing causes confusion. For example: in the sentences, “the test the sequence of elements should be meaningful”, it is not evident what is meant by the wording meaningful. What is understood as “meaningful sequence of elements” for one person may not be meaningful for others. This is likely to cause confusion, which leads to inconsistency in any testing results.
WCAG 2.0 is divided to separate documents: the guidelines and techniques. The guidelines are stationary and technology independent. In contrast the techniques is a living document which is updated as technology evolves. This makes it possible to update WCAG 2.0 with hands on techniques as the technologies used on the web evolve. One challenge is that W3C updates the techniques document for non-proprietary software only. This means that there will be no techniques collected by W3C for proprietary software, such as for example Adobe Flash. Thus, there will be no techniques from W3C on how to make Adobe Flash accessible.
How to present data from successfull techniques and common failures have not been presented by W3C. WCAG 2.0 identifies two types of criteria an element can match:
It is not so that the successfull techniques and common failures are opposite measures. Thus, not following a success technique does not mean that a barrier exist. Similarly, it is not so that avoid a common failure necessarily means that the element is accessible. Therefor, elements which nether match the successfull techniques nor common failures fall into some unknown state and cannot be claimed to be accessible nor in-accessible.
How to present data from a web page with common failures and successfull techniques are not clear.
The author further present some recommendations when measuring web accessibility according to WCAG 2.0. The recommendations are as following:
It is natural to assume that financial wealth leads to better government. It is further reasonable to expect that wealthy countries have higher quality of the e-government services compared to countries with less financial wealth. But how much does the finances alone influence quality e-government services? This short study gives a peek of how finances affects e-government services.
In this study the data used for quality of e-government services is the E–Government Development Index (E-readiness score) from the United Nations E-Government Survey 2010. Thus, it is directly assumed that a government with high quality e-government services will receive a high score, and visa versa. The remaining data used is from the World Bank Data Catalog.
The following figure presents a box plot of the differences between the E–Government Development Index of Developing and Developed countries. The plot shows that developing countries have in average score of 0.4 while developed countries have an average score of about 0.7. Furthermore, all developing countries have scores less than 0.7, while all the developed countries have a score higher than 0.5. Thus based on the United Nations E–Government Development Index score it is, not surprisingly, significant difference between e-government services in developing and developed countries.
E-readiness score versus developing and developed countires.
Thus, the quality is clearly dependant on the finances, but how much of the quality e-Government services are influenced by finances alone?
The development of government services is complex procedure shaped by many factors. There exists no general conclusion of which factors influence the quality of the government service. It is however possible to determine to what extent data from the financial situation in a country can be used to predict the e-readiness score.
The following graph presents the plot between E–Government Development Index and GNI per capita. The graph also includes a regression, which can be used to calculate the E–Government Development Index based on the GNI per capita alone.
E-readiness versus GNI per capita
The trends in the data are clearly visible. The regression can be seen as the black line, the mean response is shows as a green dashed line while the prediction interval is presented as the blue dashed line.
The regression line (black line) shows the relationship between the E–Government Development Index and GNI per capita. If no correlation existed between the two data sets, the line would be completely horizontall. The regression line can be used to predict the E–Government Development Index using only the GNI per capita. The graphs shows us that the relationship is not linear, but more complex.
The mean response interval (green dashed line) tells the estimated mean of the data.
The prediction interval (blue dashed line) tells where future data is expected be located (similar to confidence interval).
The data shows that the mean response interval and prediction interval changes as the GNI per capita increases. Generally, we are more certain of the prediction when these intervals are small. From this we can draw the following conclusion. It is relatively easy to predict the E-readiness score when a country has a low GNI per capita. In contrast, to predict the E-readiness score based on the GNI Per Capita alone for wealthy countries is a lot less precise. I.e. lack of finances generally means low quality services, while wealth alone is not sufficient to ensure quality in e-government.
A publication on how to facilitate collaboration between local government and vendors entitled Accessibility of eGovernment web sites: Towards a collaborative retrofitting approach (Nietzio, Olsen, Eibegger, Snaprud) has recently been published.
Changing a local government web site is often a long process which normally includes vendors, editors and specialists in local regulations and legal enforcements. Results from benchmarking studies are often a good facilitators, but the results alone are of limited use when it comes to updates in practice. This is especially true if the web site updates are relatively small such as removing accessibility barriers. Thus, the paper presents an approach for rapid accessibility updates of government web sites. The approach uses benchmarking results together with forums and online checkers.
Collaboration process between municipalities, vendors and eGovMon
The approach, visualised in the figure above, is applied to a group of Norwegian municipalities who want to improve the accessibility of their web site.
Accessibility benchmarking often fail to have an impact. This may be because of the following reasons:
The presented approach includes three areas:
This approach allows for local web site editors to use e-government benchmarking results together with an online forum to fix any accessibility issues with the web site. Furthermore, the editors gets knowledge of which issues they cannot fix themselves, but has to be carried out by updates of the CMS software or web site template. Even though this collaborative concept was applied to web accessibility barriers, it may be useful for other areas of local e-government as well.
(Full disclosure: I’m a co-author of the paper)
A very interesting study called E-government as an anti-corruption strategy showed that establishing e-Government reduces corruption. This should not be a surprise to anyone working with e-Government since it commonly believed that introduction of e-government diminishes the contact between corrupt officials and citizens, as well as increases the transparency and accountability. Unfortunately, hard evidence for these claims have been lacking (United Nations Development Programme, Fighting Corruption with e-Government Applications – APDIP e-NOTE 8, 2006).
The study is innovative as it uses a statistical approach to examine trends between e-Government and anti-corruption. Most other papers presenting quantitative data in the area do not use a statistical approach, which makes it more challenging to trust the results.
However, in this publication the author inspected, in a sound statistical way, the changes in corruption, using the control of corruption index presented by the World Bank, versus the changes in e-Government, using data from a Global e-Government Survey.
Unfortunately, for the OECD countries the author was not able to find any clear trends. This could be explained by less corruption in the OECD countries (compared to non-OECD countries), which means that the OECD countries had less to win, when it comens to anti-corruption, by introducing e-Government. Note that this is not evidence for absent of reduced corruption because of e-Government in OECD countries, just that the trends are not clearly visible in the data.
However, for the non-OECD countries, there are clear trends in the examined data. The results strongly imply that the introduction of e-Government has led to a significant reduction of corruption. Thus, supporting the view that e-Government is a very useful for reducing corruption – on a global scale.
The United Nations E-government Survey index is a weighted combination of three indices:
These three are all weighted equally contributing 1/3 to the score, which means that formally the e-readiness is as following:
E-readiness =
1/3 * Web Measure +
1/3 * Human Development +
1/3 * ICT Infrastructure
An interesting question that follows is what happens if we assign other weights to these indices For example, if we change the weights, can we also change the ranking a country gets?
Using Monaco as an example, it was ranked as member state number 112 in the UN e-readiness survey 2010. However, by adjusting weights of the three indices, we can change the ranking of Monaco from 112 up to 25, or down to 184.
In the following plot, possibile combination from 10% up to 80% of the three indicies are plotted and the corresponding ranking of Monaco.
Similarly, the following graphs how the top five member states, according to the E-readiness ranking in the 2010 survey, would rank if different weights would be used.
(Note that for reason of clarity some weightings have deliberatly been removed).
The question which naturally arises is:
Why does the current E-readiness index use equal weights, and is this any more correct than any weights?
Thanks do Deniz Susar for input on this idea.
A new version of the eAccessibility Checker has been launched by the eGovMon-project.
The tool targets checking how accessible web pages and web sites are for people with special needs. This new release focus on being understandable both for content providers and web developers. People no longer need to be web accessibility experts to find out both the accessible status of a web page and how to improve it.
The tool also includes an accurate presentation of the code ((X)HTML and CSS) which creates barriers. As well as good and bad examples of web accessibility.
Can you make your web site accessible and get the 
-logo?
The United Nations Global E-government Survey 2010 is now available. This fifth UN E-government survey focuses on e-government at a time of financial and economic crises.
The first part of the report is a discussion on ways e-government can mitigate the effects of the financial crises on development. It sees e-government in the light of the following United Nations priorities:
The second part is the results from the global survey. As previously, this includes the e-government ranking of the United Nations member states, regions and comparisons to the previous survey. Additionally, the second part includes the e-participation ranking and a (superficial) methodology section.
Please see the official page for more details.
Recently, a very interesting and solid paper titled “Is e-government leading to more accountable and transparent local governments? An overall view“, authored by Vicenta Pina, Lourdes Torres and Sonia Royo, has been published. I recommend anyone interested in e-government assessment and transparency to read this.
The paper focuses on to what degree introducing e-government has had a positive impact of the transparency of local governments.
The transparency measurements are carried out by assessing local government web sites with a methodology that rewards the presence of services and information. The underlying assumption is that, for example, a web site having contact information is more transparent than a web site where contact information is missing.
The survey includes five local government web sites (the web site of the capital and the four subsequent largest cities) from 15 European web sites. It is easy to argue that this is not a representative sample since smaller municipalities are not at all included in the survey. We can expect substantial differences between web sites from smaller and larger municipalities.
According to the survey results, the most transparent local governments can be found in the United Kingdom, followed closely by Germany, the Netherlands and Sweden. On the other hand, according to the survey, Greece had most improvement potential.
In addition to transparency the authors have performed a survey on account interoperability, usability and web site maturity.
A very interesting presentation has been made available discussing the impacts of the recent financial crisis on the eGovernment in Denmark. (Adam Grønlykke Mollerup, The economic and financial crisis: Impact on e-government in Denmark?)
The study claims, as can be expected, that more strict economy meant increased budged deficits, fall in investments, and decreased productivity.
Much more interesting is the impact it had on eGovernment in the country. According to the presentation the recent financial recession, and the measures taken accordingly, had a positive impact on the eGovernment, namely:
I have unfortunately only been able the find the presentation of this study (Adam Grønlykke Mollerup, The economic and financial crisis: Impact on e-government in Denmark?). In this presentation, the findings are not discussed in any details. More elaborate argumentations for the findings would have been very useful.
Ever wondered what the practical difference between the UN E-government measures and the UN E-participation measures?
The recently publish data from UNPAN shows us that the differences are practically absent. In the following image, I have plotted the correlation between the E-Government measurements and E-participation measurements.
Correlation between UN E-Government Measure and UN E-Participation Measure
A straight diagonal line, which is clearly visible in the plot, means that there is a strong correlation. I.e. that the E-participation measure can be extracted from (or calculated from) the E-Government measure. If the data looks chaotic, which is not the case here, it means the measures from E-participation and E-Government are independent.
This plot clearly shows a strong correlation. It even has a Pearson Correlation, which is a statistical way of showing that to data sets are correlated, is a staggering 0.66, which is extremely much in the social sciences.
The question which naturally arises is why bother with both measurements?
