W3C eGov Roadmap

Dr. Brand Nieman offered up a collection of AOL Government/Digital Adgenda for Europe (data). The data is searchable but added context is always helpful.

From [2.4. EGOV Foundations (WHAT)]

The foundations include the nature, definition and conceptualization of EGOV. According to the official W3C definition "eGovernment is the use of the Web and other information technologies by governments to interact with the citizenry, between departments and divisions, and with other governments".

Implicit in this definition is that, while the Web is a public space, governance has a much longer history and legacy information processing standards. The legacy standards, often built up over hundreds of years, are tightly encapsulated and integrated in governance. What may seem like arbitrary constraints are nothing of the sort, rather checks upon behavior for the good of all.

From [2.3. EGOV Localization (WHERE)]

level of socio-economic development in the country, state or territory

language and cultural identify


The pages below concern the boundaries of the dataset above. When data is classified by country code, there are entailments. When data is classified by two character language codes, there is implied inheritance, and quite a bit of tourism advertising for foreign consumption.

In the "Outside Face" table below, the Interlingua is a CURIE of two character terminology language codes. These are the languages found in the ofren multi-lingual web sites. The Bibliograph is a CURIE of three character language codes. The American Community Survey indicates Americans speak predominantly English in public, and 110 other languages in private.

N.B. The Country Code "EL" in the data base should be "GR". EL is actually an iso 639-1 language code for Modern Greek.

The outside face

Many governments have working relationships with other governments based in history. It is not necessary to detail these relationships, unless of course one wants to. It is important to note that policies made in one place will have an uncertain effect on others who need to be on a conceptual copy-list. This is such a list. There are 38 distinct country codes in the dataset and 77 countries on the copy list.

The Outside Face of the Data Set

The inside face

Each of the 77 Members on the copy list has a number of internal subdivisions. It is unlikely that these sub-agents need policy updates, still, there should be a way to verify internal coverage. And, making yourself central to the interagency turf wars, where image is everything.

The Inside Face of the Data Set

The 77 Members (Agencies) on the copy list have about 1,533 Sub-Agencies - states, territories, provinces, etc. These can be enumerated if necessary.

Rough Name Cross-Reference (PDF)

Detailed Name Cross-Reference (CSV)