Project Description

Digital transformation constitutes one of the most important innovations at the local level of government. It is expected to fundamentally reshape the local delivery of public services, the structures of public administration, and governance in Europe in general. Most recently, the COVID-19 pandemic revealed the fundamental importance of well-prepared digital administration. In many countries, local government is the most significant tier of public service delivery, ensuring proximity to citizens and playing a key role in digital transformation. Against this background, it is a matter of concern that in current comparative research concerning the digital transformation of state and administration, local levels of government have been insufficiently investigated. Indeed, no systematic, cross-countries comparative knowledge is available regarding the state of implementation and the effects of digital transformation at the local tier of government in Europe. The DIGILOG research project aims to remedy those deficits.

The DIGILOG Project addreses two key research questions:

  • What are the dynamics, scale, and pace of digital transformation in European local governments? Is the change radical and revolutionary or, on the contrary, incremental and evolutionary, and can regional differences be identified?
  • What effects does digital transformation in these organizations have, especially in terms of their output (service delivery, organization, processes, and resources), outcomes (performance and accountability), and impact (acceptance by the citizens, governance, emerging areas of tension)?

To answer these questions, data the project collects data on all municipalities in the 46 member states of the Council of Europe. In this, a range of state of the art research quantitative and qualitative reearch methods is used, including a set of case sstudies, a survey among the the leadership of municipal administrations and a web-crawling based analysis of municipality websites.

Case Studies

For a deeper understanding of the digital transformation on the ground and its relevant causal processes, selected municipalities are the subject of qualitative case studies.


In order to find out more about the spread of municipalities, a quantitative survey is sent to all participating municipalities every twelve months for the duration of the project.

Web Crawling and Scraping

The two traditional methods of the social sciences are supplemented by the use of a web crawler and scraper, which regularly extracts data from the websites of all local administrations involved. This is a novel form of data collection for the field, and its use in this project can be seen as a test of this method for the administrative and organizational sciences as a whole.

Scientific Contribution and Publications

The project results are published in various publications, including scientific articles in recognized journals, a project report, and four doctoral theses. In addition, the collected data will also be prepared for the general public and presented on our dashboard.

Case Studies 

To accompany the quantitative surveys, comparative case studies are being conducted in selected municipalities forming part of the extended survey sample. The case studies are about municipalities with different administrative cultures in order to capture the country-specific variance in local administrative systems. The case study approach relies on field research methods, semi-structured expert interviews, and focus groups conducted with local chief executives, chief information officers (CIOs), department heads, staff representatives, and staff members. Building on the interim results from the quantitative research, the aim is to gain deeper insights into the internal processes and actor constellations of the respective digital transformation paths by recording the organizational realities in the municipalities.


In addition to the qualitative case studies, the DIGILOG project will be based on two quantitative forms of data collection: a web crawler for analyzing municipal websites and a survey among the leadership of European municipal administrations.

The survey has several objectives. Primarily, it collects information on the status of the external and internal digital transformation of the municipal administrations surveyed, from which a Europe-wide index on the level of digitalization in local governments is created. Externally, the focus is mainly on the digital services offered by the administrations. These are assigned to different maturity levels according to an established social science model, ranging from providing information and options for digital communication with administrative employees to the fully digital and seamless handling of administrative processes. Internally, the project will cover, among other things, the technical equipment of administrations, forms of internal communication, data management, and the automation of processes and routine decisions.

Additionally, the survey collects data on a large set of other variables relevant to the digital transformation. This includes potential enablers and hurdles for digitalization processes, the administrative culture and management processes of the municipalities, and potential effects of the digital transformation, ranging from more direct outcomes like changes to an administrations efficiency and accountability to wider ranging societal impacts.

Web Crawling and Scraping

Web crawling is a vital component of the DIGILOG project. The automatic crawling and analysis of the municipal websites are part of the quantitative analysis and complement the survey by providing information on the services municipalities provide digitally as well as the technical sophisitcation of their websites. The results of the data analysis described below will be displayed on a dashboard within a monitoring platform.

The monitoring platform is based on three main components which will interact with each other: web crawling, data storage, and the subsequent data analysis. With this platform, the political communities' websites are monitored for the duration of the project. In order to cope with the amount of data, different approaches allow for selective crawling while losing as little information as possible. One project goal is to research and implement the most efficient method for this task.

Data storage relies on two different database systems, a relational and a document-oriented system. Database keys and standardized information are stored in the relational system, the respective documents of the website, and the results of the analysis in the document-oriented system. Finally, indications of digital transformation (e.g., mention of selected services or keywords) will be extracted and evaluated. Various methods used in natural language processing (NLP), a subfield of machine learning, are used for this purpose.

The analysis, in turn, provides effective feedback to the intelligent crawler, which contributes to its continuous improvement. The quality of the analysis is safeguarded by domain experts who  interpret the results and classify them for the business, political, and administrative sciences.