Knowledge Base

The Data Governance Institute defines Data Governance as a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models, which describe who can take what actions with what information, and when, under what circumstances, using what methods. It encompasses strategies and technologies used to make sure organisations data stays in compliance with regulatory and legal requirements.[1]

Governance is a term that has a quite broad context and means in its core to shape or design areas of life. E-Governance (Electronic Governance) is devoted to the challenges of shaping life areas in face of digital revolution and information era and affects all sectors encompassing the public, private and civil sector. It also affects communication and exchange between the sectors.

Evidence-based policy refers to policy decisions that are informed by objective evidence. Without evidence, policy-makers need to fall back on intuition, ideology, or conventional wisdom.
Originally, the concept has evolved in the medicine, encompassing the toolbox of quantitative experimental methods such as randomized controlled trials or quasi-experimental trials to support medical decisions.

New technologies have great influence on work and work processes, as we know them today. For example, new technologies offer the possibility of mobile work, can optimise the work process and make it more economical. [1]

The term “smart” in this trend indicates, that it is not only about collecting and storing data, but about automation of data analyses. Kim et al. describe this as follows: “Smart surveillance system is mainly composed of automatic video/audio analysis. Therefore, an emerging surveillance system must consider multimedia information for monitoring activities and extracting meaningful information from the environment.”[1]

This trend deals with the use of algorithms in policy and decision making. First, there is the trend of algorithmic regulation. Algorithmic regulation means that regulatory decision making is delegated to algorithms. The algorithms give the instructions of what should be done to achieve a desired outcome. [1]
The trend of using algorithms in governance and an increasing reliance of public decision making on algorithms is sometimes also called algocracy. [2]

Nudge or Nudging in governmental context can be seen as a concept of libertarian paternalism, which is about improving decision making. Nudging comes from the behavioural economics and the basic assumption is that people are not able to make the right decisions. Therefore, the behaviour of individuals should be influenced in a predictable way. Experts decide what is the best possible decision and try to steer the people into this direction. The people still have the option to choose an alternative, which makes this concept different to classical paternalism. [1]

Until now, it has usually been the case that documents have to be submitted in every authority, i.e. it is always the same information that is passed on to the authorities. This procedure is paper-based and involves a great deal of effort.

The goal of IT consolidation is to simplify and modernise the IT infrastructure in order to increase IT security, data protection and IT controllability. For example, central IT service centers with a strong focus on the service aspect are being set up and modern infrastructure platforms are being shared. The IT consolidation creates a basis for successful digitization. [1][2]

Probably one of the biggest needs for administration is to keep up with the technical innovation. To cope with the production of huge volumes of data is a technical problem as well as a big challenge for the staff. On the one hand, there should be established technical infrastructure for new policies and the increasing number of data, on the other hand, the staff needs to be trained and able to manage data and produce “good” data.