A well-defined set of indicators is important for assessing the impact of the German Federal Government's High-Tech Strategy. It also serves the purpose of evaluating individual funding programs - thus enabling us to measure their success on a solid basis.

The challenge, however, is that research and innovation is dynamic and constantly evolving. The digital transformation, technological progress and increasing international integration are just some examples for these dynamic developments. In addition, various actors from business, science and society are involved in this development. Hence, established indicators cannot always fully capture emerging innovations.

Capturing innovations - new topics, methods and sources

It is a core interest of the German government to maintain and further enhance the international performance of Germany as an innovative country. Motivated by the OECD Blue Sky Forum in 2016, the Federal Ministry of Education and Research (BMBF) decided to fund projects to improve and further develop indicators for measuring research and innovation (R&I) in science and education. Since 2017, these projects have contributed to the recording and impact measurement of new topics, innovation sectors and phenomena. In this way, standard measurement models are expanded and recast with innovative indicators. In addition, empirical approaches are opened up through the use of new data sources and methods. Our goal is to utilize this research to enable evidence-based funding policies and to continuously improve funding instruments.

Redefining indicators - funding announcements and research funding.

The first round of the funding call on "Further development of indicators for research and innovation" of January 2017 aimed to initiate capacity building in the field of innovation research that will be effective in the long term. The BMBF selected seven projects for funding. In November 2018, the second round initiated the funding of seven additional projects for the further development of the indicator system. The funded research projects focus on new phenomena such as social innovations, household innovations and open innovation processes. They apply new methods in the context of digitization, tap additional data sources and further develop existing indicator catalogs.

Current Projects

Trend TDF

Within the TrenDTF project, text mining methods are used to improve accessibility to the corpus of German research reports held at the German National Library of Science and Technology (TIB). This will transform the corpus into a database for new and improved indicators to support the impact evaluation of research and development activities. Furthermore, complementary documents such as funding calls will be added to the corpus, thus allowing the comparative analysis of funding providers’ intentions and the resulting research.

Project period 01.10.2019 – 30.09.2022

Project description: PDF

Project coordination German National Library of Science and Technology (TIB) Hanover

GEI-OE

The GEI-OE project aims to develop new indicators for quantifying informal knowledge flows. It particularly focusses on the significance of knowledge exchanges between individuals. New data sources will be utilized and analysed using innovative methods with the aim of developing broadly applicable indicators for recording informal relations and implicit knowledge. Finally, these indicators will be validated in cooperation with three participating Fraunhofer high-performance centres and supplemented by findings from an accompanying survey.

Project period 01.10.2019 – 30.09.2022

Project description: PDF

Project coordination Fraunhofer Institute for Systems and Innovation Research ISI Karlsruhe

PeerInnovation

The significance of private users in the development and spread of sustainable technologies is indisputable. Peer communities have become a core component of innovation ecosystems and can play an important role in sustainable change. However, official statistics are restricted to science and market data as there is a lack of suitable indicators for activities in the household sector. The aim of this project is to develop measuring tools for peer innovations using online communities from the fields of sustainable energy, mobility and urban development as examples.

Project period 01.10.2019 – 30.09.2022

Project description: PDF

Project coordination Institute for Ecological Economy Research (IÖW)

IreWiNE

The IreWiNE project – Indicators for Regional Knowledge Transfer Structures for Sustainable Development – focusses on the role of knowledge transfer institutions and intermediaries. Researchers at the University of Göttingen and Darmstadt University of Applied Sciences aim to find ways to quantify innovation activities relating to sustainable development in regional innovation systems. Innovation networks and intermediaries can work at a regional level between business, science, administration and stakeholders from civil society to support and speed up innovation processes.

Project period 01.09.2019 – 31.08.2022

Project description: PDF

Project coordination Georg August University of Göttingen

WISIH

Extensive research has been done into technological innovations. However, innovations that help bring about changes in social practices or procedures are largely unknown. Gaps are particularly noticeable when it comes to such “social innovations” from institutions of higher education. WISIH aims to contribute toward understanding the underlying processes and facilitating the measurement of these processes, the reporting of results and impacts of social innovations. The goal is to produce a social innovation model and accompanying set of indicators that can be used in institutions of higher education.

Project period 01.10.2019 – 31.01.2023

Project description: PDF

Project coordination Centre for Higher Education Gütersloh

DynTOBI

As a follow-on from the research design used in the TOBI project, the DynTOBI project focusses on mapping innovation dynamics over time. In comparison with existing surveys, this project will discuss potential for improving the currently used innovation indicators in terms of additional content or methods. On the one hand, the indicators to be developed and the methods on which they are based aim to improve existing innovation statistics, while at the same time enabling improvements to the mapping of how innovations are spread. The results are thus relevant in a scientific context, for stakeholders providing policy advice and for strategic company management.

Project period 01.10.2017 – 31.03.24

Project coordination Justus Liebig University of Giessen

IndiSI+

IndiSI+ focusses on the validation and consolidation of the IndiSI framework model and the underlying sets of indicators. The results of the IndiSI project provide insight into the following three areas: firstly, about future needs in the field of innovation indicators, secondly with regard to required regional capacities and thirdly, concerning the realization of innovative solutions.  Based on the results from the pilot project in the Rhine-Ruhr region, plans are now in place to extend the survey to the Länder level, thus enabling a regional comparison.

Project period 01.01.2018 – 31.03.23

 Project coordination Westfälische Hochschule University of Applied Sciences Gelsenkirchen - Institute for Work and Technology

Completed Projects

NETINU

The NETINU project aims to develop new indicators for measuring the connectedness of (innovative) companies. These indicators will describe networks in terms of sector, location, size and structure as well as facilitate an analysis of network dynamics. The project pursues four main goals: collecting indicators of connectedness; calculating network indicators based on two different data sources; linking innovation indicators; validating the new indicators.

Project period 01.10.2019 – 30.09.2021

Project description: PDF

Project coordination Technical University of Munich

UseAltMe

Altmetrics focus on enhancing traditional scientific publishing indicators such as citation rates or the h-index. In addition to print literature in academic journals whose citations are counted, altmetrics attempt to map out science communication in social media in order to show the total impact of the research. UseAltMe looks at connections between altmetrics and bibliometrics. It aims to produce a separate set of indicators for altmetrics, which are aggregated higher than the article level.

Project period 01.10.2019 – 31.03.2022

Project description: PDF

Project coordination TH Köln – University of Applied Sciences

TechSpace

The successes of innovation activities and public research funding are often measured using quantitative outcome indicators. However, whether or not innovations actually result in something new being produced is often overlooked. TechSpace presents the idea of technology spaces as a new empirical approach to analysing long-term technology developments. Indicators for evaluating and identifying general and regional technological developments are being developed and the political implications are also presented. There is a particular focus on how radical new innovations are.

Project period 01.01.2018 – 31.12.2020

Project description: PDF

Project coordination University of Bremen 

InnoMetrics

The aim of the InnoMetrics project is to render previously overlooked unstructured information from text sources such as research reports into something usable for measuring the newness of innovations. This research approach is based on the assumption that the more novel an idea is, the more a text describing the innovation will differ from already existing texts. This project aims to use the associated linguistic change as a tangible way to measure the degree of novelty.

Project period 01.01.2018 – 31.12.2020

Project description: PDF

Project coordination RWTH Aachen University

NEO-Indikatorik

Cooperation between companies has proven very promising in successfully managing complex innovation processes. However, there has been no systematic recording of the connections within the German innovation system to date, especially not at the level of technology fields. It is particularly important to consider change over time as networks are extremely dynamic systems. The project therefore develops a proposal for how various aspects of networking can be integrated into existing R&D data collection methodology.

Project period 01.01.2018 – 31.12.2020

Project description: PDF

Project coordination Wissenschaftsstatistik gGmbH Essen

INFOWIK

The INFOWIK project aims to improve the recording of knowledge-based capital and thus also innovation indicators. The main priorities are:
1. Measuring expenditure for developing corporate competences whilst avoiding overlaps with other expenditure for physical or knowledge capital.
2. Developing tools to measure investment in corporate competences that do not require company surveys to be carried out.
3. Analysing the relationships between individual components of knowledge capital on the one hand and innovation expenditure and innovation successes on the other.

Project period 01.12.2017 – 31.05.2020

Project description: PDF

Project coordination ZEW – Leibniz Centre for European Economic Research in Mannheim

InDUI

InDUI stands for Innovation Indicators for the Doing-Using-Interacting Mode (DUI mode). The DUI mode is an umbrella term for various forms of learning and interaction, which lead to innovations in small and medium-sized enterprises in particular. The InDUI project works to develop indicators which can better portray this form of innovation in DUI mode. It strives to use these indicators in economic and innovation policy. In addition to this, underlying learning processes are mapped out in the economic experiment and investigated under controlled laboratory conditions.

Project period 01.10.2017 – 31.03.2021

Project description: PDF

Project coordination Georg August University of Göttingen  

TOBI

In this project, web-based innovation indicators are developed which compensate for the disadvantages of traditional innovation indicators from surveys and patent data (e.g. lack of current relevance, scope, granularity and high data collection costs). In order to analyse company websites, a web-mining-based approach was designed that relies on ARGUS, a web-scraping software specially developed for this purpose. The extracted data are analysed in order to identify innovation-related information with the help of data mining techniques.

Project period 01.10.2017 – 30.09.2020

Project description: PDF

Project coordination Justus Liebig University of Giessen

IndiSI

IndiSI investigates the measurement of social innovations across three mutually interactive levels: (1) organisational innovativeness, (2) regional innovation capacities and (3) discourse-related early indicators. This research field has been neglected up to now. As an exploratory scoping study, IndiSI highlights ways to effectively record social innovations on the three measurement levels. IndiSI formulates recommendations on how the examined perspectives and tried and tested indicators can complement existing approaches to measuring innovation or be integrated in these approaches.

Project period 01.01.2018 – 31.03.2021

Project description: PDF