Current activities

Officially I am retired but I wish to share my experience, networks and knowledge, which I acquired over 40 years. Therefore (from spring 2019) I work as a boardmember Information/ICT for 2 organisations in the care in the Netherlands and I am operational as independent consultant. Apart from the projects already mentioned in the section “Who am I?”:

In Uganda I was involved in a project to improve the operational management of hospitals to manage their bed occupancy. For this purpose an algorithm has been developed that, based on the data of the patient, his / her family and his / her illness, predicts the patients’ likelihood of discharge.

In Ethiopia I have been working with the Tigray Institute of Policy Studies (TIPS, see http://www.tips.gov.et) to improve the capacity for advanced, quantitative research.

In the Netherlands I have been involved in a programme to implement a complete ERP system at Fairphone: A social enterprise which aims to develop smartphones that are designed and produced with minimal environmental impact, that does not contain conflict minerals (such as gold, tin and tungsten) and has fair labour conditions for the workforce along the supply chain producing it.

In recent years I have become fascinated by the opportunities for innovation offered by data analysis and data science in “soft sectors”. Not only because of the technology itself, but even more because of the opportunities, the ethical dilemmas and the organizational challenges. For the coming years I would like to contribute to the responsible use of data analysis and data science in these sectors.

This has already resulted (amongst others) in the following activities:

In Q3 of 2020 I conducted an online training workshop in datascience for a group of 7 lecturers (with a thorough background in ICT) of the Polytechnic College Suriname (PTC, https://ptc.edu.sr/) which offers recognized higher professional education (HBO) courses. This workshop had the ambition to enable the lecturers to develop a curriculum in Datascience. The curriculum development will be finalized in March 2021 and the programme will be offered to students in Suriname from the 2nd half of 2021.

In Q4 of 2020 I conducted (together with Michiel Kupers, ASML) an online training for 4 ICT companies in Bangladesh in cooperation with the Bangladesh Association of Software and Information Services (BASIS) : the national trade body for Software & IT Enabled Service industry, see https://basis.org.bd with more than 1100 member organizations. The workshop was a mixture of webinars and coaching sessions with the objective to enable participants with a good background in programming and statistics to acquire a thorough technical and commercial insight into the possibilities of Datascience and to develop a prototype of a new service which can be offered to new or existing clients.

The workshop took some 5 – 7 weeks (some follow-up coaching sessions are still taking place) with a focus on knowledge transfer in the first 3 weeks (with an average of 6 webinars a week) and coaching in development the new service in the following weeks. The extremely enthusiastic participants requested for a follow-up in 2021 in the form of an advanced training which was implemented in august – november 2021.

Form March 2021 I worked for the project ‘NLP4Stories’, an application for users doing surveys and narrative research such as Sprockler.

Sprockler is an application which supports researchers with the analysis of data collected from projects, events, research partly with open questions. When the number of respondents is getting high, it becomes very complex to analyse the answers to open questions. In this project a number of Natural Language Processing technologies are used for the analysis of open answers with the aim to support Sprockler users by

  • Finding commonalities and differences in stories of respondents
  • Analysing frequently used words/terms
  • Identifying weak signals with potentially high impact (the so-called outliers)
  • Automatic generation of summaries
  • Detecting striking differences in the answers e.g. on variables such as age etc.

NLP4 Stories has been developed to support the users. Not to partially automate the analysis. The first pilot was successful and NLP4Stories will be rolled out on a larger scale in Q3.