Dear Minister HEITOR,
dear Manuel, Dear Rector Joao SÀÁGUA ,
Dear colleagues,
Ladies and Gentlemen,
I thank Rector SÀÁGUA and Vice-Rector Elvira FORTUNATO for their kind invitation to participate to the NOVA Science Day. It is always a pleasure for me to be in Portugal and enjoy its remarkable hospitality.
For my lecture this morning I chose the topic of “interdisciplinarity” because of its importance and relevance today but also because of the challenges it represents for policy makers, funding agencies and for universities and research organisations altogether. If I had to give a title to it, it could be “Supporting Interdisciplinarity, a challenging obligation”.
First, it is very important to be conscious of the considerable variety of situations that involve interdisciplinarity: from the obvious case of complex problems that require bringing together truly diverse competencies (of which Climate Change provides an excellent example) to emerging new disciplines, from evaluation issues to training issues, etc.
A lot of discussions have taken place about possible differences between interdisciplinarity, pluridisciplinarity or even transdisciplinarity. I will not be discussing this here, and for the sake of simplicity only refer to interdisciplinarity.
Dealing with complex issues
There are numerous examples of scientific issues that require expertise from different disciplines. In recent years, one of the most evident examples has been provided by the follow up of Climate Change by the International Panel on Climate Change (IPCC) set up by the United Nations, a unique initiative. The IPCC faced and faces many challenges:
- to collect a considerable amount of data with a stable methodology;
- to develop models and scenarios validated for the past on the data assembly;
- to produce reports subject to a very thorough cross-evaluation by validated experts from different disciplines and different countries.
To make sense of the information gathered requires an extraordinary combination of knowledge. If there are indeed models for the general atmospheric circulation, it is very demanding to articulate them with the description of local situations.
As a result, it is quite hard to make an extensive list of fields that need to be mastered in this endeavour: Geography, Physics, Chemistry, Statistics, Mathematics, Plant Biology, Sociology and in particular Urban Sociology, Agriculture, Political Science. All these domains are needed in order to come up with scenarios for the future decades of which uncertainties can be properly estimated. And indeed uncertainties are to be expected. They just have to be bounded carefully in order to deliver a clear message about the most relevant measures to take and the impact on many sectors of society and on the life of ordinary citizens.
This represents a very comprehensive effort mobilising thousands of scientists with many backgrounds. We all know that the major challenge is probably not even the scientific effort that needs to be done but, on the basis of the evidence assembled, to get politicians to make good use of it and implement the changes that need to be understood and accepted by everyone.
Accompanying the emergence of new areas
A quite different setting where interdisciplinarity is relevant concerns the emergence of new domains that, later, continue to exist as independent entities with their own organisations and structures.
I would like to point to two examples, with the aim of showing that the timeframes for such developments can be quite different: the birth of Molecular Biology, making later the Human Genome Project possible and leading to Bioinformatics, and the development of Cognitive Sciences and Behavioural Economics.
Molecular Biology results from an attempt in the late 1930s to explain life using the basic laws of Physics and Chemistry. The combination of these two disciplines and the belief that they allow to consider mechanisms involving very complex, but specific, structures led to the creation of a new field. The key actors of what in the end became a revolution are some specific macromolecules: nucleic acids, and in particular the most famous one, DNA, and proteins, through which living organisms act. It took quite a long time, some 50 to 60 years, to develop it successfully as it required characterizing the structure, of these complicated molecules, their function and their relationships.
As is well known, it was the unravelling of the very peculiar double helix structure of the DNA that played a key role in understanding the functioning of the genome. This led to nothing less than the deciphering of the Human Genome. Such a project looked completely unreachable for some time because of its complexity and its costs reaching hundreds of millions of Euros. Thanks to extraordinary progress in the technology and computing power, such an endeavour, which originally required the mobilisation of many teams around the world for months sharing in a planned way their know how and their resources, has now become a routine exercise. Individuals can now be provided with their genome in minutes and for a few hundred Euros. All this lies at the heart of the development of Bioinformatics and a lot of activities in ‘omics’, starting with genomics, proteomics, etc. Again, let me stress here that such a perspective, now the basis of the hope for the advent of personalised medicine, was considered for a while just a dream.
All this could only happen thanks to extensive exchanges leading to the development of a common language and shared methodologies by scientists who, initially, had quite different approaches. This was of course a lengthy process that required open minds, patience and perseverance. Along the way there have been necessarily failures due to too impatient steps taken on the basis of naive views. Nothing of this sort could have happen without some people thinking out of the box and dreaming the impossible to reach the boundaries of the possible. Support to risk-taking is key for such things to happen.
As mentioned before, dealing with the huge amounts of data that all “omics” sciences require was only possible thanks to the new computing power provided by the massively expanded capacity of computers but also thanks to the development of efficient algorithms to deal with these data in a manageable and efficient way. This actually meant a quite radical transformation of Biology and turning part of it into a “Big Science” when its tradition favoured small teams working on quite different and narrow projects.
The development of another new discipline is worth being looked into: Cognitive Science. The basis of it is the study of the processes by which the mind builds cognition from information that various senses gather so that several functions are articulated properly, from perception to memory, from memory to action, from emotion to language, etc. The fields dealing with such knowledge are very diverse: Physiology, Neuroscience, Psychology, Linguistics or Mechanics. Getting actors in these fields to interact and propose complementary representations could not be achieved without developing new concepts and suggesting how computational models can integrate data collected, hence the role also played in these disciplines by Computer Science. New investigative methodologies are added permanently. A good example is given by proton magnetic resonance spectroscopy coming from sophisticated physics: it now allows following the electro-chemical activity of the brain with a high level of detail and in real time. The process to analyse the signals is very involved, so that referring to it as an “imaging” process is hugely oversimplified.
To be noted: the level of information that has become accessible through these approaches is beyond anything that was expected some 30 years ago. Indeed it allows to relate very directly any physical activity to what is happening in the brain. To achieve such a high level of integration of competences is very challenging as it requires people with totally different background to coordinate efforts and to accept that new methodologies invade their usual practice. This does not go without resistance. The development of a new more comprehensive approach by the actors remains key for future progress, and this is what is happening with a Cognitive Science approach to Behavioural Economics, one of the new frontiers in the area.
The reality of interdisciplinary research seen from the ERC
