Research databases

Preliminary discussions led to the inclusion of a question about the use of research databases in order to explore some of the less apparent but potentially significant impacts of ICTs on research practices. As noted, a third of all respondents saw databases as ‘essential’ and a further third reported using them. The use of research databases is higher in the sciences – with 75% of science and medical researchers reported using databases and more than 40% suggesting that they were ‘essential’. Nevertheless, almost 60% of social sciences, humanities and arts researchers reported using databases, with 15% regarding them as ‘essential’.

Just over 40% of interviewees reported that they had perceived a change in the relative importance of primary source datasets vis-à-vis secondary sources – 37% in social sciences, humanities and arts, and 47% in science and medical fields. Asked about the nature of that change, as many as 80% reported noticing an increase in the use of primary data – 100% of those in science and medical fields noting a

change, and around 60% of those in social sciences, humanities and arts fields noting a change.

Figure 4.23 Change in use of primary sources?

Source: Interviews conducted for Houghton, J.W. et al. (2003) Changing Research Practices in

the Digital Information and Communication Environment, DEST, Canberra.

Some noted significant changes in both how research was being done and what was being done. Some suggested that access to primary data, related software and computer power was changing their field of research in important ways. Indicative comments included:

It changes the nature of research, with much more primary material used because it is now available (Cultural Studies).

Some of the key databases are now central tools (Medicine). Much more use of satellite data (Environmental Science). Genetics data is opening new areas of research (Genetics).

Databases (eg. gene, protein, etc.) are changing things. Datamining gives leads as to what to look at (Structural Biology).

We do things now that were just not possible before, due to both data and the computer power to crunch the numbers. We now realise that a lot of what we thought we knew was not sound (Modelling).

There is more 'virtual fieldwork', partly because of the increased pressure to publish and get work out quickly (Asian Studies).

More use of primary sources 82%

More use of secondary scources

6%

Other 12%

Things like the ‘virtual reconstruction’ of sites have taken off in Archaeology, and help in analysis and teaching. There is much more analysis of the data generated from digs… more is collected. They are much more intensive these days (Archaeology).

Modelling appears to have entered a number of fields and be used widely across disciplines. For example, interviewees noted a:

Proliferation of modelling in silico rather than experimenting (Mechanical Engineering).

Somewhat less field work now, and more modelling (Geophysics).

Evidence-based data is now being used… mined (Pharmacy and Nursing).

In workshops participants noted that they accessed a good deal of publicly available data, and occasionally private subscription access data (eg. Celera’s gene data), and that they often did so outside the institution’s library and information system (eg. linking out of PubMed). Indicative comments included:

Different types of computer work are having a big impact on medicine and science generally, tools that help in pattern recognition and predictive work in particular are becoming extremely important (Medicine).

There are a number of very important information resources (databases and datasets) around the world which have made a huge difference to our work. A number of foundations… [have] been important in making a great deal of information available to the public (Medicine).

In atmospheric science, thank God for the U.S., because they are very generous with the amount of material they make available (Geography).

In Molecular Biology there has been a huge change in the way research is being done. The most important changes are in gathering data and making it available, mainly by putting it on the web… We have moved from analysis to synthesis, we are talking to mathematicians and others, looking for patterns. Research is sometimes moving away from hypothesis to much more ‘suck it and see’ work. Now you can do in a shorter space of time an examination of thousands of bits of information which would have taken much longer in the past (Genetics).

There are new challenges being thrown up by the existence of these databases as the scope, the type and the kind of research is changing significantly. Some of the new empirical observations which are now possible, due to computing, often throw up the need for more theoretical work, revisiting old assumptions (Economics).

There are shared databases [in the speech recognition area] which you have to contribute to to get access. If you are a private company you have to pay a fee of $60 000 to $70 000 for the same access (Computer science).

I think there is a substitution underway from thinking to information gathering, checking first on how everyone who has done anything on this has handled it. There is a shift to running a whole lot of hypotheses because it is easier to test, rather than thinking hard about it (Economics).

A number of researchers also talked about the software they needed to analyse the newfound wealth of data. In some cases access is open, in others it is much more guarded. One workshop participant reported that access to data was rather guarded and access to the necessary software was even harder – requiring very strong

personal networks and some purchasing. Others found the software easier to acquire.

I have a feeling that the time between the need arising and the [software] tool being available is shortening. In fact, it is sometimes the case that it is there before you know you need it (Genetics).

People are guarded about sharing data and related software. You have to use the network [of research colleagues] or buy it. My department spends thousands of dollars a year (Neuro-science/Bio-chemistry).

Access to data, related software and analytical objects is clearly vital – as is the management and dissemination of information created. In the words of one workshop participant:

What has changed is the access to databases, which has lessened the necessity to read journals (Chemistry).