Integration of Data and Publications - Alliance for Permanent Access

Report on Integration of Data and Publications Grant Agreement no.: 261530
descriptions of the data to so-called data publications all the way to (linking) the full
publication using the data. Services like Pangaea that require researchers to submit
metadescriptions with their data and adhere to certain formatting conventions (so that
all datasets can be interpreted in a similar way) are a solid beginning. Crosslinks
between articles and data are another means to support interpretability, because
verbalized interpretation of the dataset in a publication helps the understanding of the
original dataset. While links from articles to data become increasingly common, the
other way around from data to articles is not yet so widely used, but good examples exist:
e.g., Pangaea, PubChem and the Cambridge Crystallographic Database Centre. From a
technical viewpoint, the interpretability of datasets can be ensured by separating them
from vulnerable data carriers like CD-ROMs or DVDs and storing them on hard drives,
including backups, forward migration and replications. Data centres seem to be best
equipped to take on this challenge. In disciplines where there are no established data
centres (yet), the universities institutional data centre, well equipped libraries, or library
federations or initiatives like Dryad UK should stand in, although this may perpetuate
the risk of fragmentation.
Re-usability
Ensuring re-usability is the most difficult goal of data management in a data centre and
library setting. In addition to all the preconditions needed to ensure interpretability, reusability
often requires software to be available for analysing the datasets. The
researcher who wants to re-use another researcher’s dataset does not only need
intellectual, discipline specific understanding of the available datasets, but also the
skills to operate the appropriate software. Besides constant monitoring of the data
holdings, libraries and data centres need to maintain format and software registries to
plan for data preservation actions. First approaches to preservation of scientific data
were for example, developed in the CASPAR project 70 , and are followed up in the
APARSEN network of excellence 71 , but continued research is needed.
General dilemmas
Altogether, the many new initiatives in the area of data integration are promising.
However, against the expected explosion of research data (see chapter 1 and 2) they are
still more or less exceptional cases. There are a couple of pioneering libraries, often
embedded in big and capable universities and involved in several initiatives at one time.
The danger is that a few actors master the transition to a data-intensive scholarly
information infrastructure well, and that the majority of stakeholders follow in a passive
manner.
70 http://www.casparpreserves.eu/
71 http://www.alliancepermanentaccess.org/current-projects/aparsen
Opportunities for Data Exchange (ODE) –www.ode-project.eu 77