Challenges of Open Data
Occasionally the hurdles and (perceived) disadvantages of Open Data are quoted. These challenges can often be traced back to a lack of incentives to use Open Data practices, or disincentives in the science system. The following have sometimes been quoted as (perceived) disadvantages and hurdles of Open Data:
- High time investment: The organisation and preparation of the data for publication is often perceived as a significant time investment, coupled with a lack of recognition of this effort. This can seem to be disadvantageous, particularly if people who have a say in the further career path of the author set this as a false priority. In addition, it can cost time to answer questions if the materials are published. However, an explanation for handling the data can be uploaded together with the data. Good documentation and preparation of the data also leads to such queries being minimised. In addition, this has the advantage that your own research data are also permanently stored for your own use. This can be an advantage later and save time at another point, for example during reuse or applying for funding.
- Effects on publications: The publication of research data does not endanger the possibility of publishing an associated publication at a later date. The overwhelming majority of publishers do not regard the publication of a dataset as pre-publication, meaning that you can already publish your data continually during the research project. You thereby raise the visibility and traceability of your research and your article, which is based on the evaluation of these data, potentially receives a greater number of citations.
- Worrying about risks: Sometimes researchers worry that others will be able to profit more from their research data than they themselves. Another worry is that some researchers do not keep to the rules of good scientific practice and may release published research data as their own. These fears rarely exist in practice. Most repositories provide the stored data with a persistent identifier such as the Digital Object identifier (DOI). The published data have a publication date and a time stamp with which you can permanently prove that you were the first to publish these data.
- High costs: Worries about high costs should not hold you back, because Open Data doesn’t necessarily need to cost a lot. Careful planning and documentation, the avoidance of mistakes in the study design and in the implementation of the data collection, and the archiving of the data usually generate high-quality data. You profit from this for your own purpose as well as if the data are passed on and reused. Furthermore, you can (usually) apply for project funds that cover the additional costs for the preparation of data and documentation.
- Complicated collaboration: Following an Open Science approach can make research collaboration more complicated – for example, if not all researchers are enthusiastic about publishing the research data. The advantages are listed above and by allaying their fears, you have good arguments for getting other researchers interested in Open Data.
You can avoid many of the hurdles of Open Data, and some of them turn out to be myths. Practicing Open Data can also lead to the abovementioned advantages. We have also put together some further advantages of Open Data for you.