Open science data is a type of open data focused on publishing observations and results of scientific activities available for anyone to analyze and reuse. A major purpose of the drive for open data is to allow the verification of scientific claims, by allowing others to look at the reproducibility of results, and to allow data from many sources to be integrated to give new knowledge. While the idea of open science data has been actively promoted since the 1950s, the rise of the Internet has significantly lowered the cost and time required to publish or obtain data.
History
The concept of open access to scientific data was institutionally established with the formation of the World Data Center system, in preparation for the International Geophysical Year of 1957–1958. The International Council of Scientific Unions established several World Data Centers to minimize the risk of data loss and to maximize data accessibility, further recommending in 1955 that data be made available in machine-readable form. The first initiative to create a database of electronic bibliography of open access data was the Educational Resources Information Center in 1966. In the same year, MEDLINE was created – a free access online database managed by the National Library of Medicine and the National Institute of Health with bibliographical citations from journals in the biomedical area, which later would be called PubMed, currently with over 14 million complete articles. In 1995 GCDIS put its position clearly in On the Full and Open Exchange of Scientific Data : The last phrase highlights the traditional cost of disseminating information by print and post. It is the removal of this cost through the Internet which has made data vastly easier to disseminate technically. It is correspondingly cheaper to create, sell and control many data resources and this has led to the current concerns over non-open data. More recent uses of the term include:
SAFARI 2000 used a license informed by ICSU and NASA policies
The human genome
An Open Data Consortium on geospatial data
Manifesto for Open Chemistry
Presentations to JISC and OAI under the title "open data"
First draft of the Open Knowledge Definition explicitly references "Open Data"
XTech,
In 2004, the Science Ministers of all nations of the OECD, which includes most developed countries of the world, signed a declaration which essentially states that all publicly funded archive data should be made publicly available. Following a request and an intense discussion with data-producing institutions in member states, the OECD published in 2007 the OECD Principles and Guidelines for Access to Research Data from Public Funding as a soft-law recommendation. In 2005 Edd Dumbill introduced an “Open Data” theme in XTech, including:
In 2006 Science Commons ran a 2-day conference in Washington where the primary topic could be described as Open Data. It was reported that the amount of micro-protection of data in areas such as biotechnology was creating a Tragedy of the anticommons. In this the costs of obtaining licenses from a large number of owners made it uneconomic to do research in the area. In 2007 SPARC and Science Commons announced a consolidation and enhancement of their author addenda. In 2007 the OECD published the Principles and Guidelines for Access to Research Data from Public Funding. The Principles state that:
Access to research data increases the returns from public investment in this area; reinforces open scientific inquiry; encourages diversity of studies and opinion; promotes new areas of work and enables the exploration of topics not envisioned by the initial investigators.
In 2010 the Panton Principles launched, advocating Open Data in science and setting out for principles to which providers must comply to have their data Open. In 2011 was launched to realize the approach of the Linked Open Science to openly share and interconnect scientific assets like datasets, methods, tools and vocabularies. In 2012, the Royal Society published a major report, "Science as an Open Enterprise", advocating open scientific data and considering its benefits and requirements. In 2013 the G8 Science Ministers released a Statement supporting a set of principles for open scientific research data In 2015 the World Data System of the International Council for Science adopted a new set of Data Sharing Principles to embody the spirit of 'open science'. These Principles are in line with data policies of national and international initiatives and they express core ethical commitments operationalized in the WDS Certification of trusted data repositories and service.
By "open access" to this literature, we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited.
The logic of the declaration permits re-use of the data although the term "literature" has connotations of human-readable text and can imply a scholarly publication process. In Open Access discourse the term "full-text" is often used which does not emphasize the data contained within or accompanying the publication. Some Open Access publishers do not require the authors to assign copyright and the data associated with these publications can normally be regarded as Open Data. Some publishers have Open Access strategies where the publisher requires assignment of the copyright and where it is unclear that the data in publications can be truly regarded as Open Data. The ALPSP and STM publishers have issued a statement about the desirability of making data freely available:
Publishers recognise that in many disciplines data itself, in various forms, is now a key output of research. Data searching and mining tools permit increasingly sophisticated use of raw data. Of course, journal articles provide one ‘view’ of the significance and interpretation of that data – and conference presentations and informal exchanges may provide other ‘views’ – but data itself is an increasingly important community resource. Science is best advanced by allowing as many scientists as possible to have access to as much prior data as possible; this avoids costly repetition of work, and allows creative new integration and reworking of existing data.
and
We believe that, as a general principle, data sets, the raw data outputs of research, and sets or sub-sets of that data which are submitted with a paper to a journal, should wherever possible be made freely accessible to other scholars. We believe that the best practice for scholarly journal publishers is to separate supporting data from the article itself, and not to require any transfer of or ownership in such data or data sets as a condition of publication of the article in question.
Even though this statement was without any effect on the open availability of primary data related to publications in journals of the ALPSP and STM members. Data tables provided by the authors as supplement with a paper are still available to subscribers only.
Relation to peer review
In an effort to address issues with the reproducibility of research results, some scholars are asking that authors agree to share their raw data as part of the scholarly peer review process. As far back as 1962, for example, a number of psychologists have attempted to obtain raw data sets from other researchers, with mixed results, in order to reanalyze them. A recent attempt resulted in only seven data sets out of fifty requests. The notion of obtaining, let alone requiring, open data as a condition of peer review remains controversial.
Open research computation
To make sense of scientific data they must be analysed. In all but the simplest cases, this is done by software. The extensive use of software poses problems for the reproducibility of research. To keep research reproducible, it is necessary to publish not only all data, but also the source code of all software used, and all the parametrization used in running this software. Presently, these requests are rarely ever met. Ways to come closer to reproducible scientific computation are discussed under the catchword "open research computation".
