Open scientific data

Open scientific data or open research 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.

The modern concept of scientific data emerged in the second half of the 20th century, with the development of large knowledge infrastructure to compute scientific information and observation. The sharing and distribution of data has been early identified as an important stake but was impeded by the technical limitations of the infrastructure and the lack of common standards for data communicaton. The World Wide Web was immediately conceived as a universal protocol for the sharing of scientific data, especially coming from high-energy physics.

History

Scientific data was not formally defined until the late 20th century. The first influential policy definition appeared as late as 1999, when the National Academies of Science described data as "facts, letters, numbers or symbols that describe an object, condition, situation or other factors". Institutional and epistemological discourses favored alternative concepts and outlooks on scientific activities: "Even histories of science and epistemology comments, mention data only in passing. Other foundational works on the making of meaning in science discuss facts, representations, inscriptions, and publications, with little attention to data per se." For Christine Borgman, the main issue is not to define scientific data ("what are data") but to contextualize the point where data became a focal point of discussion within a discipline, an institution or a national research program ("when are data").

Due to its late emergence, the concept of scientific data has developed in parallel with the open data and the open science movement: whether or not to share the data, to what extent it should be shared and to whom has always been a major component of the scientific data lifecycle. According to Paul Edwards, opening and sharing belong to a fundamental characteristics of computing data, data friction: "Edwards’ metaphor of data friction describes what happens at the interfaces between data ‘surfaces’: the points where data move between people, substrates, organizations, or machines (…) Every movement of data across an interface comes at some cost in time, energy, and human attention. Every interface between groups and organizations, as well as between machines, represents a point of resistance where data can be garbled, misinterpreted, or lost. In social systems, data friction consumes energy and produces turbulence and heat – that is, conflicts, disagreements, and inexact, unruly processes." The opening scientific data is both a friction in itself and also a way to manage and reduce frictions.

Development of knowledge infrastructures and data frictions (1945-1990)

Punch-card storage in US National Weather Records Center in Asheville (early 1960s). Data holding have expanded so much that the entrance hall has to be used as a storage facility.

The emergence of scientific data is associated with a semantic shift in the way core scientific concepts like data, information and knowledge are commonly understood. Following the development of computing technologies, data and information are increasingly described as "things": "Like computation, data always have a material aspect. Data are things. They are not just numbers but also numerals, with dimensionality, weight, and texture".

After the Second World War large scientific projects have increasingly relied on knowledge infrastructure to collect, process and analyze important amount of data. Punch-cards system were first used experimentally on climate data in the 1920s and were appplied on a large scale in the following decade: "In one of the first Depression-era government make-work projects, Civil Works Administration workers punched some 2 million ship log observations for the period 1880–1933." By 1960, the meteorological data collections of the US National Weather Records Center has expanded to 400 millions cards and had a global reach. The physically of scientific data was by then fully apparent and threatened the stability of entire buildings: "By 1966 the cards occupied so much space that the Center began to fill its main entrance hall with card storage cabinets (fi gure 5.4). Officials became seriously concerned that the building might collapse under their weight"

By the end of the 1960s, knowledge infrastructure have been embedded in a various set of disciplines and communities. The first initiative to create a database of electronic bibliography of open access data was the Educational Resources Information Center (ERIC) 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 (USA) with bibliographical citations from journals in the biomedical area, which later would be called PubMed, currently with over 14 million complete articles. Knowledge infrastructures were also set up in space engineering (with NASA/RECON), library search (with OCLC Worldcat) or the social sciences: "The 1960s and 1970s saw the establishment of over a dozen services and professional associations to coordinate quantitative data collection".

Early discourses and policy frameworks on open scientific data emerged immediately in the wake of the creation of the first large knowledge infrastructure. The World Data Center system (now the World Data System), aimed to make observation data more readily available in preparation for the International Geophysical Year of 1957–1958. The International Council of Scientific Unions (now the International Council for Science) 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. In 1966, the International Council for Science created CODATA, an initiative to "promote cooperation in data management and use".

These early forms of open scientific data did not develop much further. There were too many data frictions and technical resistance to the integration of external data to implement a durable ecosystem of data sharing. Data infrastructures were mostly invisible to researchers, as most of the research was done by professional librarians. Not only were the search operating systems complicated to use, but the search has to be performed very efficiently given the prohibitive cost of long-distance telecommunication. While their conceptors have originally anticipated direct uses by researcher, that could not really emerge due to technical and economic impediment:

The designers of the first online systems had presumed that searching would be done by end users; that assumption undergirded system design. MEDLINE was intended to be used by medical researchers and clinicians, NASA/RECON was designed for aerospace engineers and scientists. For many reasons, however, most users through the seventies were librarians and trained intermediaries working on behalf of end users. In fact, some professional searchers worried that even allowing eager end users to get at the terminals was a bad idea.

Christine Borgman does not recall any significant policy debates over the meaning, the production and the circulation of scientific data save for a few specific fields (like climatology) after 1966. The insulated scientific infrastructures could hardly be connected before the advent of the web. Projects, and communities relied on their own unconnected networks at a national or institutional level: "the Internet was nearly invisible in Europe because people there were pursuing a separate set of network protocols". Communication between scientific infrastructures was not only challenging across space, but also across time. Whenever a communication protocol was no longer maintained, the data and knowledge it disseminated was likely to disappear as well: "the relationship between historical research and computing has been durably affected by aborted projects, data loss and unrecoverable formats".

Sharing scientific data on the web (1990-1995)

The World Wide Web was originally conceived as an infrastructure for open scientific data. Sharing of data and data documentation was a major focus in the initial communication of the World Wide Web when the project was first unveiled in August 1991 : "The WWW project was started to allow high energy physicists to share data, news, and documentation. We are very interested in spreading the web to other areas, and having gateway servers for other data".

The project stemmed from a close knowledge infrastructure, ENQUIRE. It was an information management software commissioned to Tim Berners-Lee by the CERN for the specific needs of high energy physics. The structure of ENQUIRE was closer to an internal web of data: it connected "nodes" that "could refer to a person, a software module, etc. and that could be interlined with various relations such as made, include, describes and so forth". While it "facilitated some random linkage between information" Enquire was not able to "facilitate the collaboration that was desired for in the international high-energy physics research community". Like any significant computing scientific infrastructure before the 1990s, the development of ENQUIRE was ultimately impeded by the lack of interoperability and the complexity of managing network communications: "although Enquire provided a way to link documents and databases, and hypertext provided a common format in which to display them, there was still the problem of getting different computers with different operating systems to communicate with each other".

The web rapidly superseded pre-existing closed infrastructure for scientific data, even when they included more advanced computing features. From 1991 to 1994, users of the Worm Community System, a major biology database on worms, switched to the Web and Gopher. While the Web did not include many advanced functions for data retrieval and collaboration, it was easily accessible. Conversely, the Worm Community System could only be browsed on specific terminals shared across scientific institutions: "To take on board the custom-designed, powerful WCS (with its convenient interface) is to suffer inconvenience at the intersection of work habits, computer use, and lab resources (…) The World-Wide Web, on the other hand, can be accessed from a broad variety of terminals and connections, and Internet computer support is readily available at most academic institutions and through relatively inexpensive commercial services. "

Defining open scientific data (1995-2010)

The development and the generalization of the World Wide Web lifted numerous technical barriers and frictions had constrained the free circulation of scientific data. Yet, social, cultural economic barriers remained.

The legality of data sharing was early on identified a crucial issue. In contrast with the sharing of scientific publication, the main impediment was not copyright but undertainty: "the concept of ‘data’ [was] a new concept, created in the computer age, while copyright law emerged at the time of printed publications." In theory, copyright and author rights provisions do not apply to simple collections of facts and figures. In practice, the notion of data is much more expansive and could include protected content or creative arrangment of non-copyrightable contents.

New research policy have to be implemented to realize the original vision laid out by Tim Berners-Lee of a web of data. Climate research has been a pioneer in the conceptuel definition of open scientific data, as it has been in the construction of the first large knowledge infrastructure in the 1950s and the 1960s. In 1995 GCDIS (US) articulated a clear commitment On the Full and Open Exchange of Scientific Data (A publication of the Committee on Geophysical and Environmental Data - National Research Council):

The Earth's atmosphere, oceans, and biosphere form an integrated system that transcends national boundaries. To understand the elements of the system, the way they interact, and how they have changed with time, it is necessary to collect and analyze environmental data from all parts of the world. Studies of the global environment require international collaboration for many reasons:

• to address global issues, it is essential to have global data sets and products derived from these data sets;
• it is more efficient and cost-effective for each nation to share its data and information than to collect everything it needs independently; and
• the implementation of effective policies addressing issues of the global environment requires the involvement from the outset of nearly all nations of the world.

International programs for global change research and environmental monitoring crucially depend on the principle of full and open data exchange (i.e., data and information are made available without restriction, on a non-discriminatory basis, for no more than the cost of reproduction and distribution).

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 (South Africa, 2001) used a license informed by ICSU and NASA policies
• The human genome (Kent, 2002)
• An Open Data Consortium on geospatial data (2003)
• Manifesto for Open Chemistry (Murray-Rust and Rzepa, 2004) (2004)
• Presentations to JISC and OAI under the title "open data" (Murray-Rust, 2005)
• Science Commons launch (2004)
• First Open Knowledge Forums (London, UK) run by the Open Knowledge Foundation (London UK) on open data in relation to civic information and geodata (February and April 2005)
• The Blue Obelisk group in chemistry (mantra: Open Data, Open Source, Open Standards) (2005) doi:10.1021/ci050400b
• The Petition for Open Data in Crystallography is launched by the Crystallography Open Database Advisory Board. (2005)
• XML Conference & Exposition 2005 (Connolly 2005)
• SPARC Open Data mailing list (2005)
• First draft of the Open Knowledge Definition explicitly references "Open Data" (2005)
• XTech (Dumbill, 2005), (Bray and O'Reilly 2006)

In 2004, the Science Ministers of all nations of the OECD (Organisation for Economic Co-operation and Development), 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:

• Open government
• Public web services
• Grassroots data
• Scientific and academic publishing
• Intellectual property
• Blogging and personal content
• Semantic Web

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 (e.g. by license) 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 (Organisation for Economic Co-operation and Development) 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 LinkedScience.org 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.

Relation to open access

Much data is made available through scholarly publication, which now attracts intense debate under "Open Access" and semantically open formats – like to offer the scientific articles in JATS format. The Budapest Open Access Initiative (2001) coined this term:

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, although some scientists now agree that doing so could help prevent future retractions of scientific manuscripts.

Open research computation

Main article: 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".

See also

• CODATA
• Data archive
• Dataverse
• Journal Article Tag Suite (JATS)
• Open science
• Science Commons

Bibliography

Journal articles

• Korsmo, F. L. (2010). "The Origins and Principles of the World Data Center System". Data Science Journal. 8: –55–IGY65. doi:10.2481/dsj.SS_IGY-011.{{cite journal}}: CS1 maint: ref duplicates default (link)
• Neylon, Cameron; Chan, Leslie (2016-04-18). "Exploring the opportunities and challenges of implementing open research strategies within development institutions". Research Ideas and Outcomes. 2: –8880. doi:10.3897/rio.2.e8880. ISSN 2367-7163. Retrieved 2021-11-01.{{cite journal}}: CS1 maint: unflagged free DOI (link)
• Rosenberg, Daniel (2018-11-01). "Data as Word". Historical Studies in the Natural Sciences. 48 (5): 557–567. doi:10.1525/hsns.2018.48.5.557. hdl:21.11116/0000-0002-C567-C. ISSN 1939-1811. S2CID 149765492. Retrieved 2022-03-21.{{cite journal}}: CS1 maint: ref duplicates default (link)

Books & thesis

• Gaillard, Rémi (2014). De l'Open data à l'Open research data : quelle(s) politique(s) pour les données de recherche ? (Thesis). ENSSIB.
• Borgman, Christine L. (2015-01-02). Big Data, Little Data, No Data: Scholarship in the Networked World. Cambridge, MA, USA: MIT Press. ISBN 978-0-262-02856-1.{{cite book}}: CS1 maint: ref duplicates default (link)
• Lipton, Vera (2020-01-22). Open Scientific Data: Why Choosing and Reusing the RIGHT DATA Matters. BoD – Books on Demand. ISBN 978-1-83880-984-3.{{cite book}}: CS1 maint: ref duplicates default (link)

External links

• Research Data Canada
• Open Data In Science article (P Murray-Rust)
• Open Data about monitoring of deforestation in the Brazilian Amazon Rainforest
• OpenWetWare
• Open ConnectomeProject
• LinkedScience.org
• Collective Mind Repository for computer engineering