dataesr/scientific-paragraphs-categorization huggingface dataset:
The perspective of the researcher The emphasis throughout has been on the perspective of clinical researchers, considered both as data generators and as data requesters/(re)users. To be clear, by 'data generators' we mean the trialists and other study personnel that conceive of the study, and then plan, manage, monitor, analyse and publish it. This requires a complex set of intellectual and organisational skills, and we do not wish to suggest that a trial can be reduced to mere 'data generation', or that the term 'data generators' is used in any way in a derogatory sense. It is simply that, in this context, the term usefully emphasises the role of the trial as the data generation phase, and the role of the trialists as the designers and initial creators of the data set. Other actors (funders, publishers, infrastructure providers) are all of course vitally important, but the main target group for this document are researchers themselves.
The group included experts in multinational clinical trials, trial methodology and transparency, trial management services, information technology (IT) tools, and legal issues. The core group's responsibilities were to establish the multistakeholder task force, draft intermediate versions of this report, organise and manage the consensus workshops, coordinate the subgroups, and release the final version of the report. Given the complexity of the issues around sharing and reusing data from clinical trials, any attempt to develop principles and procedures requires the involvement of a wide range of stakeholders to represent the different groups generating, managing and using IPD. It was also important to ensure that a range of scientific, technical and legal expertise was present, and that different geographical regions were represented in the discussion.
The first subgroup worked on terminology, to clarify the main terms used in the project based on legal definitions, regulations and standards. The output of this subgroup is the glossary of standardised terms and definitions reported in online supplementary appendix 2. The second subgroup worked on an environmental scan of the existing data sharing repositories and other initiatives relevant for sharing of IPD, to describe current provision and highlight possible missing features or functions. The output of this subgroup will be reported in a separate publication.
► P3: Individual participant data made available for sharing should be prepared for that purpose, with de-identification of data sets to minimise the risk of reidentification. The de-identification steps that are applied should be recorded. ► P4: To promote interoperability and retain meaning within interpretation and analysis, shared data should, as far as possible, be structured, described and formatted using widely recognised data and metadata standards. ► P5: Access to individual participant data and trial documents should be as open as possible and as closed as necessary, to protect participant privacy and reduce the risk of data misuse. ► P6: In the context of managed access, any citizen or group that has both a reasonable scientific question and the expertise to answer that question should be able to request access to individual participant data and trial documents.
Irrespective of the business model adopted, the final goal must be to encourage data sharing and reuse. Long-term storage and access costs are not easily predictable and thus not easily linked to initial funding. Possible sources of support include core/structural funding, hosting organisations or private contracting, data deposition fees, access charges, or research and development (R&D) project funding. 45 The discussion on sustainable business models for data infrastructures is ongoing, and it is difficult to identify a preferred model. A particular problem is that while many established national and international data repositories have core streams of income from research funders, these sources of income are usually shortterm and may be vulnerable to change in priorities or in responsibilities.
The Organisation for Economic Co-operation and Development Global Science Forum is working with partners on two projects related to Open Data for Science, one on the sustainable business models for data repositories and a second on international coordination of data infrastructures. 46 6. To ensure more effective and widespread sharing of IPD and other data objects, organisations should be encouraged to revise their policies to allow wider data reuse. Sometimes local policies, implemented by research institutes and universities, may restrict data sharing possibilities for the data generators. These policies can derive from a variety of historical beliefs, including a general distrust of data reuse, perhaps negative prior experiences, worries about academic competition, and concern over ownership and copyright issues.
47 But such beliefs are incompatible with the new global attitudes towards data sharing and reuse, and institutional policies should be reviewed to try and ensure that such barriers are removed. 7. Data sharing should be prospectively planned, described within a designated section of the trial protocol and summarised in the relevant section of the trial registration record. To ensure data sharing is considered from the beginning of a trial, it should be included within the trial protocol. This is also suggested by other initiatives, for example in ref  17  , and mentioned as a standard item in protocols for interventional trials by the standard protocol items: recommendations for interventional trials (SPIRIT) guideline, under 'Dissemination policy': 'The protocol should indicate whether the trial protocol, full study report, anonymised participant-level dataset, and statistical code for generating the results will be made publicly available; and if so, describe the timeframe and any other conditions for access'.
48 he description of how IPD will become accessible should therefore be much more than a vague statement of intent. It would be useful also to include this information in the trial's registry entry. WHO-adopted registries, such as ClinicalTrials. gov and international standard randomised controlled trial number (trial registry) (ISRCTN), have started to include basic information on publication and dissemination plans and availability of IPD. Following an International Clinical Trials Registry Platform (ICTRP) registry network meeting in 2017, it is expected that new data elements will in time be collected by more registries and displayed through the WHO portal.
It is difficult to make a statement that is too prescriptive about the timing of 'release' of full IPD data sets for reuse. Other initiatives have attempted to define timelines: for example, the Institute of Medicine report suggested that clinical trial data that will not be part of a regulatory application be made available for sharing no later than 18 months after study completion. 15 The ICMJE originally suggested that data underlying the results presented in a journal paper be shared no more than 6 months after publication,  21  although more recently, perhaps mindful of some of the practical issues we discuss in this paper, they have provided much more flexible guidance. 50 e believe the goal should be to make trial data and documents available in a timely manner. But the exact time will depend-for instance-on the possibility and timing of publications by the primary investigators, the complexity of the study and any associated substudies, the nature of the documents or data, the amount of analysis and preparation the data might require, and the access regime under which it is planned to make it available.
There is an expectation that most trial documents (other than those describing the aggregate results, such as a clinical study report), could and should be released soon after the end of data collection. For the IPD data sets, however, we believe investigators should be confident that they have completed their own planned authorship activity before making the whole of the IPD data set available. We think it reasonable, however, to expect de-identified data supporting a specific published paper to be available relatively quickly, normally within 1 year of that paper's publication. In addition, although different portions of the data set derived from a trial may be released at different times, we believe (along with the ICM-JE  50  ) that investigators should clearly indicate when they anticipate all the data will be released.
52 We therefore recommend a broad consent for 'data sharing for scientific purposes', which explicitly excludes any other, for example, for insurance or forensic purposes. 14. An appropriate consent process for secondary use of data should ensure the following: a. The reasons for asking about data sharing, and the general benefits of data sharing in clinical research, are made clear to the trial participant. Although it is envisaged that most trial participants will willingly consent to data sharing, it is still important that potential trial participants are informed about the general benefits of such sharing for science and medical practice. This information is likely to be part of the patient information sheets. b. The nature of data preparation, storage and access is explained to the trial participant, so far as they are known at the time the patient documents are produced.
51 he practical difficulties, and associated costs, in modifying data already delivered to a separate repository should not be underestimated, and it may therefore be difficult to offer the withdrawal option once data have been deposited. There are even more difficulties in withdrawing data after they have been shared with a secondary user-in fact this may be impossible in practical terms. The key point is that any limitations to withdrawing consent for data sharing should be made clear in any explanatory material in the patient information sheets. DAtA PrePArAtIOn: PrOteCtIOn Of trIAl PArtICIPAnts P3: IPD made available for sharing should be prepared for that purpose, with de-identification of data sets to minimise the risk of reidentification. the de-identification steps that are applied should be recorded.
Anonymisation is a technique applied to personal data to make it, in practice, unidentifiable. Full (complete, or irreversible) anonymisation involves de-identification and the destruction of any link to an identified or identifiable person via a pseudonym. Effective anonymisation can be applied to a specific data set, by de-identification and removal of the link to a pseudonym, coupled with the use of new identifiers for individuals. There is no link maintained between these new internal identifiers and any others that might exist, for example in another pseudonymised data set (eg, pseudonymised data set of the sponsor). Thus, if a de-identified data set is pseudonymised, the participants in it can be identified only by those who possess the relevant 'additional information'. If a de-identified data set is fully anonymised, the participants cannot be identified by anyone (leaving aside the theoretical possibility of matching against the original clinical data).
To make it easier to review the de-identification that has occurred, we need a standardised, and ideally machine readable, way of describing those de-identification actions. 18. An assessment of the residual risks for reidentification of participants in de-identified data sets should be performed. Under the GPDR, at least in Europe, there is obligation on the data controller to carry out a data protection impact assessment (DPIA), to 'evaluate… the origin, nature, particularity and severity' of the 'risk to the rights and freedoms of natural persons' before processing personal data. The impact assessment 'should include the measures, safeguards and mechanisms envisaged for mitigating' the identified risks. This implies that the initial de-identification of data, for instance prior to its deposition in a repository, should be accompanied by such an impact assessment, ideally included within the record of de-identification described in recommendation 17.
Non-commercial clinical research infrastructures should actively support the prospective use of data standards, for instance by taking advantage of existing training, materials and supporting services, and expanding these as needed. The use of data standards in non-commercial research has been relatively limited up to now, and consequently there is a need to increase awareness of the different standards available and their uses, and develop tools and services that can help researchers apply them in practice. Infrastructure organisations, such as ECRIN and the various national networks, working with the standard development organisations, can play a key role in this. Support might range from awareness raising workshops and developing informational materials through to curating libraries of data collection instruments.
Key to that process will be academic recognition and reward for input into standard development. 26. Clinical trial data sets should always be associated with metadata that describes the characteristics of each data item (eg, type, code, name, possibly an ontology reference), as well as the schedule and design of the trial. As a minimum, a basic data dictionary and study schedule should be provided, for instance as spreadsheets, or as an (CDISC) operational data model (ODM) XML file. Ideally, however, the metadata should include the meaning of the individual data items (eg, to clarify different types of blood pressure measurement, or the meaning of 'clinically significant') either by providing brief descriptions or by referencing a published ontology. The CDISC Define. XML metadata system provides one mechanism to remove ambiguity in this way.
The more uniform data set metadata becomes, the more feasible it will be to build tools that can search, compare and aggregate data sets automatically, potentially reducing the costs of data reuse. 27. Data sets should be made available for sharing in one or more standardised file formats that can be read by a wide variety of different systems. Proprietary and statistical software formats should be avoided. Using relatively simple and generally interchangeable file formats (sometimes referred to as transport standards), which can be accessed using a variety of file manipulation tools, is an important aspect of making shared data as accessible as possible to a wide range of potential users. Any formats should, however, allow for the explicit preservation of structure within the data, including parent-child relationships.
A range of access types to shared data and documents is expected and encouraged, including different forms of controlled access. The guiding principle we encourage is that IPD and associated documents should become as openly accessible as possible. Although we believe most trial documents should be openly accessible without re-Open Access strictions, we acknowledge that IPD may pose concerns for the data controllers (the sponsors)-over protecting participant privacy-and the data generators (the investigators)-for instance over possible misinterpretation of the data. Given the current lack of established standards surrounding IPD sharing, we believe a range of access models to data sets will be inevitable. We would recommend, however, that for IPD the secondary user should as a minimum identify him or herself, and agree to some basic conditions of data use (see recommendation 29).
The right to request access to data should not be limited to specific professions or roles. As a general principle, access to data should not be limited to a specific type of requester or professional profile. In cases where the access model includes a formal evaluation of a data access application, the scientific question to be addressed, and the ability of the requesters to answer that question, is more relevant to the assessment of data requests than the requesters' current job roles. Data could be sought, for example, by students and science journalists as well as by active researchers or reviewers. The requesters or their team would, however, normally need to demonstrate the ability to draw scientifically literate conclusions from the data. If access is formally managed, the data requester may need to provide a research protocol and analysis plan, including information on data management, data storage and plans for publication of the results of the reanalysis.
Inconsistent decisions should be avoided and criteria should be explicit. 35. To simplify the request process, repositories should be encouraged to make the interface presented to secondary users as consistent as possible. Processes, information requirements and proformas should be the same or very similar between different repositories, to make life simpler for all concerned but especially the secondary data users. It may even be possible to develop a common 'access request pipeline', especially for smaller repositories, so that associated costs could be shared, even if each repository retains the rights to individually approve or reject requests. Taking this one stage further, it should also be possible to share boards across repositories. The existing CSDR scheme provides a similar approach, with data generated and stored by different commercial companies, but with the Wellcome Trust orchestrating the process and supporting a common Independent Review Panel.
Such feedback could be a useful complement to the data described in recommendation 38, helping to improve transparency and increase user involvement, as well as providing direct feedback to repositories. Implementation could be by individual repositories or by an external service, or by some combination of the two. DAtA MAnAgeMent AnD rePOsItOrIes P8: besides the IPD data sets, other clinical trial data objects should be made available for sharing (eg, protocols, clinical study reports, statistical analysis plans, blank consent forms) to allow a full understanding of any data set. In any discussion about data sharing the emphasis is naturally on the data sets themselves. But to fully understand that data requires the context, purpose and timing of the data collection to be clear, as well as the processing and analysis that were originally carried out on that data.
The available standards, requirements and certification instruments for trusted data repositories need to be examined and their applicability to clinical research data objects needs to be checked. If necessary, extensions or adaptions should be provided. There will also be a need to develop or adapt sustainable systems to assess repositories for clinical data and data objects against these standards. This is all work still to be undertaken but, given the likely variety of repositories that will be available to researchers, we see it as a necessary part of any acceptable data sharing environment. Research infrastructure organisations can play a key role in developing and disseminating both the standards and the assessment systems. 41. Information about the different repositories that hold clinical research objects should be made available to data generators so that they can make an informed choice, so far as local policies allow.
This information should include costs as well as the features and access options available, and any assessment against the quality standards described above. The purpose is simply to assist the data generators in their decision on where to store data objects, as well as to encourage some healthy competition between repositories. We envisage a central service giving information and contact details on the repositories available, similar to the data provided now by re3data for general repositories (we believe the current re3dataset would need substantial modification to support the needs of clinical researchers selecting repositories). Ideally the repositories themselves would find it beneficial to keep their records within such a system as up to date as possible. 42. The transfer of any data objects to repositories (including those within the same institution) should be subject to a formal agreement that set out the roles, rights and responsibilities of the data generators and the repository managers.
We would expect a data transfer agreement to apply to the transfer of data and documents to a repository. In other words, the transfer should always be a formal arrangement, with the responsibilities of each party clearly set out, rather than an informal upload. Aspects that are particularly important include the agreed access regime for the data, the mechanism by which any future data sharing decisions will be made and the assignment of the data controller role. 43. Mechanisms for implementing an 'analysis environment ',  allowing in situ analysis of data sets but preventing downloads, should be further evaluated. Such an analysis environment should allow different data sets from different host repositories to be combined on a temporary basis This would be a specialist repository facility analogous in many ways to the 'glove boxes' or analysis environments now made available for examining some pharmaceutical research data.
Open Access One could envisage a web-based system that provided the necessary fields and prompts and that could be made available to data generators. It is important that wherever possible it is the data generators that create the metadata, as only they have the full knowledge of the material required (although they might not provide the metadata until the data objects are about to be transferred to a repository). The advantage of web-based data collection is that it could also aggregate the data for different repositories at the same time, because the data would be stored in the same 'back end' database system. This would then make it much easier to make the data available through a single portal.
The reasoning behind this position was that, ultimately, data sharing and reuse are intended to help improve the health of all, and the utility of data sharing is increased if it encompasses all trial participants. At the heart of the debate was the different emphasis people put on the autonomy, privacy and safety of the individual, versus the potential gains to society from increasing the ease and efficacy of data sharing. The majority in the task force felt, however, that distinct consents were necessary, and in any case a single consent process would be hard to implement within the current legislative frameworks, at least for pseudonymised data (see recommendations 12 and 14). Nevertheless, it was clear that this issue raised considerable and passionate debate, and that it deserves more detailed research and discussion involving experts in medical ethics and law, researchers, trial participants and citizens.
Thus, we have emphasised the need to develop appropriate support systems for planning data sharing and for preparing data, and for finding and accessing the data in ways that respect the concerns of both generators and secondary users. the future role of repositories Several questions for the future concern data repositories. These have been recognised as useful tools in allowing data sharing in other scientific domains, and we urge their further development (see principle 9), but so far they have been little used for clinical trial data. The environmental scan performed within the context of this project has shown that there are several repositories already available (eg, B2SHARE, EASY, Zenodo, Dryad, Figshare) that do include at least some clinical trial data sets, and several more are under development (eg, the MRCT's Vivli).