ࡱ> 9;8 3Ebjbjss 4^= 999MMMMD$M6ZZZ/6161616161616p8;N1698"Z16WF6###d89/6#/6##_1D!3ٲM32&6\6062`;O`;L3`;93TZ>,#$ZZZ1616KZZZ6`;ZZZZZZZZZ : Data Publication from an Example Data Centre (BODC) Perspective Roy Lowry and Gwen Moncoiffe British Oceanographic Data Centre (BODC) Introduction At the 2009 meeting of the SCOR/IODE data publication working group BODC agreed to undertake a pilot project to investigate how BODC as an example of an IODE data centre could engage in data publication activities. The investigation focussed on three use cases: UC1: Base Dataset Publication. Providing infrastructure for publication and citation of base datasets used in science publications. This involves making cited, frozen versions of data packages available either exactly as delivered to the data centre or enhanced through collaborative work with the data originators and/or peer reviewers as part of the journal editorial process. UC2: Dataset Publication from Existing Ingested Data Holdings. This is the process of identifying meaningful collections of ingested, quality controlled and metadata augmented data to be instantiated as cited snapshots. Examples are the BODC past practice of CD-ROM dataset publication and the World Ocean Database releases by the US NODC. UC3: Modified Dataset Publication. Providing infrastructure for publication and citation of modified data objects associated with individual tables and figures in science publications. About BODC BODC is the UK National Oceanographic Data Centre in the IODE Network. BODC is primarily funded by the UK Natural Environment Research Council (NERC) and its primary mission is to function as NERCs designated data centre for marine data. This covers ingestion of marine data collected by NERCs institutes and collaborative centres plus NERC-funded data collected by Higher Education Institutes. Other core funded activities include the promotion of data sharing throughout the wider UK marine community through MEDIN, whose secretariat is hosted by BODC, and development of the GEBCO global bathymetry. BODC also receives a proportion of soft money that covers its participation in technology development projects such as NERC DataGrid and NETMAR, the ingestion of project datasets such as GEOTRACES and data sharing infrastructure development such as SeaDataNet and Geo-Seas. The Difference between Data Serving and Data Publication It is essential to understand the difference between the operational model of data centres such as BODC and that of libraries. The primary mechanism by which BODC delivers data to users is through a mechanism that we will term data serving. Data from many different sources are atomised into a common schema, quality assured by graphical examination and point-by-point flagging and enhanced through the addition of copious amounts of evaluation and usage metadata. The ingestion process involves significant amounts of work, involving reformatting, ingestion, metadata collation, composition of plaintext usage metadata, audit and final quality control checking. This takes time to complete, sometimes years for data considered to be low priority. Another consequence is that the data evolve into their final form through a process of continuous development rather than the creation of a series of quantised snapshots. Whilst this process of change slows at the final checking stage, it doesnt stop. Data are tagged with references to resources that may change (e.g. a clearer descriptive name may be given to a parameter code) and there is continual effort to raise metadata quality through addition of additional fields that are retrospectively supplied to legacy data. The primary discovery method for these data is through user specification of basic filters defining spatial coverage, temporal coverage and the parameters measured. These are sometimes augmented by data classification filters such as the concepts of activity (e.g. cruise), instrument, platform and project. These filters are applied to the entire atomised data repository resulting in the creation of a dynamic dataset, which is the meaningful collection of data pertaining to that specific user query. Once the dataset has been defined, it is instantiated from the current, presumed best, holdings in the atomised data repository and delivered to the user. Users typically receive a zip file containing a collection of data files, each of which is accompanied by an XHTML usage metadata report plus a metadata summary of the entire collection. This is NOT data publication. Data publication must satisfy the following criteria: The concept of dataset must be static. Repeated requests for instantiation of a given labelled dataset should always return the same object to the extent that it has been suggested to include internal checksums as dataset metadata. Others take a more relaxed view, allowing minor change to occur. However, how does one define minor? Any change in dataset content should be done through the creation of a new dataset instantiation snapshot that is labelled differently, usually through version numbering. Every version of the dataset should be citable and obtainable through the appropriate citation. The dataset is identifiable in published papers through a citation conforming to a standardised, globally recognised syntax The dataset should carry a permanent identifier (URN) that resolves to a location on the internet (URL) from where the dataset may be freely obtained without any form of authentication or authorisation. UC1: Base Dataset Publication From a data centre operational point of view this may be considered as the publication of what BODC terms accessions: deliveries of data file collections that are possibly accompanied by paper documentation. However, there is a whole spectrum of service level options that may be applied to this process. Bronze Standard Service At the minimal end, BODC could simply offer an accession publication service to its data originators, which would involve obtaining a permanent identifier such as a DOI, populating the URL to which the DOI resolves with the appropriate file set and posting an appropriate data discovery record such as Dublin Core or an ISO19115 profile. Delivering this would require significant, but feasible, infrastructure development at BODC because whilst BODC archives asis every accession that comes through the door, the filestore where these are kept is inaccessible from the Web for security reasons. This service could never apply to all BODC accessions due to issues such as access control requirements. From the data centres point of view offering such a service has the benefit that it makes accession submission more attractive to the data originator, which will result in additional data submissions from which the data centre may cherry pick data for ingestion. The service should also be adequate to allow the data centre to be certified as a suitable repository for ESSD data publications providing there are no concerns over the long term future of the data centre. It could also cover to some extent the data management requirements for scientific paper base dataset publication. Even this minimal service scenario comes with a significant risk of scalability issues. It must be considered likely that offering such a service would significantly increase the number of accessions arriving at the data centre. The publication process for each accession requires a small, but significant, amount of staff resource. There is also the issue of data storage. BODC has access to a significant storage resource with approaching 100 Terabytes of spinning disk on site. However, it would only take a handful of multi-terabyte data accessions to cause problems as there are physical limits (machine room size) as well as cost limits on storage expansion. Silver Standard Service A higher service level would involve the data centre getting involved in some degree of quality assessment and enhancement of each accession prior to its publication rather than accepting whatever comes in and publishing it. This could either be in isolation or as part of an editorial peer review process. Inevitably this would require more staff resource per accession. However, if the process could  SHAPE \* MERGEFORMAT be reduced to checking whether the accession conforms to a clear set of standards guidelines then it could require very little additional effort to basic ingestion and therefore be feasible for BODC. Expecting the data centre to take whatever comes and work it up to the required standards is not considered to be feasible. Gold Standard Service The gold standard service level would be to subject accessions that the originator wants published to the data centres full ingestion and quality assurance procedures. On completion the data are the exported as a snapshot from the data centre data system, given a DOI and published. This is considered to be totally infeasible for BODC. The level of service inevitably makes a potential difference to the quality of the published dataset, in particular to the likelihood of it being usable 25 years from now without recourse to additional sources of information. There is a view in some parts of the digital curation community that technology can provide this for any collection of files through machine-readable specification of the system (physical data encoding), structural (arrangement of information in files) and semantic (data meaning) layers. This is not shared by the authors who believe that datasets checked for conformance to standards designed to promote interoperability by data management professionals are much more likely to be of future value. Dataset Publication from Existing Holdings Dataset specification In the BODC model, every query we input to our data system generates a dataset. The problem is the identification of the queries that result in datasets worthy of data publication. The only realistic scenario where dataset publication from existing holdings is where a data originator (or originators) wish to make those data the subject of a data publication such as an ESSD paper. Consequently, the dataset specification would inevitably be the result of collaborative discussions between the data centre and the data originators. Dataset instantiation This is an area where BODC has some experience from its publications of CD-ROM datasets. Experience has shown that the metadata content of these products either as ASCII or PDF plain language documents has proved adequate to deliver human access to the data content 10-20 years after publication. The data were delivered in commercial binary formats (MS Access), bespoke binary formats and ASCII files. Experience has shown that the Access databases and bespoke binary files are still readable although this has required significant BODC effort to maintain. The ASCII copy of the data is still readily accessible through a range of off the shelf present day tools. BODC would therefore base any request to instantiate a dataset for publication on the structural models used for its CD-ROMs. Obviously, the instantiated dataset would have to conform to the standards and conventions established for UC1 silver service datasets. Dataset citation At the current time a DOI assignment combined with a Dublin Core or ISO19115 discovery record is seen as the only viable option for machine-readable citation, with a yet to be agreed universal standard syntax human-readable citation to be included in published papers . Dataset publication As part of the pilot project to develop data publications from BODCs existing holdings consideration was given as to how the publication process formerly based on CD-ROMs could be resurrected in the current age of the internet. The suggestion of developing an e-Repository internally wasnt received enthusiastically for the following reasons: It requires the creation of at least one duplicate copy of each dataset in an environment where data storage growth is limited by the physical size of the computer room. Establishing an e-Repository would require developer time and once established it would require management resources in an environment where there are many competing projects for existing staff and limitations on recruitment due to concerns about the future. Consequently, the current position from within BODC is that if ingested datasets are to be published a suitable external e-Repository needs to be identified. This could of course change if UC1 were implemented, because the same infrastructure could be used for both UC1 and UC2. E-Repository Candidates for BODC How does one go about identifying an E-Repository resource for ones organisation? It has to be admitted that the serious thought to be given to the issue was during the thinking through of the BODC data publication pilot project. There was an implicit assumption that as a data centre we would provide, but to date this hasnt been the case. Some possibilities that have come to mind are: A NERC E-Repository. NERC is currently developing a large centralised information resource at BGS Keyworth. It has also made Data Citation one of the themes for the new NERC information strategy. Whilst this strategy is in its infancy, there would seem to be merit in steering it towards establishing a NERC e-Repository within the new development. This idea isnt universally accepted, particularly by those who see any form of centralised infrastructure development as a challenge to the established data centres and by those who fail to grasp the criteria for acceptance as an accredited data store by ESSD. British Library and the Digital Curation Centre. There is definite momentum in this arena for establishing infrastructure. Exactly what and on what terms is currently unclear, but that is only because there has been no attempt to establish the necessary communication for clarification. San Diego Super-Computer Centre. There is a lot of hardware here and at least one individual with an interest in data publication. Could this be a possible way forward? Something else? It is clear that if this SCOR/IODE data publication is to be taken forward then e-Repository infrastructure will need to be identified. Modified Data Publication After due consideration, BODC can see no operational advantage in its becoming involved in the provision of the digital backbone for the publication of the processed data behind individual figures and tables in papers. However, there are clear advantages to science, not least in the improved clarity of the science publication process, in the provision of such infrastructure and therefore the use case needs to be taken forward, but this may be a responsibility more for the digital library community than the data centre community. Conclusions Guidelines are needed to direct data centres on how they can become engaged in the data publication process and used to engage a network of data centres in the activity. Standards need to be developed for dataset submissions that are to be published asis by data centres. International e-Repository infrastructure is required and the SCOR/IODE process needs to find ways to develop this. The digital library community and data editors need to be engaged in the publication of processed data behind tables and figures (the Wiebe Use Case). Journal editors and the library community need to develop standard ways of citing datasets used in journal publications in the same way as they have developed standard ways of citing reference to published written articles. It may be that these exist and all that is required is clearer flagging of their status as a standard.  EMBED Visio.Drawing.11   ,3?@Ak    %     $ % 5 6 = > ? 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