Workshops prior to the International Digital Curation Conference

Pre-conference workshops can be very useful and interesting; they can be a good part of the justification for attending a conference, giving an extended opportunity to focus on a single topic, followed by a broader (but shallower) look at many topics, at the conference itself. This time it is quite frustrating, as I would very much like to go to all the workshops! There is still time to register for your choice, and for the IDCC conference itself.

Disciplinary Dimensions of Digital Curation: New Perspectives on Research Data


Our SCARP Project case studies have explored data curation practice across a variety of clinical, life, social, humanities, physical and engineering research communities. This workshop is the final event in SCARP, and will present the reports and synthesis.

See the full programme [PDF]

Digital Curation 101 Lite Training


Research councils and funding bodies are increasingly requiring evidence of adequate and appropriate provisions for data management and curation in new grant funding applications. This one-day training workshop is aimed at researchers and those who support researchers and want to learn more about how to develop sound data management and curation plans.

See the full programme [PDF]

Citability of Research Data


Goal: Handling research datasets as unique, independent, citable research objects offers a wide variety of opportunities.

The goal of the new DataCite cooperation is to establish a not-for-profit agency that enables organisations to register research datasets and assign persistent identifiers to them.

Citable datasets are accessible and can be integrated into existing catalogues and infrastructures. A citable datasets furthermore rewards scientists for their extra-work in storage and quality control of data by granting scientific reputation through cite-counts. The workshop will examine the different methods for the enabling of citable datasets and discuss common best practices and challenges for the future.

▪ See the full programme [PDF]

Repository Preservation Infrastructure (REPRISE)
(co-organised by the OGF Repositories Group, OGF-Europe, D-Grid/WissGrid)


Following on from the successful Repository Curation Service Environments (RECURSE) Workshop at IDCC 2008, this workshop discusses digital repositories and their specific requirements for/as preservation infrastructure, as well as their role within a preservation environment.

Libraries of the Future: SourceForge as Repository?

In his talk (which he pre-announced on his resumed blog), Peter Murray-Rust (PMR) suggested (as he has done previously) that we might like to think of SourceForge as an alternative model for a scholarly repository (“Sourceforge. A true repository where I store all my code, versioned, preserved, sharable”). I’ve previously put forward a related suggestion, stimulated by PMR’s earlier remarks, on the JISC-Repositories email list, where it got a bit of consideration. But this time the reaction, especially via the Twitter #lotf09 feed, was quite a bit stronger. Reactions really fell into two groups: firstly something like: SourceForge was setting our sights way too low; it’s ugly, cluttered by adverts, and SLOOOOOWWW (I can’t find the actual quote in my Twitter search; maybe it was on Second Life). Secondly, the use cases are different, eg @lescarr: “Repositories will look like sourceforge when researchers look like developers” (it might be worth noting that PMR is a developer as well as a researcher).

Through my JISC-Repositories explorations, I was already beginning to be convinced by the “different use-case” argument, although it was not articulated that way. SourceForge acts as a platform providing a range of services and utilities supporting the development of software by disparate teams of developers. Is there a parallel use case in the repositories area?

The closest I could come was some of my suggestions from my Research Repository System posts, for moving the repository upstream in the researcher’s workflow, and specifically helping authors write multi-author articles. This is a reasonable parallel in several ways, but there are some significant differences.

Software source files are simple text files, completely independent of whatever system is used to edit them. The source of a software system comprises many individual software modules, each of which is usually in a separate file and can be edited independently. There are strong file name conventions, and complex “recipe” systems (eg make files) for converting them from source to actionable programs, combining them with software libraries and system-wide variables. If one developer changes one module, the system “knows” how to rebuild itself.

Journal articles, by contrast, are mostly written using proprietary (sometimes open source) office systems which create and edit highly complex files whose formats are closely linked to the application. Apart from some graphic and tabular elements, an article will usually be one file, and if not, there is no convention on how it might be composed. Workflow for multi-author articles is entirely dependent on the lead author, who will usually work with colleagues to assign sections for authoring, gather these contributions, assemble and edit them into a coherent story, circulating this repeatedly for comments and suggested improvements (sometimes using tracked change features).

Using LaTeX and include files, it might be possible to re-create a similar approach to that used in software, but for the human reader, the absence of a single editorial “voice” would be very apparent. And anyway, most of us just don’t want to work that way. I got out of the habit of writing in LaTeX around 20 years ago, when word processors began to arrive on workable desktop computers (Word on the early Macs), and I’d prefer not to go back.

Oh, and while it’s a “category mistake” to confuse SourceForge with any particular version control system, it looks to me (and at least one respondent on JISC-Repositories) as if distributed systems like git are fitter for purpose (in any kind of distributed authoring system) than their more centralised companions like VCS, SVN etc.

Well, is PMR’s suggestion of SourceForge as a model for scholarly repositories entirely a dead duck? I think it probably is, but I do hope that those who design repository systems, and indeed virtual research environments, do think hard about the capabilities of such systems when thinking through their responses to user requirements. And particularly where those requirements relate to what the researchers and authors need, rather than their institutions, libraries or readers.

More posts on International repositories workshop

Just to note a post by Jeremy Frumkin from Arizona, who like me was in the Organisation breakout, and another by Maurice Vanderfeesten from the SURFfoundation, who was in the Identifiers workshop, and gives a very clear summary of what resulted there.

International Repositories Infrastructure workshop

Amsterdam in Spring, who could turn down the offer? Perhaps it would be irresistible a little later in Spring than early March (brrr), but when the sun did come out, and the workshop was done, it was lovely. I was in Amsterdam for a curious International workshop on repository infrastructure, funded by JISC and SURF, with the DRIVER project. It turns out I had no idea what repository infrastructure meant before I went, and I guess I know only a little more now.

I was asked to take part in this workshop late last year, and was supposed to stimulate discussion on a use case on preservation. There were 4 use cases:

• Preservation
• Access
• Deposit Workflows and Environments
• Online reputation and reporting

Maybe some of us didn’t do enough work on this, as somewhere along the line this morphed into 4 proposed action plans, each with a breakout group:

• Identifier infrastructure
• Citation Services
• Repository handshake
• Organisation Structures

The first 3 of those probably fit with the last 2 use cases, but I don’t know what happened to the others, or where the last one came from.

If you use Twitter, you can read (in reverse order) some of the backchat on this through the hashtags #repinf09 (for the whole workshop), #rihs09 (for the handshake group) and #reporg09 (for the organization group). If you do have a look, bear in mind that what you read is devoid of context, and represents only a small part of what was going on, probably from a vocal, cantankerous, ornery, rumbustious and maybe just plain rude subset! (As a new Twit, I haven’t yet worked out how much ruder tweeting during a meeting is, compared with passing notes in class, say.) Oh, and not all the Twits were actually there.

So what happened? The introductory presentation was given by Norbert Lossau of DRIVER. Lots of interesting stuff, but I was a bit taken aback by claims that the defining vision of repositories was the Berlin Open Access Declaration, and that data were out of scope. Personally I think Open Access is most often a Good Thing, but sometimes it’s inappropriate: repositories of sensitive data, for instance. And I’m not at all sure that you can cleanly distinguish document from data, or that it makes sense to do so, especially when supplementary materials and extended documents come into the frame.

I was in the organisation group, so I don’t know in detail what happened in the other groups, but we did come together right at the end for a plenary. I was particularly impressed by what Les Carr said about the Citation Group, including the idea of creating a test corpus, and also a competition for the best text mining algorithms to find citations and references (and even their surrounding context: “we illustrate the errors in Rusbridge (2006)" is clearly different from “following the excellent suggestions given in Carr (2009)"). I don’t think much was said about the citation microformat (perhaps it really is dead?), nor about whether text mining might be aided by embedding RDF etc in documents. Nevertheless, a sensible plan of work was laid out.

On identifiers, it also sounded as if some sensible progress was made. In particular, it seemed as if identifiers for authors (as disambiguation tools for citations etc) went from being ruled out to being a strong part of the work plan. They had the ultimately cool mindmap.

From the repository handshake tweets, it looked like they had a bumpy ride getting their 8 use cases agreed, but did get through their “stormin’, normin’ and formin’” stages into at least the first part of “performin’”. I did like “beg” as a repository verb!

So to the repository organisation group. Here too, there were plenty of storms, and maybe the odd teacup. It was quite hard to work out what sort of organization we were interested in; what it was intended to do. There was a strong feeling of unspoken sub-text; whatever it was we were talking about was proposed to launch on October 7. One of the best quotes for me came from Sandy Payette; she said the DSpace/FEDORA organizations could provide some of the things that were being talked about, but they would have to “feel the hunger”. It was difficult to feel the hunger for whatever this thing was. At one point, I’m afraid I compared it unfavourably with jelly; whenever I thought I had hold of it, something bulged out somewhere else (yucky image, sorry).

On the start of day 2 our organisers had a new approach, which worked better. They broke the breakout into yet smaller breakouts, and gave each of us a role to play and 6 questions to answer. My table was “funders”. That’s OK, I’ve been one, I could handle that (even funded repository work back in 1998 or thereabouts, think Harnad’s CogPrints and Krichel’s WoPEc/RePEc, which made it particularly annoying to be patronized at one point as someone who obviously didn’t know much about repositories). I think the two main “expectations” for our group were “clarity of aims” and “benefits to justify investment”. Anyway, the result of all this was that, by the skin of our teeth, we did have something to say at the final plenary. Not that I yet know quite what this organization would be for!

Was it entirely coincidental in this context that the DRIVER project was ending in a few months? Well, we had heard that DRIVER did repository infrastructure, that DRIVER did published papers, not data, that DRIVER Guideline enabled interoperability, that DRIVER Guidelines were in demand internationally and had been translated into (2? 3?) other languages, and that the continuation of the DRIVER brand was seen as important. Some Twit asked “If the DRIVER Guidelines are the answer, what is the question?” Join the dots…

The workshop was ended with some closing remarks from Cliff Lynch, as perspicacious as ever, but slightly more hoarse than usual (not from shouting at us; too much inter-planetary travel, I suspect). And after the workshop there was a “funders’ meeting”. Real funders, the kind with money. What went on there, I have no idea!

Repository preservation revisited

Are institutional repositories set up and resourced to preserve their contents over the long term? Potentially contradictory evidence has emerged from my various questions related to this topic.

You may remember that on the Digital Curation Blog and the JISC-Repositories JISCmail list on 23 February 2009, I referred to some feedback from two Ideas (here and here) on the JISC Ideascale site last year, and asked 3 further questions relating to repository managers’ views of the intentions of their repositories. Given a low rate of response to the original posting (which asked for votes on the original Ideascale site), I followed this up on the JISC-Repositories list (but through oversight, not on the blog), offering the same 3 questions in a Doodle poll. The results of the several different votes appear contradictory, although I hope we can glean something useful from them.

I should emphasise that this is definitely not methodologically sound research; in fact, there are methodological holes here large enough to drive a Mack truck through! Nevertheless, we may be able to glean something useful. To recap, here are the various questions I asked, with a brief description of their audience, plus the outcomes:

a) Audience, JISC-selected “expert” group of developers, repository managers and assorted luminaries. Second point is the same audience, a little later.

• Idea: “The repository should be a full OAIS [CCSDS 2002] preservation system.” Result 3 votes in favour, 16 votes against, net -13 votes.
• Idea: “Repository should aspire to make contents accessible and usable over the medium term.” Result: 13 votes in favour, 1 vote against, net +12 votes.

b) Audience JISC-Repositories list and Digital Curation Blog readership. Three Ideas on Ideascale, with the results shown (note, respondents did not need to identify themselves):

• My repository does not aim for accessibility and/or usability of its contents beyond the short term (say 3 years). Result 2 votes in favour, none against.
• My repository aims for accessibility and/or usability of its contents for the medium term (say 4 to 10 years). Result 5 votes in favour, none against.
• My repository aims for accessibility and/or usability of its contents for the long term (say greater than 10 years). Result 8 votes in favour, 1 vote against, net +7 votes.

A further comment was left on the Digital Curation Blog, to the effect that since most repository managers were mainly seeing deposit of PDFs, they felt (perhaps naively) sufficiently confident to assume these would be useable for 10 years.

c) Audience JISC-Repositories list. Three exclusive options on a Doodle poll, exact wording as in (c), no option to vote against any option, with the results shown below (note, Doodle asks respondents to provide a name and most did, with affiliation, although there is no validation of the name supplied):

• My repository does not aim for accessibility and/or usability of its contents beyond the short term (say 3 years). Result 1 vote in favour.
• My repository aims for accessibility and/or usability of its contents for the medium term (say 4 to 10 years). Result 0 votes in favour.
• My repository aims for accessibility and/or usability of its contents for the long term (say greater than 10 years). Result 22 votes in favour.

I guess the first thing is to notice the differences between the 3 sets of results. The first would imply that long term is definitely off the agenda, and medium term is reasonable. The second is 50-50 split between long term and the short/medium term combination. The third is overwhelmingly in favour of long term (as defined).

By now you can also see at least some of the methodological problems, including differing audiences, differing anonymity, and differing wording (firstly in relation to the use of the term “OAIS”, and secondly in relation to the timescales attached to short, medium and long term). So, you can draw your own conclusions, including that none can be drawn from the available data!

Note, I would not draw any conclusions from the actual numerical votes on their own, but perhaps we can from the values within each group. However, ever hasty if not foolhardy, here are my own tentative interpretations:

• First, even “experts” are alarmed at the potential implications of the term “OAIS”.
• Second, repository managers don’t believe that keeping resources accessible and/or usable for 10 years (in the context of the types of material they currently manage in repositories) will give them major problems.
• Third, repository managers don’t identify “accessibility and/or usability of its contents for the long term” as implying the mechanisms of an OAIS (this is perhaps rather a stretch given my second conclusion).

So, where to next? I’m thinking of asking some further questions, again of the JISC-Repositories list and the audience of the Digital Curation Blog. However, this time I’m asking for feedback on the questions, before setting up the Doodle poll. My draft texts are

• My repository is resourced and is intended to keep its contents accessible and usable for the long term, through potential technology and community changes, implying at least some of the requirements of an OAIS.
• My repository is resourced and is intended to keep its contents accessible and usable unless there are significant changes in technology or community, ie it does not aim to be an OAIS.
• Some other choice, please explain in free text…

Are those reasonable questions? Or perhaps, please help me improve them!

This post is made both to the Digital Curation Blog and to the JISC-repositories list...

OAIS: CCSDS. (2002). Reference Model for an Open Archival Information System (OAIS). Retrieved from http://public.ccsds.org/publications/archive/650x0b1.pdf.

Repositories and preservation

I have a question about how repository managers view their role in relation to long term preservation.

I’m a member of the Blue Ribbon Task Force on Sustainable Digital Preservation and Access (hereafter BRTF). At our monthly teleconference last week, we were talking about preservation scenarios, and I suggested the Institutional Repository system, adding that my investigations had shown that repository managers did not (generally) feel they had long term preservation in their brief. There was some consternation at this, and a question as to whether this was based on UK repositories, as there was an expressed feeling that US repositories generally would have preservation as an aim.

My comment was based on a number of ad hoc observations and discussions over the years. But more recently I reported in an analysis of commentary on my Research Repository System ideas on discussions that had taken place on Ideascale last year, during preparatory work for a revision of the JISC Repositories Roadmap.

In this Ideascale discussion, I put forward an Idea relating to Long Term preservation: “The repository should be a full OAIS preservation system”, with the text:

“We should at least have this on the table. I think repositories are good for preservation, but the question here is whether they should go much further than they currently do in attempting to invest now to combat the effects of later technology and designated community knowledge base change...”

See http://jiscrepository.ideascale.com/akira/dtd/2276-784. This Idea turned out to be the most unpopular Idea in the entire discussion, now having gathered only 3 votes for and 16 votes against (net -13).

Rather shocked at this, I formulated another Idea, see http://jiscrepository.ideascale.com/akira/dtd/2643-784: “Repository should aspire to make contents accessible and usable over the medium term”, with the text:

“A repository should be for content which is required and expected to be useful over a significant period. It may host more transient content, but by and large the point of a repository is persistence. While suggesting a repository should be a "full OAIS" has not proved acceptable to this group so far, investment in a repository and this need for persistence suggest that repository managers should aim to make their content both accessible and usable over the medium (rather than short) term. For the purposes of this exercise, let's suggest factors of around 3: short term 3 years, medium term around 10 years, long term around 30 years plus. Ten years is a reasonable period to aspire to; it justifies investment, but is unlikely to cover too many major content migrations.

“To achieve this, I think repository management should assess their repository and its policies. Using OAIS at a high level as a yard stick would be appropriate. Full compliance would not be required, but thought to each major concept and element would be good practice.”

This Idea was much more successful, with 13 votes for and only one vote against, for a net positive 12 votes. (For comparison, the most popular Idea, “Define repository as part of the user’s (author/researcher/learner) workflow” received 31 votes for and 3 against, net 28.)

Now it may be that the way the first Idea was phrased was the cause of its unpopularity. It appears that the 4 letters OAIS turn a lot of people off!

So, here are 3 possible statements:

1) My repository does not aim for accessibility and/or usability of its contents beyond the short term (say 3 years)
(http://jiscrepository.ideascale.com/akira/dtd/14100-784 )

2) My repository aims for accessibility and/or usability of its contents for the medium term (say 4 to 10 years)
(http://jiscrepository.ideascale.com/akira/dtd/14101-784 )

3) My repository aims for accessibility and/or usability of its contents for the long term (say greater than 10 years).
(http://jiscrepository.ideascale.com/akira/dtd/14102-784 )

Could repository managers tell me which they feel is the appropriate answer for them? Just click on the appropriate URI and vote it up (you may have to register, I’m not sure).

(ermmm, I hope JISC doesn’t mind my using the site like that… I think it’s within the original spirit!)

(This was also a post to the JISC-Repositories list)

Gibbons, next generation academics, and ir-plus

Merrilee on the hangingtogether blog, with a catchup post about the fall CNI meeting, drew our attention to a presentation by Susan Gibbons of Rochester, on studying next generation academics (ie graduate students), as preparation for enhancements to their repository system, ir-plus.

I shared a platform with Susan only last year in Sydney, and I was very impressed with their approach of using anthropological techniques to study and learn from their user behaviour. In fact, her Sydney presentation probably had a big influence on the ideas for the Research Repository System that I wrote about earlier (which I should have acknowledged at the time).

Now their latest IMLS-funded research project takes this even further, as preparation for collaborative authoring and other tools integrated with the repository. If you're interested in making your repository more relevant to your users, the report on the user studies they have undertaken so far is a Must-Read! I don't know whether the code at http://code.google.com/p/irplus/ is yet complete...

Project data life course

This blog post is an attempt to explore the “life course” of an arbitrary small to medium research project with respect to data resources involved in the project. (I want to avoid the term life cycle, since we use this in relation to the actual data.)

This seems like a useful exercise to attempt, even if it has to be an over-generalisation, as understanding these interactions may help to define services that support projects in managing and curating their data better, and a number of such services are suggested here. This is about “Small Science”; James M. Caruthers, a professor of chemical engineering at Purdue University has claimed ‘Small Science will produce 2-3 times more data than Big Science, but is much more at risk’ (Carlson, 2006). Large and very large projects tend to have very particular approaches, and probably represent significant expertise; I’ll not presume to cover them.

Is this generalisation way off the mark? I’d really like to know how to improve it, accepting that it is a generalisation!

The overall life course of a project (I suggest) is roughly:

• pre-proposal stage (when ideas are discussed amongst colleagues, before a general outline of a proposal is settled on), followed by
• the proposal stage (constrained by funder’s requirements, and by the need to create a workable project balancing expected science outcomes, resources available, and papers and other reputational advantages to be secured). If the project is funded, there follows
• an establishment phase, when the necessary resources are acquired, configured and tested, (which overlaps and merges with)
• an execution phase when the research is actually done, and
• a termination phase as the project draws to a close.
• Somewhere during this process, one or more papers will be produced based on the research understandings gained, linked to the data collected and analysed.

My message here is that curation is most impacted by decisions in the first 3 phases, even though it requires attention throughout!

Pre-proposal stage
At the pre-proposal stage, you and your potential partners will mostly be concerned with working out if your research idea is likely to be feasible, how and with roughly what resources. During these conversations, you will need to identify any external or already existing data resources that will be required to enable the project to succeed. You should also start to identify the data that the project would create, or perhaps update, and how these data will support the research conclusions. In doing so, attention must be paid to resource constraints, not necessarily financial, but also legal and ethical issues affecting use of the data. However, discussions are more likely to be generic rather than focused! Thus begins the impact on curation…

Curation service: 5-minute curation introduction, with pointers to more information…
Curation service: Help Desk service. Ask a Curator?

Proposal stage
Apart from the obvious focus on the detailed plan for the research itself, this stage is particularly constrained by funder requirements. Increasingly, these requirements include a data management plan. This is unlikely to be a problem for large projects, which will already have spent some time (often lots of time) considering data management issues, but may well be a new requirement for smaller projects. However, forcing attention to be paid to data management is definitely a Good Thing! I’ll have a closer look at data management plans in a later blog post.

Curation service: Data Management Plan templates
Curation service: Data Management Plan online wizards?
Curation service: consultancy to help you write your Data Management Plan?

Key issues that the project should address, and which should be reflected in the data management plan, include the standards and encodings for analysing, managing and storing data. While these must be determined by a combination of local requirements, such as the availability of licences, skills and experience, and the local IT environment, they must take account of community norms and standards. While in some cases maverick approaches can lead to breakthrough science, they can also lead to silo data, inaccessible and not re-usable (sometimes not re-usable even by their creators, after a short while). This stage begins to have a significant effect on curation, as the decisions that are fore-shadowed here will have major effects later on. Repeat after me: curation begins before creation!

Curation service: Guidance on managing data for re-use in the medium to long term
Curation service: registries and repositories to support re-use, sharing and preservation
Curation service: pointers to relevant standards, vocabularies etc.

[Note, we have concerns about the scalability of the latter, which is why the DCC DIFFUSE service is being re-modelled to be more participative.]

Establishment stage
It’s during the establishment phase that the real work is in sight. In the case of a well-established laboratory or research centre, this may merely be “yet another project” to be fitted into well-known procedures, perhaps with some adaptations. But from my observation and anecdotally, there is often a high degree of individual idiosyncratic decision-making taking place here; the focus is often on “getting down to the research”. The consequences of this for curation may be very significant, but are unlikely to be apparent until much later.

The key curation aim is to set the data management plan into operation. This requires ensuring access to external data required by the project (an activity that should have been started, at least in principle, ahead of project approval). While you’re thinking of access, rights and ownership, negotiating and documenting data ownership and access agreements for the data created in the project would be a smart idea (too often ignored, or left until problems begin to arise). Of course, it’s not just rights that are at issue, but also responsibilities, particularly where data have privacy and ethical implications.

Curation service: Briefing papers on legal, ethical and licence issues.

Meanwhile a critical step is establishing the IT infrastructure. While the focus is likely to be on acquiring and testing the data acquisition and analysis equipment, software, capabilities and workflows, in practice the apparently background activities of ensuring adequate data storage, sensible disaster recovery procedures (or at the very least, proper data backup and recovery), and thoughtful data curation processes will be critical for later re-use.

Curation service: Briefing paper on Keeping your data safe?
Curation service: tools for various tasks, eg data audit, risk assessment

It’s worth remembering that there are different kinds of data storage. While you will often be most concerned with temporary or project-lifetime storage, you may need to think about storage with greater persistence. There may be a laboratory or institutional or subject repository, external database or data service that will be critical to your project; negotiating with the curation service providers associated with these services should be an important early step. In effect, right at the start you are planning for your exit! But more on this another time…

Curation service: Guidance on data repositories for projects?
Curation service: thought-stimulating discussion papers, blog posts and case studies, journal, conference, discussion fora…

Project execution
Through the lifetime of your project, your focus will rightly be on the research itself. But you should also take time out to test your disaster recovery procedures, and check on your quality assurance. You care about the quality of your materials and syntheses (or your algorithms, or your documentary sources), you need to care as much about the quality of your data, both as-observed and as-processed. You’ll be collecting a lot of data; if some support your hypothesis and some contradict it, you’ll need to ensure you are collecting (perhaps in laboratory notebooks or equivalent) sufficient provenance and context to justify the selection of the former rather than the latter.

Not sure if there is a curation service here, or if these are good practice research guides for your particular domain… but I guess the same could be said for standards and vocabularies. Question is whether domains HAVE good practice guides for data quality?

As the project goes forward, issues may arise in your original data management plan, and you should take the time to refine it (and document the changes), and your associated curation processes. If you did take idiosyncratic decisions in haste at project establishment, at some point you may need to review them. It’s a warning sign when a staffing change is followed by proposals for major architectural changes!

Finally, at some stage you should test any external deposit procedures built into your plan.

Curation service: Guidance on data deposit…

I don’t think I’m claiming that this is the limit of curation issues during project execution; rather that here the course of projects is so varied that generalisations are even less justifiable than elsewhere. Nevertheless, the analysis here should be strengthened, so input would be helpful!

Project termination stage
As the project comes towards an end, you enter another risk phase. Firstly, most management focus is likely to be on the next project (or the one after that!). Secondly, if employment is fixed term, tied to the particular project, then research staff will have been looking for other posts as the end of the project draws near, and the project may start to look denuded (and the data management and informatics folk may be the most marketable, leaving you exposed). And of course, the final reports etc cannot be written until the project is finished, by which time the project’s staffing resources will have disappeared. It’s the PI’s job to ensure these final project tasks are properly completed, but it’s not surprising that there are problems sometimes!

Curation service: Guidance on (or assistance with) evaluation

During this final phase, you must identify any data resources of continuing value (this should have occurred earlier, but does need re-visiting), and carry out the plans to deposit them in an appropriate location, together with the necessary contextual and provenance information. Easy, hey? Perhaps not: but failure here could have a negative impact on future grants, if research funders do their compliance checking properly.

Curation service: Guidance on appraisal, Guidance on data deposit.

Finally, given that data management plans are currently in their infancy, it’s worth commenting on the plan outcomes in your project final report!

Writing papers
This is not really a project phase as such, as often several papers will be produced at different stages of the project. The key issues here are:

• Include supplementary data with your paper where possible
• Ensure data embedded in the text are machine readable
• Cite your data sources
• Ensure supportive data are well-curated and kept available (preferably accessible; this is where a repository service may come in useful).

I’ll write more on this in a separate post.

Curation service: Proposals for data citation
Curation service: Suggestions for the Well-supported article

So: the message is that curation should be a constant theme, albeit as background during most of the project execution. But the decisions taken during pre-proposal, proposal and establishment phases will have a big effect on your ability to curate your data, which may affect your research results, and will certainly affect the quality and re-usability of the data you deposit.

Carlson, S. (2006, June 23). Lost in a Sea of Science Data: Librarians are called in to archive huge amounts of information, but cultural and financial barriers stand in the way. The Chronicle of Higher Education, 52, 35.

DCC White Rose day

Fresh from a fascinating day in Sheffield, organised by the DCC and the White Rose e-Science folk. Objectives for the day included building closer relationships between White Rose and DCC, helping us learn more about their approach to e-Science, identify data issues, and influence the DCC agenda!

After introductory remarks, the day started with Martin Lewis, Sheffield Librarian, talking about the UK Research Data Service (UKRDS) feasibility study. Martin was keen to emphasise the last two words; it’s important to manage expectations here, and we’re a long way from an operational service. There’ll be a conference to discuss the detailed proposals in February 2009, after which they hope to get funding for several Pathfinder projects. Martin and I argued ferociously, as we always do, but I should be clear that this has the potential to be an extremely valuable development. The really difficult conundrum is getting the balance of sustainability, scalability, persistence and domain science involvement in the curation. Oh, plus an appealing pitch to the potential funders. Not at all an easy balance!

Then we heard from Dr Darren Treanor from Leeds about their virtual slide library for histopathology; he claims it as one of the largest in the world, with over 40K slides digitised, even if only a thousand or so are fully described and publicly available. At 10 Gb or more a slide, these are not small; not just storage but bandwidth becomes a very real issue when accessing them. We had a brief discussion about technologies that optimise bandwidth for view very large or high resolution images; think Google Earth as one example, or the amazing Seadragon, created by Blaise Aguera y Arcas and now owned by Microsoft (the technology appears to be incorporated into Photosynth, but I can’t explore it, as it doesn’t work in my OS!).

Sarah Jones from the DCC and HATII at Glasgow spoke about the Data Audit Framework, now being piloted at 4 sites. This is a tool aimed at helping institutions to discover their research data resources, and begin to understand the extent to which they are at risk. More about that one later, I think!

Then we heard about 3 more very different projects, although Virtual Vellum probably had more in common with the virtual slide library than the presenter would have previously expected. This project shows digitised and cleaned up medieval manuscripts, with their TEI-based transcription in parallel. We heard an entertaining rant against SRB (wrong tool for the job, I think), but more worryingly that these projects were strongly constrained by IPR problems (yes, the digitised versions of half-millennium-old manuscripts do acquire new copyright status, and can also be ringed about with contractual restrictions). So much for open scholarship!

We also heard about the CARMEN project, aiming to support sharing and collaboration in neuroscience. Graham Pryor will be releasing a report from his involvement with CARMEN before too long, so I won’t dwell on it, other than to say it is a really good project that has thought a lot of issues through very carefully. It also has one decent and one cringeworthy acronym: MINI, for the Minimum Information for a Neuroscience Investigation, and MIAOWS, for Minimum Information About a Web Service… but maybe Frank Gibson was pulling our legs, since I didn’t find it on a Google search, nor is it in the MIBBI (Minimum Information for Biological and Biomedical Investigations) Portal!

Finally we heard about the University of York Digital Library developments; this is not so much a project as the development phases of a service. They've choesn Fedora plus Muradora as their technology platform, but it was clear again that this was a thoughtful project, recognising that there's much more to it than "build it and they will come".

This was a really interesting day; I hope we gave good value; I certainly learned a lot. Thanks everyone, especially Dr Joanna Schmidt, who organised it with Martin Donnelly.

Some interesting posts elsewhere

I’m sorry for the gap in posting; I’ve been taking a couple of weeks of leave at the end of my trip to Australia. Since return I’ve been catching up on my blog reading, and there are some interesting posts around.

A couple of people (Robin Rice and Jim Downing in particular) have mentioned the post Modelling and storing a phonetics database inside a store, from the Less Talk, More Code blog (Ben O'Steen). This is a practical report on the steps Ben took to put a database into a Fedora Commons-based repository. He details the analysis he went through, the mappings he made, the approaches to capturing representation information, to making the data citable at different levels of granularity, and an interesting approach that he calls “curation by addition”, which appears to be a way of curating the data incrementally, capturing provenance information of all the changes made. It’s a great report, and I look forward to more practical reports of this nature.

Quite a different post on peanubutter (whose author might be Frank Gibson): The Triumvirate of Scientific Data discusses ideas that he suggests relate to the significant properties of science data. His triumvirate comprises

"content, syntax, and semantics, or more simply put -What do we want to say? How do we say it? What does it all mean?"

Oddly, the discussion associated with this blog post is on Friendfeed rather than associated with the blog itself. Very interesting to see the discussion recorded like that, and in the process see at least one sceptic become more convinced!

To me, there seemed to be strong resonances between his argument and some of the OAIS concepts, particularly Representation Information. However, context, syntax and semantics might be a more approachable set of labels than RepInfo!

ARROW Repositories day: 3

Dr Alex Cook from the Australian Research Council (a money man! Important!) talking on the Excellence in Research Framework (ERA), the Access Framework and ASHER. ERA appears to be like the UK’s erstwhile RAE, and will use existing HE Research Data Collection rules for publication and research income information where possible. 8 clusters of disciplines have been identified. Currently looking at the bibliometric and other indicators which will be discipline-specific (principles, methodologies and a matrix showing which are used where). Developing the System to Evaluate Excellence of Research (SEER) that will involve institutions uploading their data; sounds like something that MUST (and they say will) work with repositories (RAE in UK too often went for separate bibliographic databases, not interoperable, which meant doing the same thing twice). Copyright still an issue (I wonder if they are brave enough to take a NIH mandate approach? See below… not so explicit, but some pressure that way). Where a research output is required for review purposes, institutions will be required to store and reference their Research Output Digital Asset. Repositories a natural home for this.

Accessibility framework requires research outputs to be made sufficiently accessible to allow maximum use of the research. ASHER a short term (2 year?) funding stream to help institutions make their systems and repositories more suitable for working in this new framework.

Andrew Treloar talking about ANDS, the Australian National Data Service, and its implications for repositories. Mentions again the Australian Code for the Responsible Conduct of Research. Institutions need to think about their obligations under this code, obligations that are quite significant! Good story about Hubble telescope: data must be made available at worst 6 months after capture; most of published data from Hubble is not “first use”! (Would this frighten researchers? I put all the work in, but someone else just does the analysis and gets the credit?)

Structure of ANDS: developing frameworks (eg encouraging moves towards discipline-acceptable default sharing practices), providing utilities (building and delivering national technical services to support the data commons, eg discovery, persistent identifiers, and collections registry), seeding the commons, and building capabilities, plus service development activities. ISO 2146 information model important here (I think I’ve already talked about this stuff from the iPres posts [update: no, it was from the e-Science All Hands Meeting, but the links still points to the right place]).

Australian Strategic Roadmap Review talks about national data fabric, based on institutional nodes, and a coordination component to integrate eResearch activities, and see expertise as part of infrastructure. There’s also a review of the National Innovation System: ensure data get into repositories, try to get data more freely available.

Implications for repositories: ANDS dependent on repositories, but doesn’t fund repositories! May need range of repository types for storing data. Big R and little r repositories: real scale issues in data repositories. Lots of opportunities for groups to take part in consultation etc. Different but related discovery service. Links to Research Information Systems. Persistent Identifier Service (in collaboration with Digital Education Revolution). (I worry about this: surely persistence requires local commitment, rather than remote services?)

Panel discussion… question about CAIRS, the Consortium of Australian Institutional Repositories, funding left over from ARROW, being run by CAUL, the Australian University Librarians, which now has an Invitation to Offer to find someone to run the proposed service.

Some questions about data, whether they should be in repositories or in filestore. Scale issues (numbers, size, rapidity of deposit and re-use etc) suggest filestore, but there are then maybe issues about integrity and authenticity. There will be ways of fixing these, but they imply new solutions that we don’t yet have. The data world will soon go beyond the current ePrint/DSpace/Fedora realms.

A few more questions, too hard to summarise, on issues such as the importance of early career scientists, on the nature of raw data etc. But overall, an extremely interesting day!

ARROW Repositories day: 2

Lynda Cheshire speaking as part of “the researcher’s view”, talking about the view from a qualitative researcher working with the Australian Social Science Data Archive (ASSDA), based at ANU, established 1981, with about 3,000 datasets. Most notable studies election studies, opinion polls and social attitudes surveys, mostly from government sources. Not much qualitative data yet, but have grants to expand this, including new nodes, and the qualitative archive (AQuA) to be at UQ. Not just the data but tools as well, based on existing UK and US qualitative equivalents.

Important because much qualitative data is held by researchers on disk, in filing cabinets, lofts, garages, plastic bags! Archiving can support re-use for research, but also for teaching purposes. Underlying issues (she says) are epistemological and philosophical. Eg quantitative about objective measurements, but qualitative about how people construct meaning. Many cases (breadth) vs few cases (depth). Reliability vs authenticity. Detached vs involved.

Recent consultation through focus groups: key findings included epistemological opposition to qualitative archiving (or perhaps re-use), because of loss of context; data are personal and not to be shared (the researcher-subject implied contract); some virtues of archiving were recognised; concerns about ethical/confidentiality challenges; challenges of informed consent (difficult as archiving might make it harder to gather extremely sensitive data, but re-use might avoid having to interview more people about traumatic events); whose data is it (the subject potentially has ownership rights in transcripts, while the researcher’s field notes potentially include personal commentary); access control and condition issues; additional burden of preparing the data for deposit.

The task ahead: develop preservation aspects (focus on near retirees?), and data sharing/analysis under certain conditions. Establish protocols for data access, IPR, ethics etc. Refine ethical guidelines. Assist with project develop to integrate this work.

Ashley Buckle from Monash on a personal account of challenges for data-driven biomedical research. Explosion in amount of data available. Raw (experimental) data must be archived (to reproduce the experiment). Need for standardised data formats for exchange. Need online data analysis tools to go alongside the data repositories. In this field, there’s high throughput data, but also reliable annotation on low volume basis by expert humans. Federated solutions as possible approaches for Petabyte scale data sets.

Structural Biology pipeline metaphor; many complex steps involved in the processes, maybe involving different labs. Interested in refolding phase; complex and rate-limiting. They built their own database (REFOLD), with a simple interface for others to add data. Well-cited, but few deposits from outside (<1%). Spotted that the database was in some ways similar to a lab note-book, so started building tools for experimentalists, and capture the data as a sideline (way to go, Ashley!). Getting the data out of journals is inadequate. So maybe the journal IS the database? Many of the processes are the same.

Second issue: crystallography of proteins. Who holds the data? On the one hand, the lab… but handle it pretty badly (CDs, individuals’ filestore, etc). Maybe the Protein Data Bank? But they want the refined rather than the raw data. Maybe institutional libraries? TARDIS project providing tools for data deposit and discovery, working with ARCHER, ARROW and Monash library... This field does benefit from standards such as MIAME, MIAPE etc, which are quite important in making stuff interoperable. Ashley's working with Simon Coles etc in the UK (who's mostly at the small molecule end).

So how to go forward? Maybe turning these databases into data-oriented journals, with peer review built in etc would be a way to go? Certainly it's a worry to me that the Nucleic Acids field in general lists >1,000 databases; there has to be a better way than turning everything into Yet Another Database...

ARROW Repositories day: 1

I’ve been giving a talk about the Research Repository System ideas at the ARROW repository day in Brisbane, Australia (which is partly why there has been a gap in posting recently). Here are some notes on the other talks.

Kate Blake from ARROW is talking about metadata. Particularly important for data, which cannot speak for itself. Metadata thought of as a compound object that comprises some parts for “library management” issues (things like author, title, keyword) for the whole document and/or its parts, plus University management parts, such as evidence records for research quality management purposes. These link to metadata that applies to the community of practice, eg the appropriate metadata for an X-ray image. Have the content (maybe a PDF), its rich metadata (Kate used MARC/XML as an example, which surprised me, since she also suggested this group was specific to the content), lightweight descriptive metadata, technical metadata (file size, type etc), administrative metadata, eg rights or other kinds of institutional metadata, preservation metadata such as PREMIS, and both internal and external relationship metadata. METS is one way to wrap this complex set of metadata and provide a structural map (there are others). (Worrying that this seems like a very large quantity of metadata for one little object…) Aha, she’s pointing out that aggregating these into repositories and these repositories together across search services leads ot problems of duplication, inconsistency, waste of effort, etc. So lots of work trying to unravel this knot, lots of acronyms: RDF, FRBR, SWAP, DCMI AM, SKOS etc…

FRBR making the distinction between the work, its expressions, manifestations and items. SWAP being a profile for scholarly works, as text works, not much use for data.

Names appear in multiple places in the metadata, and different parts have different rules. Do we have a name agent service (registries)? Need services to gather metadata automatically, that way you might introduce consistency and interoperability.

Kylie Pappalardo from QUT’s OAK Law project on legal issues on managing research data so it can be included in a repository and accessed by others. Government statements in favour of openness (eg Carr: More than one way to innovate, also “Venturous Australia” strategy). To implement these policies we need changes to practice and culture, institutional engagement, legal issues being addressed, etc. Data surrounded by law (!): copyright, contract, patents, policies, confidentiality, privacy, moral rights. Conflicting legal rights: who can do what with the data? QUT has OAK Law and also Legal Framework for e-Research project.

Survey online, May 2007, 176 participants responded. 50 depositing data in database; of those 46% said available openly, 46% required some or complete restrictions. 54% said their organisation did NOT have a data policy at all; where they did have a policy, most were give guidelines. 55% said they prepared plans for data management; two thirds of these at time of proposal, balance later. Should be early, not least because data management costs and should be part of the proposal, also disputes can be hard to resolve later. 7% felt that clearer info on sharing and re-use would help, and 90% wanted a “plain English” guide (who wouldn’t?). Lawyer language doesn’t help, so researchers make their own informal agreements… maybe OK if nothing goes wrong.

The group has a report: analysis of Legal Context of Infrastructure for Data Access and Re-use in Collaborative Research. Also Practical Data Management: a Legal and Policy Guide. They have some tools, including a “simple” Data Management (legal) toolkit to fill in to gather information about (eg) copyright ownership etc.

Peter Sefton of USQ talking about OAI-ORE, and what it can do for us. Making the point that we build things from a wide variety of standard components, which (mostly) work pretty well together, eg found bricks in a garden wall… OAI-PMH mostly works, moving metadata from one place to another. But it’s just the messenger, not the message. So a harvest of metadata across multiple repositories shows wide variations in the keywords, subjects etc. Problems with XACML for defining access policies: no standardisation on the names of subgroups, so in the end it’s no use for search. Point being that these standards may appear important but not work well in practice.

So on to ORE (Object Re-use and Exchange)… Pete asks “shouldn’t it be exchange, then re-use?”. ORE view of a blog post: a resource map describes the post, but in fact it’s an aggregation (compound object) of HTML text, a couple of images, comments in separate HTML, etc. The aggregation does have a URI, but does not have a fetchable reality (the resource map does). Can get complex very rapidly. See Repository Challenge at OpenRepositories 2008 in Southampton, and the ORE Challenge at RepoCamp 2008. USQ participating with Cambridge in JISC-funded TheOREM project, also internal image project called The Fascinator. Based on his ICE system that has been mentioned before, integrated with ORE tools to push stuff into the repository. Can have the repository watching so it can get it for itself.

ORE can: supplement OAI-PMH for moving content around; improve research tols like Zotero; replace use of METS packages; allow “thesis by publication” more elegantly; and pave the way for a repository architecture that understands content models (no more discussion of atomistic versus compound objects).

Data as major component of national research collaboration

This is perhaps the last of my posts resulting from conversations and presentations at the UK e-Science All Hands meeting in Edinburgh. This one relates to Andrew Treloar’s presentation on the Australian National Data Service (ANDS), and its over-arching programme, Platforms for Collaboration, part of the National Collaborative Research Infrastructure Strategy.

There are strong historical reasons why collaboration over a distance is very important for Universities and researchers in Australia. Now the Government seems to have really got the message, with this major investment programme. Andrew described how a basis of improving the basic infrastructure (network and access management) supports 3 programmes, high performance computing, collaboration services, and the Data Commons. The first two of these are equally important, but in from my vantage, I’m particularly interested in the Data Commons.

The latter is provided (or perhaps supported; it’s highly distributed) by ANDS. The first business plan for ANDS is available at http://ands.org.au/andsinterimbusinessplan-final.pdf and will run until July 2009, with ANDS itself expected to run to 2011. The vision for ANDS is in the document “Towards the Australian Data Commons”.

The vision document :

"...identifies a number of longer term objectives for data management:

• A. A national data management environment exists in which Australia’s research data reside in a cohesive network of research repositories within an Australian ‘data commons’.
• B. Australian researchers and research data managers are ‘best of breed’ in creating, managing, and sharing research data under well formed and maintained data management policies.
• C. Significantly more Australian research data is routinely deposited into stable, accessible and sustainable data management and preservation environments.
• D. Significantly more people have relevant expertise in data management across research communities and research managing institutions.
• E. Researchers can find and access any relevant data in the Australian ‘data commons’.
• F. Australian researchers are able to discover, exchange, reuse and combine data from other researchers and other domains within their own research in new ways.
• G. Australia is able to share data easily and seamlessly to support international and nationally distributed multidisciplinary research teams. (p. 6) "

Andrew writes:

“ANDS has been structured as four inter-related and co-ordinated service delivery programs:

• Developing Frameworks [Monash]
• Providing Utilities [ANU]
• Seeding the Commons [Monash]
• Building Capabilities” [ANU]

Andrew also mentioned the Science and Research Strategic Roadmap Review, published just this August, which seems to centre on NCRIS. This includes the notion of a” national data fabric”, based on institutional nodes.

ARCHER, mentioned earlier, provides candidate technology for an institution participating in ANDS. As Andrew pointed out in a comment responding to my confusion in the last post: “the CCLRC [metadata] schema is the internal schema being use by ARCHER to manage all of the metadata associated with the experimental data. ISO2146 is the schema being used by ANDS to develop its discovery service”. No doubt there are many ways institutional nodes can and will be stitched together, and it will be interesting to see how this develops.

Australians sometimes bemoan the lack of an Australian equivalent of JISC. However, in this case they appear to have put together something with significant coherence in multiple dimensions. On the face of it, this is more significant than any European or US programme I have seen so far. A lot depends on the execution, but with good luck and a following wind (and a fairly strong dose of “suspension of disbelief” from researchers), this could well turn out to be a world-beating data infrastructure programme.

For comparison, I’ll try to take a look at the emerging UK Research Data Service proposals, shortly. Perhaps that has the opportunity to be even better?

ARCHER: a component of Australian e-Research infrastructure?

At the e-Science All Hands meeting, David Groenewegen from Monash spoke (PPT, also from Nick Nicholas and Anthony Beitz) about the outputs of the ARCHER project, almost finished, intended to provide tools for e-Research infrastructure. They see these e-Research challenges:

• "Acquiring data from instruments
• Storing and managing large quantities of data
• Processing large quantities of data
• Sharing research resources and work spaces between institutions
• Publishing large datasets and related research artifacts
• Searching and discovering"

The tools they have nearly completed (the project finishes this month) include:

• "ARCHER Research Repository - for storing large datasets, based on SRB
• Distributed Integrated Multi-Sensor & Instrument Middleware – concurrent data capture and analysis
• Scientific Dataset Manager (Web) - for managing datasets
• Metadata Editing Tool
• Scientific Dataset Manager (Desktop) – for managing datasets
• Analysis Workflow Automation Tool - streamlining analysis
• Collaborative Workspace Development Tool - bringing researchers together"

The research repository is based around a simplified version of what they call "CCLRC Scientific metadata", which they said was the only appropriate set of metadata they could find at the time. Here's a simpified diagram:


This does look to me like the metadata for a Current Research Information System (CRIS); I've spoken of these before. Maybe the CERIF metadata might do a similar job? Later we heard that the ANDS programme was to use yet another metadata set or standard (ISO2146); OK guys, I got a bit confused at this point!

Clearly this is a generic system; they also have some customisations coming for crystallographers, including the wonderfully-named TARDIS (The Australian Repositories for Diffraction Images). It's not yet clear to me how domain science curation and domain-specific metadat fit into this model, but I hope to find out more next month.

So where next for ARCHER? David wrote:

• "Currently testing the tools for release by late September
• Some tools already out in the wild and in use
• Expecting that the partners will continue to develop the tools they created
• New enhanced versions already being worked on
• Looking at how these tools might be used within ANDS (Australian National Data Service) & ARCS (Australian Research Collaborative Service) and beyond!"

This does look like good stuff!

(I think ARCHER is a collaboration of ANU, James Cook, Monash and Queensland Universities.)

How to make repositories a killer app for scientists

Cameron Neylon wrote a nice post indirectly addressing the question of how Nature might make Connotea more useful. It's well worth reading for its own merits, but I was so taken by his questions, I thought they might be re-purposed to apply to repositories. As Cameron says "These are framed around the idea of reference management but the principles I think are sufficiently general to apply to most web services". The text below is Cameron's, except with chunks taken out (shown by ellipses ...) and some of my text added [in brackets] (added text may replace some of Cameron's text).

1. "Any tool must fit within my existing workflows. Once adopted I may be persuaded to modify or improve my workflow but to be adopted it has to fit to start with. ...
2. Any new tool must clearly outperform all the existing tools that it will replace in the relevant workflows without the requirement for network or social effects. Its got to be absolutely clear on first use that I am going to want to use this instead of ...[some other tool, like a lab web site]. ... And this has to be absolutely clear the first time I use the system, before I have created any local social network and before you have a large enough user base for these to be effective.
3. It must be near 100% reliable with near 100% uptime. ... Addendum - make sure people can easily ... download their stuff in a form that will be useful even if your service disappears. Obviously they’ll never need to but it will make them feel better (and don’t scrimp on this because they will check if it works).
4. Provide at least one (but not too many) really exciting new feature that makes people’s life better. This is related to #2 but is taking it a step further. Beyond just doing what I already do better I need a quick fix of something new and exciting. ...
5. Prepopulate. Build in publically available information before the users arrive. ..."

I think what Cameron's saying is what we all should know by now of the needs of potential repository depositors: make it easier, make it better, make it worth my while.

It's the "how" that's tricky. I don't think this is impossible, but these targets are hard to hit. It's what all the "negative click" Research Repository System attempts have all been about. They do need a re-think, however, if not to fall foul of Cameron's rule #1! So what other ideas are there out there, folks?

Adding value to data: eScience conference session

If you nearly had a paper ready for the International Digital Curation Conference in December (the closing date was the end of July), you may still have time to get one in to the special session "Adding value to data – Digital Repositories in the e-Science world" at the 4th IEEE International Conference on eScience, whose deadline has just been extended to 31 August. From the call for papers on the DReSNet blog:

"There is a great, untapped potential for synergies between grid/e-science technologies and a cluster of related systems addressing the management of digital assets in digital libraries and repositories. The digital material generated from and used by academic and other research is to an increasing extent being held in formal data management systems; these systems are variously categorized as digital repositories, libraries or archives, although the distinction between them relates more to the sort of data that they contain and the use to which the data is put, rather than to any major difference in functionality. In many cases, these systems are used currently to hold relatively simple objects, for example an institution’s pre-prints and publications, or e-theses. However, some institutions are beginning to use them to manage research data in a variety of disciplines, including physical sciences, social sciences, and the arts and humanities, as well as the output from various digitisation programmes."

This does look very interesting. They suggest several research challenges, which I think tie in pretty much with our own agenda, although the last is novel to me in the way it's framed:

• Digital preservation and curation in research infrastructures
• Interoperability
• Security
• Provenance
• Metadata Extraction
• Workflow Integration
• Architecture of Participation

There's a good programme committee, so the session could be extremely useful. Go to their entry for the submission details...

Repositories and the CRIS

As I mentioned in the previous post, there has been some discussion in the JISC Repositories task force about the relationship between repositories and Current Research Information Systems (CRIS). Stuart Lewis asserted, for example, that “Examples of well-populated repositories such as TCD (Dublin) and Imperial College are backed by CRISs.” So it seems worth while to look at the CRIS with repositories in mind.

There has been quite a bit of European funding of the CRIS concept; not surprising perhaps, as research funders would be significant beneficiaries of the standardisation of information that could result. An organisation (EuroCRIS) has been created, and has generated several versions of a data model and interchange standard (which it describes as the EC-recommended standard CERIF: Common European Research Information Format), of which the current public version is known as CERIF 2006 V1.1. CERIF 2008 is under development, and a model summary is accessible; no doubt many details are different, but it does not appear to have radically changed, so perhaps CERIF is stabilising. Parts of the model are openly available at the EuroCRIS web site, but other parts require membership of EuroCRIS before they are made available. This blog post is only based on part of the publicly accessible information.

I decided to have a look at the CERIF 2006 V1.1 Full Data Model (EuroCRIS, 2007) document, with a general aim of seeing how helpful it might be for repositories. Note this is not in any sense a cross-walk between the CERIF standards and those applicable to repository metadata.

Quoting from a summary description of the model:

“The core CERIF entities are Person, OrganisationUnit, ResultPublication and Project. Figure 1 shows the core entities and their recursive and linking relationhips in abstract view. Each core entity recursively links to itself and moreover has relationships with other core entities. The core CERIF entities represent scientific actors and their main research activities.
Figure 1: CERIF Core Entities in Abstract View”

The loops on each entity in the diagram above represent the recursive relationships, so a publication – publication relationship might represent a citation, or one of a series, or a revision, etc. Entity identifiers all start cf, which might help make the following extract more understandable:

“The core CERIF entities represent scientific actors (Persons and Organisations) and their main research activities (Projects and Publications): Scientists collaborate (cfPers_Pers), are involved in projects (cfProj_Pers), are affiliated with organisations (cfOrgUnit_Pers) and publish papers (cfPers_ResPubl). Projects involve people (cfProj_Pers) and organisations (cfProj_OrgUnit). Scientific publications are published by organisations (cfOrgUnit_ResPubl) and refer to projects (cfProj_ResPubl), publications involve people (cfPers_ResPubl), organisations store publications (cfResPubl), support or participate in projects (cfProj_OrgUnit), and employ people (cfPers_OrgUnit). To manage type and role definitions, references to classification schemes (cfClassId; cfClassSchemeId) are employed that will be explained separately…”

The model adds other “second-level” entities:
Figure 5: CERIF 2nd Level Entities in Abstract View

As Ian Stuart wrote in the repositories discussion:

“The current repository architecture we have is a full deposit for each item (though some Repositories jump round this with some clever footwork) - which runs straight into the "keystroke" problem various people have identified.

With a CRIS-like architecture, the user enters small amounts of [meta-]data, relevant to the particular thing - be it a research grant; a presentation at a conference; a work-in-progress; a finished article; whatever.... and links them together. It is these links that then allows fuller metadata records to be assembled.”

It should be clear that having this much information available should make populating a repository relatively trivial task. It's not entirely clear how easily the metadata will transfer, although it does appear that Dublin Core metadata has been used in the model, but whether this is mandatory or optional is not clear from this document. I suppose it’s also not clear how much the CERIF standard is used in actual implementations.

I’ll leave the penultimate word to Stuart Lewis, who wrote

“[The CRIS] doesn't replace the repository, but offers a management tool for research. Inputs to the CRIS can include grant record systems, student record systems, MIS systems etc, and outputs can include publication lists and repositories… Now we just need an open source CRIS platform... E.g.:

http://www.symplectic.co.uk/products/publications.html
http://www.atira.dk/en/pure/
http://www.unicris.com/lenya/uniCRIS/live/rims.html”

Note, I have not checked out any of the above products in any detail, although the 3rd one appears to be a non-responsive web-site; use at your own risk! And it should be obvious that anything that links into MIS systems in any institution is likely to require a major implementation effort. It may also suffer from institutional silo effects (links to my institutions management information, but not my collaborators’ information).

Reference:

EuroCRIS. (2007). CERIF2006-1.1 Full Data Model (FDM) Model Introduction and Specification (Recommended standard). http://www.dfki.de/%7Ebrigitte/CERIF/CERIF2006_1.1FDM/CERIF2006_FDM_1.1.pdf

Comments on Negative Click Research Repository System

You may remember that I wrote a series of posts about a Research Repository System, aiming to improve deposits by getting repositories to do more that’s useful to the researcher. I had suggested it should contain these elements:

• web orientation
• researcher identity management
• authoring support
• object disclosure control
• data management support
• persistent storage
• full preservation archive, and
• spinoffs

There has been some interesting commentary on this idea. Some of it was in the comments to this blog, but most came through the JISC Repository and Preservation Advisory Group’s use of Ideascale to discuss issues related to a possible revision of the Repositories Roadmap. I decided to post some of the ideas from the RRS posts to the Ideascale forum, and they attracted comments, both positive and negative, and votes, and I will try to summarise key points here. Note, I have only picked out posts and comments that I consider relevant to this approach; there were many other interesting ideas and comments that you might want to read if you care about repositories.

BTW if you haven’t tried it, I was very impressed by the combination of technologies that Ideascale have put together, and the simplicity and value of its approach, akin to brainstorming but slower! Worth giving a whirl…

Overall, the thrust of the whole conversation seemed to support my feeling that repositories must serve their depositors rather than down-stream users (the institution, the department, colleagues, the public). This links strongly to the theme behind the RRS set of ideas.

The most popular “idea” on the JISC Ideascale site was Andy McGregor’s, not mine, but was related to this theme: “Define repository as part of the user’s (author /researcher/ learner) workflow” (21 voted for, 2 against, net 19). While there was general support, there was some concern as well: ojd20 wrote “I agree with this idea in the sense of ‘take account of things users need to do’, but not in the sense that we can reduce the myriad functions of an HE institution to a small set of flow charts and design repositories to fit those… ‘Familiar processes and tools’ is a much better way of expressing it [than workflow]” The other warning, from Owen Stephens, was “I'm also wary of comments elsewhere from the likes of Peter Murray-Rust on this. He warns (my interpretation) that we need to be careful of doing this as if it complicates the workflow, it just won't happen”. A. Dunning echoed a common theme in saying “Disagree - the repository is a back end data provider that should not be part of the researchers' / learners' workflow - but the service which sits on top of the repository should be part of the workflow.”

Rachel Heery showed another common concern, about possible over-complexity:

“I think the RRS you envisage sounds fantastic and would be a 'good thing', what worries me is the 'function creep' taking us a few miles on from some of the more basic, simpler 'few keystrokes' approach to repositories. The RRS sounds to have many features of a Virtual Research Environment, albeit perhaps a less data centric VRE…”

This echoed a comment from Bill Roberts on one of the original blog posts:

“Seriously, though - the system you've sketched out is quite complicated, not so much in the individual parts of it, (though several of those parts are quite substantial) but in the design vision required to connect up all those features in a way that would be easy and natural to use. Can you identify a subset of parts that would make a useful version 1?”

And Steve Hitchcock also commented on complexity to the same post:

“The irony of the negative click philosophy is that it has led you to produce a visionary but significantly more complex system.”

The surprising (to me) winner among the RRS ideas was “Allow the user fine-grained disclosure/access control to repository objects”. This gained 12 positive and 2 negative votes, for a net 10 votes, and no negative comments. I don’t have a good explanation for why this was so popular, noting that the voters were mainly repository managers or “experts”, especially since some of the corollary ideas were much less popular.

Another idea posted by Rachel Heery, not from RRS but worth taking note of (and getting 11 votes, none against) was “We shouldn't be thinking of repositories as a place.” In particular this meant “'repositories' are best viewed as a 'type' of data store supporting a variety of services, embedded in various workflows.”

I’ll include the Researcher Identity Management idea next, not for its own votes (4 in favour, 2 against), nor for the comments (of which there were none), but because of the linkages I had made between researcher identity and Current Research Information Systems (CRIS). The idea associated with CRIS was from Ian Stuart, and got 13 positive and 4 negative votes: “Repositories are dead, long live repositories” (yes, ideas are not always best titled!). He wrote

“The current repository technology is library/cataloger centric: items are uploaded (usually by a cataloger, not the author), and most of the meta-data is added by a subject specialist. In this model, the author-as-depositor is (at best) just an initiator for a deposit process.

A better solution would be to move towards a Combined [sic] Research Information System [CRIS], where the academic can organise their areas of interest [AOI]; see the research grants they have (and associate them with their AOI); lodge keep-safe copies of work-in-progress, data-sets, talks, ideas for future work, posters, etc (and associate them with grants or AOIs).

From this corpus of data, the academic can indicate what is visible locally (within the research group/department/organisation) and what is available globally... and from that "globally available" pool, an "Institutional Repository" can be assembled.”

The idea that the repository should be more web-oriented got 6 votes. There were no negative comments on the idea itself, but I drew a comparison (echoing Andy Powell) with Slideshare, and Paul Walk reacted against this: “More like the Web - yes! Like Slideshare - no!” He expands on this comment later (see below).

The idea that the repository should be more Web 2.0-like drew 6 positive but 5 negative votes, net 1 vote, possibly the most divided idea of all! I guess it’s one I was much less sure of, but included it because of comments to my earlier posts on this theme. A. Dunning wrote: “It's not so much the repository itself that needs Web2.0 but the range of the services which exploit that data.” And Paul Walk wrote:

“The repository should be able to participate in an interactive Web. It should be entirely possible for someone else to build a remote Web 2.0 service around resource exposed in my repository. This does not preclude me building such a service - if I think I have sufficient mass of interested users etc. but if I *need* to do this because only I can, then I have probably just built another silo.

This is what I meant by my assertion that, in general, Technorati offers us a better model than Slideshare. Someone can build a better, more focussed, domain specific etc. version of Technorati if there is demand for this, without needing to move or copy the resources in their 'source repositories' (blogs, in this case).”

[Paul, I have to say I’m unconvinced so far. A repository has to have the stuff, so that makes it more like Slideshare. And for various reasons, Technorati sucks (searches don’t work properly, lots of things fall off or go wrong). If you’d said Google instead, I might have got it. But searching by reference rather than by inclusion seems like going back to Z39.50 rather than search engine harvesting approaches (or even OAI-PMH). But maybe I’m resolutely getting the wrong end of this stick!]

Richard Davis wanted a foot in both camps:

“IMO, ideally a repo would be susceptible to all sorts of Flickrish RSS, Web API type manipulation - SWORD-like and who knows what else - leading to total personalisation potential of the user experience.

OTOH, providing implementers and users with an acceptable out-of-the-box UI, that might include basic implementations of some voguish features, and widgety ways to configure them - cf. Flickr or Wordpress - is no bad thing either.”

The idea of providing persistent storage got 6 positive and 2 negative votes, net 4 votes. Paul Walk was generally happy:

“I agree that persistence, more or less as you define it here, should be a core property of what I think of as a 'source repository'. In terms of ease of use: read, or 'get' access should be simple and should be provided through HTTP unless there is a very good reason not to. We should aspire to ease of use in terms of ingest and administrative activities.

In terms of synchronisation with offline storage (unless I have misunderstood your point): this is an interesting area, but I'm not sure it is a fundamental or universal function of 'the repository'. I think we are going to see a strange race between the development of mechanisms to do this (e.g. GoogleGears) and the progress in us all becoming so ubiquitously and permanently connected that we don't need this any more…”

The idea of data management support attracted 4 votes, none negative, and no comments. I’m not sure how to interpret this… but it was not the core interest of the group, I guess. I continue to think it an important missing service that falls into repository-space.

I split authoring support into two ideas: publishing and authoring. Of these, “The repository/library should provide support in the publishing process” got 6 votes, none negative. There were some concerns, eg Owen Stephens again “This needs restating
from a user perspective.” He thought there was value in “a system to help streamline the editorial/publication process is fine (if we can persuade academics to use it), but I'm not sure I'd start by building it on the repository - maybe you could, but there are other approaches as well.” In particular, he thought “I see the point about the benefits, but if we are solving problems our end users don't feel need solving then we have a much more difficult job on our hands (and perhaps not substantially different from our current problems with getting researchers to put things into our repository.”

More direct support for authoring was more divisive (5 votes for and 3 against, net 2 votes). In support, Owen Stephens wrote “The availability of research via Open Access would increase if the same systems that provide Open Access also provided, or were integrated with, tools which support the authoring process.” There was a bit of so-what from Ian Stuart: “This is a variation of what Peter Murry-Rust proposed back in '07: google-docs mixed with a CRIS.” [Yes, Ian, explicitly this idea came from some posts by PMR.] And one outright warning from forkel: “my experience is, that feature requests of this sort are exactly the ones which end up in the "users didn't know what they wanted bin" (I'm a developer).”

Finally (almost) I posted the idea that “The repository should be a full OAIS preservation system”. This turned out to be extremely unpopular, with only 2 votes for and 6 against, net -4! I was very disappointed (repositories are surely not for transient stuff that might be here today, gone tomorrow), so re-phrased it as “Repository should aspire to make contents accessible and usable over the medium term”, when again it attracted 2 votes for and this time none against. This was very late in the day, so maybe few people were coming back to vote on new ideas by then. It was clear that part of the problem was the term OAIS; my mistake for assuming in that context that people would have understood the term.

So where does this leave the Research Repository System idea? Not fully intact, I fear, but not shredded, either. Reduce complexity, think services operating on a store, take care to ensure these are services people really want, etc… It’s going to take me a while to work this through, but I will get back to you!