Posted by Rory on January 5th, 2011 @ 10:33 am

Back in 2007 – 2008 a spate of social networking sites for scientists were established. In late 2008 David Bradley found about 20, which he discussed in his post on Social Media for Scientists.    Here is David’s list (with his comments):

• Nature Network – uber network from the publishing giant
• BioMedExperts – Scientific social networking
• BioWizard – Blogged up Pubmed search
• Mendeley – Digital paper repository and sharing
• Labmeeting (blog) – Ditto
• YourLabData – socialised LIMS
• SciLink – Sci-Linkedin
• Myexperiment.com – mostly workflows.
• Laboratree.org similar to Researchgate. Not particularly social beyond groups and sharing documents with collaborators, but email is better, and arguably more secure.
• scitizen.com – collaborative science news publishing
• SocialMD – Med-Linkedin
• Ozmosis – Ditto
• DNA Network – network of DNA/genetics bloggers
• ResearchCrossroads – Socialised grant databases
• MyNetResearch – Socialised LIMS at a price
• SciVee – YouTube for scientists (see also Watch with Sciencebase page
• Scientist Solutions – science chat
• Twitter science group and Scientwists list

Although other social networking sites oriented to scientists have appeared in the past two years, e.g. Bitsesize Bio, it’s interesting to note that the initial rush has petered out, and to speculate about why this is so.

Lack of demand?

Is the dearth of new social networking applications for scientists due to lack of demand?  Probably not.  A number of the ones on the list, including Mendeley, Academia.edu and ResearchGATE (which is not on the list), have each attracted hundreds of thousands of people to sign up, and Mendeley and ResearchGATE have both attracted substantial investments from venture capitalists, demonstrating external belief in the existence of a large market.

Need for time to consolidate?

A more likely reason for the lack of new entries into the market is that users of the social networks  need time get used to the relatively new forums for communication the networks offer, and are focussing on one or possibly two existing networks as the networks gradually improve their offering and add new features.

Limited needs?

Another possible explanation for the lack of new offerings is that scientists’ needs for collaboration and communication are limited to what the current social networks offer:   sharing publications, finding out what others in their field are doing, and seeking answers to research questions. If that’s true then there is limited scope for additional innovation, in which case the market may already have consolidated around the existing providers.

Is there scope for additional innovation? Yes!

A quick glance at Cameron Neylon’s late 2009 post, What should social software for science look like?, however, would seem to indicate that there is still plenty of scope for innovation!  Cameron lists ten things that social software for scientists should be able to do:

1. SS4S will promote engagement with online scientific objects and through this encourage and provide paths to those with enthusiasm but insufficient expertise to gain sufficient expertise to contribute effectively (see e.g. Galaxy Zoo). This includes but is certainly not limited to collaborations between professional scientists. These are merely a special case of the general.
2. SS4S will measure and reward positive contributions, including constructive criticism and disagreement (Stack overflow vs YouTube comments). Ideally such measures will value quality of contribution rather than opinion, allowing disagreement to be both supported when required and resolved when appropriate.
3. SS4S will provide single click through access to available online scientific objects and make it easy to bring references to those objects into the user’s personal space or stream (see e.g. Friendfeed “Like” button)
4. SS4S should provide zero effort upload paths to make scientific objects available online while simultaneously assuring users that this upload and the objects are always under their control. This will mean in many cases that what is being pushed to the SS4S system is a reference not the object itself, but will sometimes be the object to provide ease of use. The distinction will ideally be invisible to the user in practice barring some initial setup (see e.g. use of Posterous as a marshalling yard).
5. SS4S will make it easy for users to connect with other users and build networks based on a shared interest in specific research objects (Friendfeed again).
6. SS4S will help the user exploit that network to collaboratively filter objects of interest to them and of importance to their work. These objects might be results, datasets, ideas, or people.
7. SS4S will integrate with the user’s existing tools and workflow and enable them to gradually adopt more effective or efficient tools without requiring any severe breaks (see Mendeley/Citeulike/Zotero/Papers and DropBox)
8. SS4S will work reliably and stably with high performance and low latency.
9. SS4S will come to where the researcher is working both with respect to new software and also unusual locations and situations requiring mobile, location sensitive, and overlay technologies (Layar, Greasemonkey, voice/gesture recognition – the latter largely prompted by a conversation I had with Peter Murray-Rust some months ago).
10. SS4S will be trusted and reliable with a strong community belief in its long term stability. No single organization holds or probably even can hold this trust so solutions will almost certainly need to be federated, open source, and supported by an active development community.

By my reckoning the existing providers have made a good start on 1,2,5,6, and 8, but not 1, 3, 4, 7 and 9.  1, 3, 4, 7 and 9 all involve integration with data which is not internally generated from the social network but which scientists access or generate independent of the application.  Thus far there is not much evidence that the existing social networks are taking steps to rectify this limitation, which is understandable because (a) they have limited resources, (b) there is always immediate  pressure from users to improve existing features and add new features, and (c) it’s usually more difficult to integrate with external sources of data and/or applications than to extend the capability of your own application.

But the fact remains that, taking Cameron’s list as a benchmark, social networks for scientists are far from a finished product.  Cameron’s list, moreover, is in my view not exhaustive.   A true social network for scientists should give them the capability to share their research data.  I have argued previously that this would require:

1. An individual, user-centric focus
2. The ability for individual users to control with whom they share data, and when
3. The ability to create records with structure so that experimental data can be recorded
4. The ability to create links between records
5. An audit trail of changes made to records
6. A messaging capability

The existing social networks have 1 (a user centric focus) and some have 6 (a messaging capability), but none have 2 – 5, i.e. support for managing research data.

Where will the innovation come from?

So there is lots of scope for additional innovation.  In next week’s post I’m going to discuss where the innovation is likely to come from — existing social networks for scientists, general social media sites like Twitter and Quora, and/or new applications.

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Posted by Rory on December 16th, 2010 @ 5:13 pm

Social networking sites and science

Sir Tim Berners-Lee recently argued, in Long Live the Web:  A Call for Continued Open Standards and Neutrality, that social-networking sites pose a two-fold danger to the web. First,

“Social networking sites assemble. . . bits of data into brilliant databases and reuse the information to provide value-added service—but only within their sites. Once you enter your data into one of these services, you cannot easily use them on another site. Each site is a silo, walled off from the others. Yes, your site’s pages are on the Web, but your data are not.”

A second danger “is that one social-networking site . . . gets so big that it becomes a monopoly, which tends to limit innovation.”

In the last post I took issue with Sir Tim and argued that, on balance, social networking sites add rather than subtract to the flow of information, and stimulate rather than suppress innovation.   In this post I’ll look at the impacts social networking sites are having on science.  I’ll look focus on two large generic social networking sites, Facebook and Twitter.  In a future post I’ll look at social networking sites aimed specifically at scientists.

Facebook

Scientists, like everyone else, use Facebook, but generally they don’t use it in relation to their research.  Rather, like most people, scientists use Facebook to keep in touch with family and friends.   As I have argued previously, the serious problems with privacy — or rather lack thereof — in Facebook put scientists off from using it for research.  An even more fundamental problem is the lack of support in Facebook for adding structure to data, which makes it unsuitable for recording experimental data.

Twitter

In contrast to Facebook, Twitter is used extensively by scientists to discuss issues related to scientific issues.   Importantly, this discussion usually does not reach down to the level of active research projects that individuals or labs are carrying out. Rather discussion centers around things like research techniques and trends, approaches, technology, publications and publishing, and the research process. Twitter is not viewed as a good place for discussing active research because of concerns about confidentiality held by the majority of scientists, who are not open science advocates, and limitations on the nature of the content that can be included, which are of course far more severe than even in the case of Facebook.

Science and social networking sites

So that’s how scientists are using, and not using, Facebook and Twitter in relation to their research.  Facebook is largely irrelevant as an environment or space for conducting scientific research and scientific discussion.  I would argue, however, that Facebook is indirectly playing an important role, (a) by shaping the way  younger scientists think about how to communicate, which in turn will impact on the way they carry out science as new collaboration and communication tools become available, and (b) in stimulating scientists to think about what these tools might look like, as Cameron Neylon did in an interesting post called, What should social software for science look like?.

Twitter is already an important  environment for conversations about science, so it is more than just a model or a stimulator of new ideas.  Twitter is already making a positive contribution to science in that (a) it facilitates conversations between people who probably would not have been in contact or found each other were it not for Twitter, (b) the conversations it stimulates probably would not have taken place without the Twitter platform, and (c) the conversations are useful adjuncts to other forms of scientific communication, e.g. those which take place in academic journals and blogs.  Like Facebook, Twitter is also a model and a stimulator of new ideas about ways of communicating that will over time  find their way into specialized resources developed specifically  for scientists.  An example is the powerful stimulus that Twitter provides to the spontaneous formation and rapid development of micro communities of interest.  This has led to the growth of these communities around specific areas of scientific interest on Twitter, and there is no reason to suppose the same thing will not happen on social networking tools developed specifically for scientists.

Overall:  thumbs up for social networking sites

So the story so far is pretty positive.  Twitter is already making a significant contribution to communication between scientists, and Facebook is stimulating lots of thought about how its  new communication model can be adapted and tailored to science.

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Posted by Rory on October 27th, 2010 @ 9:49 am

In the last post I looked at a study which concludes that researchers in the life sciences are willing to share their data, but only on their own terms:  they want to decide which data to share, with whom, and when. My starting point was a recent article by Bryn Nelson lamenting the fact that data sharing is the exception rather than the rule among scientists.  In the article he gives a number of examples — some successful and some not — where top down data storage/sharing repositories have been established for particular disciplines and particular kinds of data.

Are these kinds of repositories a model for what might encourage widespread data sharing by scientists in bottom up research fields  like life sciences?  I think not, because these top down, centralized repositories generally remove control from the individual or group who is contributing the data.  They are really focused on data storage rather than data sharing. In most cases, moreover, once the data has been contributed it is open for all to see — that is the point of the exercise.  So it’s not surprising that when databases like these are offered to the researchers in the bottom up fields, they usually opt not to contribute their data.  There are few incentives to make contributing their data  an attractive proposition, and it’s yet another administrative burden.

An environment (or system, application, call it what you will) that would stand a better chance of attracting large numbers of scientists is one that does what they want — i.e. lets them  share that part of their research  data they want shared, with whom, and when.  The only kind of environment that will maks that possible is one that puts individual scientists, and groups of scientists, at the center, and in control. That is a bottom up application, not a top down, centralized application like the ones noted by Bryn Nelson.

Google Docs

Is there a model for the kind of application that might work?   How about Google Docs, which is already used by many scientists to share documents, spreadsheets and presentations? Google Docs allows users to share information in a way they control. However, it  lacks a number of necessary capabilities  to enable scientists share their research data when and with whom they want.  These include:

1. The ability to create records with structure — i.e. the kind of structure scientists are used to putting into their paper labbooks to record experimental data
2. The ability to link between records
3. An audit trail of changes made to records
4. A messaging capability

Facebook

What about Facebook?  Like Google Docs, Facebook permits sharing of information in ways the user controls.  Facebook, moreover, has the ‘social’ features that Google Docs lacks, particular the ability to communicate with other users.  But Facebook has its own set of shortcomings as a potential tool for sharing scientific research data. First, it is viewed as a tool for communicating with friends and family about social rather than work matters.  Second, there are serious problems with the privacy — or rather lack thereof — of data people put in Facebook, which might be acceptable for personal data but is not for scientific research data.  The most fundamental problem, however, is that Facebook, like Google Docs, does not provide support for recording and sharing experimental data because it does not provide the ability to create records with structure.

Essential elements of a data sharing application for scientific research

If neither Google Docs nor Facebook looks like a suitable candidate for a general data sharing application/environment for scientists in bottom up disciplines like biology, chemistry, medicine and materials, the above discussion does provide an idea of the capabilities such an application/environment would need to have:

1. An individual, user-centric focus
2. The ability for individual users to control with whom they share data, and when
3. The ability to create records with structure so that experimental data can be recorded
4. The ability to create links between records
5. An audit trail of changes made to records
6. A messaging capability

If and when an application with these elements becomes available, it would stand a good chance of being taken up by large numbers of scientists in bottom up disciplines like biology, chemistry, medicine and materials.  And that would bring benefits not only to the individual scientists themselves and those with whom they are directly collaborating, it also would lead to a far greater percentage data that is generated being, first, captured electronically, and, second, shared.

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Posted by Rory on October 20th, 2010 @ 6:21 pm

In a recent article, Data Sharing:  Empty Archives, Bryn Nelson points out that although

“Some [scientific] communities have been quite open to sharing [data] . . . those discipline-specific successes are the exception rather than the rule in science. All too many observations lie isolated and forgotten on personal hard drives and CDs, trapped by technical, legal and cultural barriers.”

The communities where most data is not widely shared include disciplines like biology, chemistry, medicine and materials where the bulk of experimental data is generated by individual researchers and labs.  In this post I’d like to take a closer look at data sharing practices and attitudes in these ‘bottom up’ research disciplines.  Let me disclose my bias at the outset — this is that data sharing practices in these disciplines should be determined by the members of the community, not by funding bodies or other policy makers.  If data sharing is to become more widespread, it should be because the members of the community want that to happen, and it should happen in ways that they determine.

The starting point has to be existing attitudes to data sharing in the communities. A recent study of seven labs doing various forms of biology: Patterns of information use and exchange:  case studies of researchers in the life sciences came up with some interesting observations about those attitudes.  What the study found was that life sciences researchers

“are in principle in favour of sharing many kinds of information, and are remarkably willing to do so in order to facilitate each other’s research, without any apparent formal reward.  Thus information is extensively shared within research groups and laboratories, and informally across organisational boundaries through wider research networks, both before and after formal publication.  This may include sharing . . . standard operating procedures, plasmids, computer programmes, scripts and statistical analysis tools.”

So researchers are willing to share  information, but on their own terms.  Essentially they are willing to share information with people they are collaborating with, inside and outside the lab.  In other words, researchers are willing to share information with whom they the researchers want.

The study went on to report that

“Researchers are much more ready to share methods and tools than experimental data . . .  They are reluctant to share the data that makes up their ‘intellectual capital’.  In particular, they are wary of giving away their data for someone else to analyse and get the credit.  ”

Researchers are willing to share experimental data, but only subject to two provisos

• “First they are concerned that they need sufficient time to complete the analysis and, in some cases, to explore intellectual property rights . . .
• Second they want to publish their results before or simultaneously to publishing their data — and they want to be the ones to publish the data.”

So researchers are also willing to share experimental data, but again only on their own terms.  And those terms are that researchers want to decide what data gets shared and when it gets shared.

Seven labs is hardly a representative sample of the hundreds of thousands if not millions of labs in ‘bottom up’ research disciplines like biology, chemistry, medicine and materials.  And yet the attitudes noted by the study have a strong feeling of familiarity about them, and it’s not implausible to assume that they are  broadly representative of  attitudes that are widespread throughout these disciplines.  The message from the scientists interviewed  in the study is loud and clear:  they are willing to share their data only when they can decide which data to share, whom to share it with, and when.

In the next post I’m going to discuss why many existing ‘top down’ data sharing initiatives have failed to take off because of lack of interest and support from the communities, and speculate about what kind of application, tool, or environment would be needed to enable scientists in bottom up research disciplines like biology, chemistry, medicine and materials to share their data in the controlled fashion they seem to prefer.

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Posted by Rory on August 18th, 2010 @ 10:22 am

The web has gone social, with Facebook and Twitter leading the way.  And applications that were not designed with social networking as a core element are scrambling to add social features.  Often, however, that’s not as straightforward as it seems and can have unintended consequences, of which  Google Buzz is perhaps the highest profile example.  As Robin Wauters at Techcrunch pointed out, “Merging something designed for public broadcasting (Buzz) with something inherently private (Gmail) was just looking for trouble.”

The issue of how many and what kind of social features to include also faces developers of collaborative tools like electronic lab notebooks.  Although collaborative tools are designed to help people work together, they are not  necessarily ‘social’.   But how can something that is designed to help people collaborate not be ‘social’?   As a way into looking at that question, let’s examine what Tom Coates, until recently head of product at Yahoo’s Brickhouse lab, was getting at it when he was quoted in the August 16 issue of Fortune as saying,

“Google is very good at building these utility-type products — search, email, and messaging . . .  But what they lack is a sense of how people share and collaborate.”

When I read that I thought, hang on a minute, what about Google Docs?  OK, Google Docs is not Google’s highest profile offering, but it is used by millions of people, so it surely must be included when considering Google’s ability or propensity to build ‘social’ products .  Document sharing is clearly a social activity, and the express purpose of Google Docs is to facilitate collaboration, so it must be the way that Google Docs is set up that, in Tom Coates’ view, excludes it from the ‘social’ category.

The Fortune article goes on to say, “Coates’s point is that you don’t have friends on Google, you have contacts and tasks.  These services reflect an engineering culture that is all about utility, but one that makes it hard for the company to create something that’s friendly and social.”   So in Fortune’s view in order to be ‘social’ it’s not enough to involve a group, in addition there needs to be an element of ‘friendliness’, and a focus on utility is implied to be anti-social.  Whether or not that is correct, it does constitute an explanation for Coates’s apparent oversight about Google Docs.  Google Docs is very much a utilitarian tool, and it is not designed to be particularly ‘friendly’.  So, even though Google Docs is intended to be used by groups of individuals, for these reasons it is not ‘social’.

Collaborative research tools, including electronic lab notebooks, are like Google Docs primarily designed for a utilitarian purpose — in the case of ELNs, to provide a platform for sharing and structuring experimental data and other information of interest to the research group.  On the Coates/Fortune view, this is at least one strike against their counting as ‘social’.  But since they are used by people not only to collaborate, but also to communicate, would they not benefit from being more ‘friendly’ and ‘social’?  Here are some capabilities, found in Facebook, that Fortune describes as the ‘social layer’.  Which of them would make an electronic lab notebook more ‘friendly’ (and useful!)?

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