Benutzer:O.tacke/OpenScience2011
Journal of Research Practice BearbeitenNachdem ich den Beitrag für die Cosci nicht fertig gestellt habe, habe ich dennoch weiter daran gearbeitet - und hatte irgendwann auch das Gefühl, er sei fertig. Der Text ist unten als Text V1.0 zu finden. Ich habe dann nach einer Zeitschrift gesucht, für die er passend sein könnte. Gestoßen bin ich auf das sehr interessante Journal of Research Practice, mit dessen Redakteur sich auch sehr unkompliziert kommunizieren lässt. Es gab zwar kein "richtiges" Review, aber immerhin eine Vorabbegutachtung mit vergleichsweise umfangreicher Rückmeldung. Seht selbst unten unter Feedback zum Text V1.0: Leider abgelehnt. Da ich den Text eigentlich gut finde, zweifele ich durchaus an mir selbst. Ich frage mich, ob es überhaupt Sinn ergibt, ihn noch einmal entsprechend zu überarbeiten... Text V1.x? BearbeitenÜberarbeite ich den Text wirklich noch einmal so stark??? Feedback zum Text V1.0 Bearbeiten1. Topic: Interesting, timely, highly relevant for JRP. 2. Content: The article mentions several recently used terms (citizen science, open science 2.0, etc.). There is a need to clarify these terms/concepts and develop a somewhat systematic account of how they relate to each other, their merits and difficulties, and the way they may change conventional notions and practices of research. There needs to be more systematic critical discussion. 3. Organization: Needs a more systematic argument. Suggestion for a more rigorous organization: (1) The meaning and origin of Open Science 2.0, (2) Current state and development, (3) Methodological core concepts of Open Science 2.0: aims, merits, and difficulties, and (4) Where do we go from here? Critical discussion and outlook. 4. Writing: Needs to follow a more disciplined and rigorous approach. The basic message comes through quickly, but the ideas do not appear to develop much further; also our attention as readers begins to waver. The message keeps being repeated in different terms and with various excursions into rather unspecific/remotely relevant territory. Clearly, there is a chance of condensing it into a much shorter article. Overall: The topic has a lot of potential, but the article lacks rigorous organization. However, we honour the author's intention in offering this as a working paper--quite in the spirit of "open science." To develop a publishable version, the author needs to move from description to argumentation. In its current state, the article is not ready for publication in JRP, although it has a potential for development.
Tagung #Cosci12 BearbeitenText V1.0 BearbeitenOpen Science 2.0: Opening scientific processes with weblogs, wikis, and twitter Technische Universität Braunschweig abstract - 3 to 5 sentences summing up the article Introduction BearbeitenScience has come a long way to its present state. When Galileo Galilei observed the sky for moons and planets, things looked quite different. Findings were kept secret or shared with a small number of other scientists in private letters only. With the spreading of the printing press and the establishment of scientific journals, the system began to change. In order to gain reputation, researchers had to publish their results instead of concealing them. For Nielsen, this shift was the first opening of science to a wider audience (Nielsen, 2011, pp. 174-176). Science thrived. Scholars now could base their research on what others had discovered and reflected on before. Moreover, they referenced their sources and published their own findings, thus augmenting the knowledge of humanity. Today, a second open science revolution is taking place. It manifests in initiatives such as Open Access and Open Data. It fosters collaboration on a large scale by means of digital media (Royal Society, 2012, p. 7). Although there is a tendency of scientific knowledge to become less excludable, there seems to be an inevitable barrier - the distinction between scientists and laypeople. Despite a more or less open access to information, it is hard for those outside the cathedra to understand what the scientific paradigm means. For instance, in 2011 former German Secretary of Defense, Karl-Theodor zu Guttenberg, was proven of having plagiarized others' work for his doctoral thesis. People on the street did not attach great importance to this issue. When interviewed, they often just answered: "Didn't we all once crib in school?" It seems that from the outside, only few actually know what is going on inside the proverbial ivory tower. In order to improve this situation, popularized magazines, TV shows, science centers, and further initiatives help to promote the understanding of scientific results to the public (Faulstich, 2006). These approaches often deliver products only. They neither reveal the processes which led to the creation of knowledge nor establish a connection to the scientists who did the job. Think of a delicious cake. You can admire the taste, but you know nothing about the baking or the baker. People do not know what problems had to be solved, what failures had to be endured, and what was learned from errors. Omitting such issues may leave a distorted picture of science, which may in turn lead to misunderstanding. Certainly, approaches such as Open Access broaden the perception of scholarly work, but they do not help the public to learn to think scientifically. In addition, the flow of information from science to public does not include a feedback channel in the opposite direction. A typical question regarding bi-directional flow of information might be: cui bono? What will scientists get in return for their munificence? One simple answer might be "maybe nothing at all". But given the tremendous challenges of humanity - such as global warming, social inequality, or financial crisis - science is a search for knowledge which has to be aware of its social responsibility (Schmidt, 2011). It should incorporate ideas from all people who might be concerned. A more complex answer would probably deal with the notion of transdisciplinary problems. Those call for pooling of micro expertise in different fields in theory and practice (Nielsen, 2012, pp. 24-26). A more complex answer would probably also highlight the potential benefits for scientists' work. That is what I am going to do in this paper. First of all, I gradually develop my notion of Open Science 2.0. Subsequently, several examples illustrate its application throughout typical stages of scientific work. I continue by discussing issues regarding the surrounding conditions of science, individual traits of people involved, their interactions, and the possible influence of the subject of research. Finally, I conclude that although there are examples of successful implementation of Open Science 2.0, crucial factors of success have yet to be identified. Open Science 2.0 BearbeitenIf you were asked to think of a scientist, what image would come to your mind? Is it a white haired man in a white lab coat? Is he busy with test-tubes, withdrawing himself from others, solitarily racking his brains, and losing touch with reality? This is how many people picture a scientist - a hermit in an ivory tower. More formally, this approach could be characterized as traditional. It produces knowledge in a disciplinary and a primarily cognitive context. Gibbons et al. (1994) call it Mode 1, and for many scholars it is identical with what is meant by science. In contrast to this notion, Mode 2 is carried out in a context of application and intends knowledge to be applicable directly. It supports transdisciplinary collaboration among scientists and practitioners of different domains. It relies on heterarchy instead of a strict hierarchy. To set the record straight: Mode 2 is not meant to replace Mode 1, but to complement it. Open Science tries to merge both. On the one hand, some authors point out that Mode 2 is nothing new but "the original format of science before its academic institutionalization in the 19th century" (Etkowitz, & Leydesdorff, 2000, p. 116). On the other hand, just recently, a group of German scientists demanded that the scholarly production of knowledge must not be completely detached from normal life. Science should be recognizable as research for humanity. The group also requests a more transparent and diligent presentation of the scientific course of action ("Für eine Entschleunigung der Wissenschaft", 2011). Regardless of being old wine in new tubes or not, there seems to be a demand for more Mode-2-ish procedures in academia. In twenty-first century, inter- and transdisciplinarity are becoming more important (Hüther, 2012, p. 11). As problems are getting more complex and require a joint effort of diverse teams, collaboration among scientists gains relevance. In fact, there is good evidence that an increasing number of results is achieved by team efforts. "Findings suggest that in sociology specifically and science generally the trend is toward greater collaborative scholarship. At the turn of the twentieth century, better than 90 percent of the articles appearing in major periodicals in physics, biochemistry, biology, and chemistry were sole authored. Today, over 95 percent of such articles are collaboratively published." (Babchuk, Keith, & Peters, 1999, p. 5) Also, studies show that collaboration has a positive effect on scientific quality (Andrade, de los Reyes López, & Martín, 2009, p. 308). An extensive list of studies affirming these observations in different disciplines was compiled by Tacke (2010, p. 37-38). To recap the discussion so far, Open Science advocates a more collaborative effort across disciplines. It often occurs in a context of application. This brief description is not sufficient, though. It lacks the popularization of science which began in nineteenth century and tries to promote scientific literacy among the general public (Daum, 2006, p. 34). For this purpose, scientists or journalists "translate" scholarly findings into a "more simple language" and incorporate them into books, TV shows, museums, science centers, or open house presentations. Those measures should also be considered elements of Open Science. Furthermore, the previous description does not yet cover the accessibility of actual scholarly (by-)products such as journal papers or the data gathered during the course of research. In order to foster broad engagement in science, anyone should be able to retrieve those results online without payment or other restrictions. This idea of open access or open data (for an overview see Herb, 2012, pp. 11-20) prospered in recent years. Laakso et al. (2011) had a closer look at the number of open access journals and articles from 1993 to 2009 and found a rapid growth above average compared to normal publishing. This development is most welcome for many scholars and can also be part of Open Science. Unfortunately, most "people don't understand the technical details of a scientific result, let alone how it was obtained, what assumptions were made, in what context the result is applicable, or what practical implications it has." (Wing, 2011, p. 10) So far, Open Science does hardly provide an insight into its inner workings. But how does research actually look like? One way to answer this question is to portray the typical process as steps arranged in a cycle (Neylon, 2009, slide 30 and Mietchen, 2012, pp. 56-57). The steps may vary in intensity depending on discipline, resources given, etc. While in physics devices may cost millions of dollars, progress in some domains of social sciences can be made just by rigorous reasoning. Nevertheless, the sequence outlined above is roughly the same. Your project starts with an idea, e.g. to explain a phenomenon that has been observed. Maybe someone already found a proper solution - case closed. If there still is a certain gap in knowledge, things get interesting and you develop a project plan on how to find your answers. You might need special machinery, co-workers, etc., and you will have to fund those resources by tax payers' money or donations from backers. Often you will have to develop a case of support, send it to sponsors, and hope for approval. If everything works out fine, you can plan in detail, record your data, and finally process it. Afterwards, you publish your findings so others can learn about them. If others build new ideas upon yours, the cycle is complete.  Open Science does two things in order to shed more light on these complex activities, making the scholarly production of knowledge comprehensible to a wider range of people. First, it tries to make processes more transparent, so you can observe what scientists are actually doing. They let information pass from inside the scientific realm to the outside. Scholars e.g. discuss their ideas or methods openly. Second, they might also allow others to participate in research. Anyone could take part in what scientists are doing - thus being a scientist. Some might frown upon this statement, arguing that this status requires membership at scholarly institutions such as universities, but in fact anyone who uses scientific methods to acquire new knowledge can be called a scientist. This concept can be related to the idea of Open Innovation known in economics. It advocates making boundaries between companies and its' environment more permeable for ideas - in both directions - in order to improve the outcome of research, development, and the commercial launch of products and services (Tacke, 2010, pp. 39-40). Finally, talking about Open Science 2.0, the famous numerical suffix needs to be explained. It is obviously derived from the term web 2.0 and used frequently, yet there is no consistent definition. It is commonly associated with online applications that facilitate manifold forms of communication, allow collaborative creation of content, and support sharing it with others - think of blogs, wikis, online community websites like Facebook, media-sharing platforms such as YouTube. Using those or similar services for opening some processes of science seems to be a logical approach. Both share the same characteristics such as openness and participation from a wide range of people. In conclusion, the term Open Science 2.0 means the application of web 2.0 services to the domain of research (and education as we will see later on). It does neither mean a new kind of science nor a better way of doing science per se. Nevertheless, it challenges traditions and may require scientists to adapt to a changing environment. Open Science 2.0 does not have to implement all aspects that were addressed so far all of the time. Depending on how many elements are incorporated, it is plainly "more" or "less" open to the general public. Having a closer (but brief) look at the adoption and use of web 2.0 tools in scholarly communications reveals a rather cautious profession. According to an inquiry of Procter et al. (2010), only 13% of the academic staff and PhD students in the UK resort to web 2.0 frequently. Indeed, there are 45% who claim to use it at least occasionally, but further investigation shows that they add in browsing Wikipedia or reading blogs. 39% declare themself as Non-users, leaving 3% of missing values. Similar studies show that the situation in Germany is very much alike (Koch, & Moskaliuk, 2009, and Bernius, Hanauske, & Dugall, 2009). Examples BearbeitenBefore discussing the potential and shortcomings of Open Science 2.0, it is helpful to glance at some examples that illustrate the intended use. For each stage of the research cycle, I am going to present at least one way to harness the internet and web 2.0 tools in particular. However, the examples are not meant to represent best practice as they may depend on other measures or certain prerequisites. In the novel "Measuring the World", Daniel Kehlmann portrays the life of Carl Friedrich Gauss. During the wedding night, the famous mathematician jumps out of bed to note an idea that had just struck his mind (Kehlmann, 2005, p. 150). He could not risk forgetting the thought which turns out to finally become the method of least squares. In real life, such urgent situations are probably very rare, but generating ideas is part of what scientists do all day long. They can choose to rely on their memory, they can write them down and reflect on them later just as fictional Gauss did, or they could spread them on the internet instantly. Using Twitter, scientists can post short messages to a global audience and ask for feedback. There might be some people who are interested in the subject and start a brief discussion with you. Perhaps, there is someone who can point out relevant literature on the issue from a different field than your own, giving you a fresh perspective. Or, unfortunate as it might be, you quickly get to know that someone else already had the same idea, solved the corresponding problem, or simply proves you wrong. Science could save a lot of time this way. If Twitter had been available earlier, maybe scholars would not have had to wait until the seventeenth century to find out that black swans really exist. When developing the rough design of a research project, it can be beneficial to receive feedback from others. A blog might be a convenient tool. If problems arise during planning, they can be described and others may comment and suggest solutions. The approach is similar to chatting about ideas via Twitter, but you have more space for discussion and it is easier to keep track of progress. Also, you do not have to attend the debate right at the beginning, but you can join later and still get the full picture. If the outline of your research project is conclusive, you can receive rather large sums of money from few governmental or industrial sponsors. Alternatively, you could try to utilize a crowd funding platform where many people pool their money to support endeavors they approve of. The single lump sum can be very small, but repeated tiny donations can add up to a large investment. This way, Tim Schaffer who is a well-known developer of computer games, managed to accumulate more than 3.3 million US dollars before he had even fully started programming (Kickstarter, 2012). Of course, Schaffer could build on his popularity and what works in computer industry may not work in science, but there are at least three platforms experimenting with the concept (The Open Source Science Project, n.d., SciFlies, n.d., and as of November 2012 ScienceStarter.de, Witt, n.d.). The planning phase of a research project could be opened using a wiki. The creation of this very article was supported this way (Tacke, 2011a). It was originally intended for presentation at the "International Conference on Science and the Internet 2012", but it eventually became too long and was withdrawn. The procedures of the conference called for an abstract that was reviewed first. I received positive feedback and was allowed to write a full paper. A wiki page was used to outline the structure and contents of the intended article in keywords. Twitter was used to ask for input and opinions. I received several hints for literature and links to websites discussing examples of my subject. Furthermore, someone proof-read the final abstract and tweaked the text. In return for this assistance, the reviewers' statements were published on the wiki and on a blog. Thus input given was valued and the general public gets insights on how some processes in science work. After planning, in empirical settings data has to be gathered to falsify or preliminarily support hypotheses. Cohn (2008) reports of collaboration of scientists and volunteers along the Appalachian Trail. Laypeople position cameras and prepare and deploy a mix of scent-gland extracts that attract animals. They help scholars to learn about the population of the region and are essential to collect information as input for scientific studies. While this example does not involve the internet, a similar project tries to discover the reason for vanishing and emerging ladybug populations in North America. Volunteers can look for ladybugs and upload their photographs and additional information to the project website (Lost Ladybug Project, n.d.). Some bio-chemists use a very different approach: a puzzle video game named Foldit (Nielsen, 2012, pp. 146-148; http://fold.it). Its objective is to arrange several amino acids in order to generate a particular protein as compact as possible. The better the solution, the higher the player's score will be. Researchers can use the high-ranking solutions to solve problems in the real world, such as determining the shape of organisms based on their genetic code or finding cure for diseases. In fact, at least one publication specifically mentions Foldit as beneficial for the results (Khatib et al., 2011). Sometimes this approach is called "citizen science", but of course other scientists would be able to chip in data as well. Processing data can be a time consuming effort. Not only do you have to apply statistical tests and interpret the results, but often there is no tool that is suitable for your specific needs. It may be necessary to design appropriate algorithms first and then to implement them in software, enabling you to tackle your problem conveniently. While some of these algorithms might be tailored to a very particular problem, many are quite generic and actually there is no need to reinvent the wheel again and again. Scientists could benefit dramatically if the source code for typical operations was availably freely (for a general discussion on the potential of free software see Stallmann, 2012). Not only could they save time for their own research, but they could replicate and thus independently test the results of others much easier. Fomel & Claerbout (2009) labeled this practice "reproducible research". They call upon scholars to always ask themselves whether they have done enough to allow the readers of their papers to verify and reproduce the computational experiments. The most popular example for Open Science within the publishing phase is probably Open Access. However, as mentioned before, it does not reveal the inner workings of research. A different example, which sheds some more light on the process of publishing and allows interaction, is Open Peer Commentary. It is not a fixed term and may come in different flavors - one implementation is described by Pöschl (2011). He references the journal "Atmospheric Chemistry and Physics" (http://www.atmos-chem-phys-discuss.net/papers_in_open_discussion.html). All papers are subject to a quick preselection. Submissions that are entitled for the formal peer review process get published immediately on the internet. Up to this point they are called discussion articles. During the next eight weeks, anyone can comment publicly. Furthermore, the reviewers' feedback will also be made accessible (anonymously, if requested so). Authors may join the discussion as well. The latter then can revise their paper which will be published in the journal's print version after final approval. Pöschl (2011, pp. 120-121) emphasizes several advantages compared to the traditional model. The preliminary results can be spread much earlier. Additionally, the original contribution before revision remains accessible. The interactive peer review and the public discussion allow direct feedback, may impede plagiarism, and they record the academic discourse related to the article. Moreover, it unveils the reviewers' efforts which normally go unnoticed. The final stage of the research cycle is labeled "read". It can get a collaborative notion if you consider sharing your thoughts with others. The web service Readmill (http://www.readmill.com) was designed specifically for this purpose. Other online services such as Diigo (http://www.diigo.com) allow you to highlight text on a website. You can also add some comments - just as you might be used to in word processing software. Your thoughts will appear as a sticky note on your screen. You can decide to make your comments public, so any user of Diigo visiting the website would be able to learn from you, perhaps sparking new ideas for research... Discussion BearbeitenIn the early Age of Enlightenment, science became the foremost impetus of progress and meant production, adoption, and transfer of knowledge (Faulstich, 2011, p. 19). But who can really benefit from Open Science 2.0? From a philanthropic perspective, it is normal people who can gain education. Fostering scientific literacy with wikis, blogs, and similar tools becomes a moral obligation. In contrast to instructing non-scientists by means of prefabricated material, instruments of web 2.0 promote self-education by actively participating. This approach rather reflects situated learning in communities of practice (Lave & Wenger, 1991). An example of amateurs doing science is documented by Blackawton et al. (2011) - yet without involvement of the internet. A group of 8- to 10-year old children investigated the behavior of bumble-bees in connection with different stimuli. They were supported by adults, but the children asked the questions, hypothesized the answers, designed the experiments, and tested their assumptions with the data that they had collected. They found out that "bumble-bees can use a combination of colour and spatial relationships in deciding which colour of flower to forage from." (Blackawton et al., 2011, p. 168) While most people will probably agree that society as a whole could profit from opening science, many will doubt that it is expedient for researchers. Nielsen (2012, pp. 133-142) proves them wrong by describing the discovery of so called pea galaxies. A group of volunteers helped scholars to categorize galaxies on freely accessible photographs of space. A special online platform called Galaxy Zoo had been set up for this purpose (http://www.galaxyzoo.org/). The group stumbled across images showing bright greenish star formations. It was very unusual for galaxies to be green. The volunteers were interested, but no one was able to explain what they had found. They further investigated the subject, developed hypotheses, and eventually taught themselves the technique of spectral analysis. This method was crucial to find out what caused the unusual color. Finally, two astronomers found time to collaborate with the amateurs and provided sophisticated software for analyzing the images. They confirmed the discovery of a new type of galaxy by laypeople (Cardamone et al., 2009). However, we could also wonder why scientists should engage in Open Science 2.0 beyond altruistic reasons. One answer has already been given in the previous paragraph. The amateurs' findings gave scholars new opportunities for research and lead to a publication. Another obvious answer simply is: saving time and money. The research project along the Appalachian Trail cannot do without the volunteers. The managers could not afford to hire enough research assistants for gathering all the data needed (Cohn, 2008, p. 193). Likewise, in the Galaxy Zoo project, categorizing galaxies by just a few scholars would virtually have taken forever. Opening the processes for others and especially a large number of people can be indispensable. The potential outside the scientific realm can also be illustrated with the story of Srinivasa Ramanujan (Zagier, 2010). In 1913, he worked as a clerk in India, had no university education, and was totally unknown. He had taught himself mathematics in his spare time and sent letters containing some of his thoughts to well-respected mathematicians in Great Britain. Two of these simply binned the documents, probably assuming that reading them would be a waste of time. Luckily, Godfrey Harold Hardy had a closer look at the manuscripts and recognized that there was more than meets the eye at first sight. He exchanged letters with Ramanujan, learned about his mastery, and invited him to Cambridge. The world of mathematics would have lost precious knowledge if Hardy had turned Ramanujan down just because he was not well-known. Another familiar argument for more permeable boundaries in science is, of course, the faster transfer of ideas from theory to practice and vice versa. In an interview, Stanford professor Andrew Ng reports on an engineer who had learned about risk evaluation via online video courses. The amateur gave important impulses during an academic conference (Noack, 2012). The oceanographer Stefan Rahmstorf says that he benefits from the comments on his blog. Questions from readers had even given him new ideas for his work (Zickgraf, 2010). This list could be extended quite a bit. General Effects While the examples above show the value of non-scientists' contributions, it is possible that you will not be able to stir up interest for your project. It may simply be too specialized. Still, opening your work online can pay off as other scholars may come across your ideas and be attracted. In general, collaboration among scientists seems to improve the quality and the efficiency of research, e.g. by pooling resources (Royal Society, 2011, p. 57). Collaboration may even increase the citation rate of papers (Royal Society, 2011, p. 59). Besides these rather hard facts, scholars can also benefit from a broader perspective due to links between different fields of research, e.g. bionics by combining biological methods with engineering. I for myself once outlined an article on discovery learning in a public wiki. I received valuable hints from a linguist, someone completely out of my domain. Besides improving content, scholars can also gain more public awareness for their activities. Classic public relations such as articles in newspapers will hardly be replaced by blogs, wikis, or online platforms for social networking. Anyhow, scientists can benefit from presenting what they are working on to interested people. Allowing them to get in touch directly can pay out as well. Noack (2012) reports on professors becoming quite famous by opening their courses to the public using online videos. At this point we should recall the crowd funding example given above that relies on certain popularity in order to raise funds. Also, less monetary gratuity can stem from opening your work. Speaking from my own experience, I was invited to conferences not despite but because I blog and tweet. Contemplating science as a whole, we should note the vast opportunities for learning that emerge from Open Science 2.0. Young academics can benefit considerably from being able to study feedback in open peer reviews (Reinmann, Sippel, & Spannagel, 2010, p. 227, also Fritz, 2011). This accounts for response to their own papers, but also for reviews of others' work. Making your progress more transparent can also help to understand how errors have arisen, how they can be avoided, and what can be learnt from them. Furthermore, openness "facilitates a systemic integrity that is conducive to early identification of error, malpractice and fraud, and therefore deters them." (The Royal Society, 2012, p. 8) The problem with all this openness is: it is not always possible. The "system" in which science takes place may set certain boundaries. For instance, when corporate funding is involved, you might not be able to talk about what you are doing because it relates to internal knowledge of companies. Often, you are even legally bound by nondisclosure agreements. Another restriction that you often cannot bypass comes with your schedule. Blogging and other activities in web 2.0 consume time which can be very sparse and only spent once. Scientists may feel that they have to make a trade-off between opening their processes and leaving enough time for their usual routine and other tasks. However, there are some opportunities to combine both. For example, if you keep account of experiments in a lab notebook, you could simply use a public wiki, thus giving others access to your experiences. Moreover, there is another explanation why investing time into Open Science 2.0 is not necessarily wasted. Rating the outcome should take several dimensions into account. According to Bourdieu (1983), there is not only economic capital in terms of money or property. There is also cultural capital, e.g. the knowledge that you acquire. Finally, there is social capital which represents your investment in a social network - in connections to other people. Bourdieu claims that the three types of capital can be converted into each other. Putting some of your hope on social capital may pay off in the long-run as revenues can be high. You get what you give. Since we are already on economic grounds, let us compare the traditional way of doing science with technology-enhanced science from the perspective of innovation management. At the dawn of the classic system, a lot of effort was put into establishing journals. Much energy was consumed by setting up the scholarly infrastructure and developing today's processes. Then at some point in time, the performance of science increased vastly. Presently, we can see its limits, though. It becomes more and more difficult to maintain the current pace, it becomes harder to find enough reviewers for the large amount of papers submitted to journals, scholars protest against exploitative behavior of publishers (Aaronson et al., 2012), etc. Science has not come to a halt and will continue to yield results, but further fine-tuning the status quo will probably not result in more efficiency. Foster (1986) noticed this relationship of effort and performance for technology in many areas. It results in an s-shaped curve if drawn into a two-dimensional diagram. Foster (1986, p. 102) also observed that those s-curves almost always come in pairs as technology advances (see image 2). The new technology, represented by the upper right curve, has the potential to deliver better performance than the old one. Unfortunately you do not know in advance, and both curves do no connect seamlessly. There is a gap between them representing discontinuity. Looking at a given effort in the overlapping section (dotted grey line in the image), you must conclude that the performance of the old technology is better than the performance of the new one. It may lead you to bet on the wrong horse in the long term.  Moreover, when someone proposes something new, he or she is confronted with all the supposable advantages of the present system. It gets romanticized and pictured as it once may have been imagined to be. This idealized version can hardly be criticized, but it is compared to the shortcomings of what is about to evolve (Dueck, 2012). The same might be true for traditional science and 2.0-ish science. The new approach is disrelished despite its potential and adopted very hesitantly. Further barriers to widespread application of open principles lie in the system of reward, esteem and promotion in universities and research institutes (The Royal Society, 2012, p. 10). The motto "publish or perish" has led to a situation which breeds scholars who are reluctant to share their thoughts publicly before they have been printed in journals. Scientists fear that someone might "steal their ideas" and come up with a paper first, thus taking away the glory. This point of view neglects that you could proof your creatorship of an idea easily if you really wanted to. Wikis usually mark their contents with timestamps and can be used as evidence. The "thief" would have to cope with punishment by the scientific community (Tacke, 2010, p. 41). Openness rather deters malpractice and fraud as was already stated above. Since the scientific system is based on reputation to a large extent, scholars may fear to endanger their standing. They avoid doing something that does not comply with standard customs. Even writing a popular science book seems to be able to inflict a negative impact on esteem in academia. Why else should the physicist Bojowald (2009, pp. 9-10) feel obliged to explain himself in the foreword to "Once Before Time"? Engaging in Open Science 2.0 actually deviates a little more from the scholarly norm than writing "books for the masses". Presently, scientists tend to only communicate the successful completion of research projects to the public. But of course, there are lots of detours, setbacks, and failures in scholarly work. If scientists conceal these, they deform the picture of science. It then only includes the shiny jigsaw pieces. The poor outcomes, such as reviewers' negative feedback to a paper (Tacke, 2012b), reports of bad speeches (Tacke, 2012a), or a discussion of drawbacks in research (Tacke, 2011b), are rare. Would they really threaten a career in science? Individual Influence Besides all the barriers imposed from the environment, personal traits can hinder Open Science 2.0. Being open is a crucial requirement (Tacke, 2010, pp. 41-42). If scientists are not willing to give something, they are unlikely to receive anything. In web 2.0, this does not only relate to insights into academic work, but also to the personality of the scholars. Some might dismiss revealing something about oneself as unprofessional, but it is essential in 2.0-ish communities. In fact, Johnson (2011) found that students' perception of instructor credibility on Twitter is best when mixing scientific information with personal tweets. Unfortunately, so far nobody examined this effect for scholars. Certainly, openness becomes difficult when private matters are involved. Then again, being open does not mean to completely unveil one's inner life on the web. An essential issue when acting online in wikis, blogs, and similar platforms is loss of control. Every piece you write, every image you post, and every thought you utter can be observed by others. Moreover, anyone can publicly react on your input, spread it, or even use or misuse your ideas. You cannot keep the consequences of your actions in check. Therefore, engaging in Open Science 2.0 requires being able to deal with this uncertainty to some extent. While open learning or research may offer authentic contexts and new opportunities, they also present new challenges. Scientists and laypeople have to be prepared for acting in public and need to accept that mistakes might find a global audience (Hofhues, 2010, p. 412). Another aspect to be dealt with is the lack of guidance on the web. From a conversation with a scientist I learned that he images the internet as a bee hive or an ant colony without evident structures. With so many individuals interacting and participating, he wonders how achievements could possibly be attributed to single persons. He even mentioned that he latently fears to become insignificant. In a scientific community with prestige as major motivation for research, this personal perspective becomes relevant. On the other hand, some scholars simply do not adhere to the race for reputation. For instance, Grigori Perelman refused to accept the prestigious Fields Medal and trophy money for his proof of the Poincaré conjecture - one of the most difficult mathematical problems. "I'm not interested in money or fame," he is quoted ("Russian maths genius Perelman urged to take $1m prize", 2010). He was content with knowing that the proof was true and that he solved it based on the work of others, e.g. Richard Hamilton. Limitations for Open Science 2.0 on an individual level do not only concern scholars, but amateurs as well. One important factor is a concept called digital divide. Its goal is to explain how information diffuses in social networks and to find relevant variables which determine its flow. According to Hilbert (2011), these are a persons' characteristics such as level of income or education, the technology used, and the intensity of connection ranging from access to information to its effective adoption. Putting it in a nutshell: if laypeople do not have access to the internet for whatever reason, they cannot connect with scientists online. If laypeople are not familiar with blogs, wikis, platforms for social networking, or similar tools, they can neither provide support nor benefit themselves. In consequence, the digital divide can severely influence the effectiveness of Open Science 2.0. Before its full potential can unfold, it may be necessary to improve the infrastructure for telecommunications first. While in so called developed countries virtually anyone can get access to the internet easily, it can be more difficult in less developed parts of the world. Furthermore, it might be necessary to foster media literacy at schools, universities, and also at adult education centers (Spannagel & Tacke, 2012, in print). Otherwise, Open Science 2.0 might remain a niche. Aspects of Interaction As stated above, laypeople can aid in gathering and processing data in research projects. For instance, they can help to classify galaxies on the Galaxy Zoo website. There are many more simple tasks that can be done by untrained people. Thus, they participate in processes of science, but they do not necessarily learn about it. The history of economics shows a parallel to this dilemma. At the end of ninteenth century, Frederick Taylor intended to boost productivity of manufactories, but not by extending labor time. He envisioned maximum prosperity for the employer, coupled with the maximum prosperity for each employee. He developed several principles which today are known as scientific management (Taylor, 1911). They advocate the strict separation of planning from doing. Some people were responsible for innovation and for designing the structure of production steps while others had to carry out their orders. Furthermore, scientific management suggested decomposing each task into simple standardized subtasks. Thus, even unskilled workers could escape poverty and get a job. Taylor's ideas lead to an increase in productivity, but they had downsides as well. Labor was too simple, monotonous and humans had no opportunity to unfold their individual potential. If Open Science 2.0 projects want to really foster scientific literacy, participation of laypeople should be more than just outsourcing simple tasks. Firstly, these do not help understanding science. Secondly, they are boring and it would be difficult to find volunteers. But then, why do people engage in Galaxy Zoo? It offers a meaningful task; it can be motivating to know that you are contributing something to society. Galaxy Zoo offers access to more information on the subject and it brings people with similar interests together. Scientists and laypeople interact and exchange ideas via an online forum. As already mentioned, a major discovery in astronomy was the result. We can note that collaboration between scholars and practitioners can be beneficial for science. Having said that, there are arguments depicting the challenges posed for collaborative research. Kieser & Leiner (2012) point out that - at least in economics - communication between scientists and managers is extremely difficult. The intentions and communication styles of both groups are said to be incompatible. Pleading Luhmann's system theory and psycholinguistic analysis, they conclude that practitioners without research expertise cannot collaboratively produce rigorous research with scholars. Even if intensive interaction was possible, other difficulties could arise. Working closely with others can lead to conformity of thinking. In certain cases, it will shut out criticism. "The more amiability and esprit de corps among the members of an in-group of policy-makers, the greater is the danger that independent critical thinking will be replaced by groupthink, which is likely to result in irrational and dehumanizing actions directed at out-groups." (Janis, 1972, p. 198) Gilbert, Bergstrom, & Karahalios (2009) indeed observed that highly frequented blogs isolate readers in so called echo chambers. They tend to attract approving comments and to repel dissenting opinions. Additionally, the infamous shitstorm reminds us that emotional and irrelevant criticism also exist on the internet (Mavridis, 2012, p. 246). It can be questioned, though, whether science blogs are effected by these phenomena. Schulmeister (2010) examined several German science blogs on education policy and eLearning and revealed a rather small number of comments. They mostly comprised positive feedback, congratulations and encouragement, but hardly contributed to a scholarly discourse. Contrariwise, the results in the blog of Fields Medalist Timothy Gowers show that scientific progress can be achieved by joint work of experts and laypersons. Collaboratively, they solved a non-trivial mathematical problem openly (Gowers, 2009a and Gowers, 2009b). It should also be noted that the study of Schulmeister proves the fear of misbehavior in comments to be gratuitous. Shitstorms seem to pass by. In consequence, instead of suspecting too much undesired feedback, it is deemed appropriate to wonder if there will be an audience for scientists' thoughts and if someone is going to contribute something. Just as in online marketing, it may be not a question of "is there a demand for my offerings" but of "how can I connect both" (Anderson, 2009, pp. 192-194). Good communication is necessary. "Good communication is assessable communication, which allows those who follow it not only to understand what is claimed, but also to assess the reasoning and evidence behind the claim." (The Royal Society, 2012, p. 38) However, that is easier said than done. Nobel prize laureate Erwin Neher stated that he appreciates colleagues who get involved with blogs and other forms of public science. Nevertheless, he doubts that every scholar is a good communicator and that those who are not were better off with leaving this task to journalists (Epping, 2011, p. 43). Subject Relevance Concluding this section, I am going to have a closer look at research subjects. Although there are some examples proving that Open Science is possible and processes can be designed transparently, some tasks might not be suitable. Bornmann, Herich, Joos, & Daniel (2012) examined the benefit of open peer commentary. They investigated the feedback given during public peer review for articles in "Atmospheric Chemistry and Physics" and compared the comments to the formal reviews. They found that the latter better supported selection and improvement of papers. However, they also pointed out that the order of comments might play a significant role. Readers from the general public may be reluctant to comment on issues which have already been raised by the reviewers. Besides particular tasks, "many areas of science demand levels of skill and understanding that are beyond the grasp of the most people, including those of scientists working in other fields." (The Royal Society, 2012, p. 8) In this respect, it is most unlikely that an open approach is going to yield results on very specialized topics. Contrariwise, if the problem is too simple, it will hardly be challenging enough to find contributors and it is probably not worth the effort of collaboration. Nontheless, if a medium ranked abstract problem in mathematics can provide opportunities for fertile transdisciplinary research as shown by Timothy Gowers, a problem close to practice is even more likely to be suitable. For example, think of teachers who could participate in projects on educational sciences (Spannagel & Tacke, 2012, in print). Throughout the whole research cycle, they could give valuable input based on their expertise in classrooms that scientists do not necessarily have. Future Prospects BearbeitenAlthough we discussed possible benefits and limitations of Open Science 2.0, it is hard to conclude whether it could be a leap forward or just a small evolutionary step - or perhaps even a dead end. Some research on research seems to be needed. As we observed, a fertile environment for Open Science 2.0 resembles a vital community of practice. Therefore, I suggest to use a framework for further investigation that helps us to analyze situations and to design environments suited for vital learning. The concept of Theme-Centered Interaction (TCI) established by Cohn (2009) seems to be a conducive instrument. TCI is an extensive and holistic approach providing a philanthropic framework for work and learning environments. It allows to perceive situations from different angles and to shape social processes suitable for personal advancement (Spielmann, 2010, p. 15-16). TCI aims to dynamically balance the matter of a subject (IT), each individual person involved with different temper, abilities, etc. (I), relationships and interaction (WE), and the organizational, physical, structural, social, political, and ecological surroundings (GLOBE) which enclose the other three factors (Löhmer & Standhardt, 2008, pp. 56-58) as depicted in image 3.  If TCI is intended to give guidance for researching Open Science 2.0, if TCI shall help designing appropriate environments for research and learning in practice, it seems reasonable to structure research questions accordingly. Elements of Open Science 2.0 which should be further investigated can be sorted as follows:
For instance, let us consider we want to find out if Twitter is a vital tool for Open Science 2.0. We might have to consider the discipline as part of "IT", because what works well in linguistics might fail in mathematics due to the need of displaying formula. We might have to bear in mind the "I", since some people could lack proper knowledge about the platform. The "WE" can become relevant if visual interaction is required to grasp a problem precisely. Finally, the "GLOBE" could be important, since Twitter might rather play a minor role during the planning phase of a research project, but be useful in other phases. The discussion in this article shows that clearly there are shortcomings of Open Science 2.0. Science in mode 2 is not better than in mode 1. Both are vital and scientists should choose what fits best regarding the four factors of TCI. The same applies to the use of web 2.0 technology. However, insisting on mode 1 as the traditional and sole best way is unfortunate and a careful stimulation of more open approaches might not be the worst idea to think of. Unfortunately, the "changes that are needed go to the heart of the scientific enterprise" (The Royal Society, 2012, p. 7) and academia is a deeply conservative profession (Marginson, 2000, p. 26). Questions of incentives and motivation arise quickly. Nielsen (2012, pp. 190-191) discusses this topic and concludes that a governmental policy of compulsion is inevitable. Publication of results should be legally bound to open access and sharing of data should be made mandatory. Additional pressure could be put on scientists if grant agencies restricted funding. For instance, the European Commission (2012) recently announced that as of 2014, all articles supported by the "Horizon 2020" research program will have to be made openly accessible not later than 12 month after first publication. Once again, this advance touches only products of science, but not processes. Furthermore, Nielsen (2012, p. 193) speaks of an "economy based on reputation" that needs to be adjusted. But science should not be an economy. I may be called naive or starry-eyed, but in my opinion scholars should want to be more open while working, not be urged or even forced to. We can try to raise the general public's awareness of Open Science 2.0 for sure. We can commend the efforts of other scientists. But if you want others to really change, you have to invite, encourage, and inspire them. Extrinsic motivation is nothing but breaking in a person and does not lead to the unfolding of potential (Hüther, 2011, pp. 125-126). If we want others to become more open, we must practice what we preach and set a good example, or as Gandhi (1999, p. 241) put it: "We but mirror the world. [...] If we could change ourselves, the tendencies in the world would also change." References Bearbeiten
Acknowledgements BearbeitenThanks to all those who supported me in bringing this paper to life, be it by giving hints on literature, by donating ideas, or by proof-reading. In alphabetical order: Anja Dahlmann, Jörg Eisfeld-Reschke, Sönke Graf, Bastian Greshake, Schimon Grossmann, Björn Hobus, Sandra Hofhues, Christian Spannagel, and Daniel Spielmann. Rückmeldung von den Gutachtern BearbeitenWenn man Beiträge zu wissenschaftlichen Konferenzen (oder bei Zeitschriften) einreicht, werden sie häufig erst einmal von anderen Wissenschaftlern begutachtet. Sie entscheiden, ob der Beitrag angenommen oder abgelehnt wird und geben den Autoren Rückmeldung und Hinweise auf Dinge, die noch beachtet werden sollten. Diese Beurteilungen bekommen Außenstehende normalerweise gar nicht zu Gesicht. Damit man einen Eindruck davon bekommt, wie so etwas aussehen kann, haben wir die Kommentare zu unserem abstract hier eingefügt. Review 1 Bearbeiten
Der Vortrag wird höchstwahrscheinlich dem in unserem Doktorandenseminar gehaltenen Vortrag des ersten Autors sehr ähneln, was a priori nicht schlecht sein muss. Ich bin dafür, den Beitrag anzunehmen, möchte aber die Autoren um mehr 'Wissenschaftlichkeit' in ihrem Abstract und in ihrem Vortrag bitten, d.h. um kritische Auseinandersetzung mit z.B. dem Konzept "Open Science". Es reicht definitv nicht aus, nur über ihre eigenen Erfahrungen mit Wikis, Blogs, Twitter, usw. zu erzählen. Auch wichtig: der Abstrakt muss mindestens 2-3 bereits vorhandene Studien nennen! Fazit: die Autoren biiten, die Submission entsprechend zu überarbeiten bzw. dies bei der Vorbereitung des Volltextes des Artikels zu berücksichtigen. Review 2 Bearbeiten
This promises to spark interesting discussions during the conference. Some thoughts and questions that came to my mind: When scholars open up their work spaces for others to see "research/teaching in the making" who actually listens to this, watches or reads it? From the point of view of the researcher, permitting access to what would otherwise happen behind closed doors offers opportunities for the general public to further develop their understanding of science. But I wonder how many people (that are not from within the same field) actually seize these opportunities. I think the paper could benefit from a discussion of an "audience" perspective. Review 3 Bearbeiten
The authors describe the concept of "Open Science", which they frame as a participatory process that brings together institutionalized science and civil society. They begin by criticizing current approaches to science communication in the mass media, which they see as unidirectional and too narrowly focused on explaining the outcomes of scientific research to lay audiences, rather than involving the general public in the framing of research agendas. I agree strongly with the authors' suggestion to describe failure as a natural part of the scientific process -- this may indeed further public understanding of science in a considerable way. In its current form the paper could do more to a) systematically define Open Science and contrast it with the current, "closed" scientific paradigm and b) critically reflect what the shortcomings of the proposed and rather idealized new direction of science could be (e.g. What happens to those citizens who aren't digitally literate? Will research agendas be subjected to (digital) mob rule? Etc). Finally, a discussion of the broader policy dimension of Open Science would be greatly appreciated (How could Open Science be incentivized?). abstract (for a talk) BearbeitenHier sind wir uns nicht ganz schlüssig, wie der geforderte abstract aussehen sollte. Normalerweise ist das eine kurze Zusammenfassung eines bereits geschriebenen Artikels mit gebräuchlichen Vorgaben hinsichtlich der Struktur: Worum geht es, welche Methoden werden verwendet, wie sehen die Ergebnisse aus und was wird daraus gefolgert. Hier gibt es den fertigen Text jedoch noch gar nicht, sondern der abstract soll eher eine Art Bewerbung sein, den Text schreiben zu dürfen. Was scheint das bessere Vorgehen zu sein:
Unsere pragmatische Lösung: Wir reichen Version 2 ein, bieten aber zusätzlich einen Link auf einen "director's cut" an, der etwas umfangreicher ist als erlaubt. | ||
version 1 BearbeitenFor generations, scholars have built their research on what others had discovered and argued before. Just as well, they referenced their sources and published their own findings, thus augmenting the knowledge of mankind. Anyone could read about their results in academic journals, books, or their digital counterparts on the internet. Despite this (more or less) open access to information, it is hard for those outside the scientific realm to understand what scientific thinking and working means. For instance, when former German secretary of defense, Karl-Theodor zu Guttenberg, was proven guilty of plagiarizing others' work for his doctoral thesis, many interviewees in public inquiries did not attach great importance to this issue - "Didn't we all once cheat in school?" It seems that outside of the proverbial ivory tower, only few actually know what is going on inside. So, pursuing the idea of open science, there are popularized magazines, tv shows, science centers, and further initiatives which help to promote understanding of scientific results to the public. But these approaches - as well as science itself - often only deliver products, but do neither reveal the processes which led to their creation nor establish a connection to those who created them. People do not get to know what problems had to be solved, what failures had to be endured and what was learned from these. Omitting such issues may leave a distorted picture of science, which may in turn lead to misunderstanding. Certainly, these approaches broaden the perception of scholarly work, but they do not help the public to learn to think scientifically. In addition, the unidirectional flow of information from science to public does not include a feedback channel in the opposite direction. Open science 2.0 means that not only the products of science are promoted to the public, but that the public participates in scientific processes. Scientists and practitioners work together in transdisciplinary projects ("mode 2 of knowledge production") solving problems collaboratively. Thus, practitioners learn how to think scientifically by participating in scientific projects, and scientists learn from the practitioners' point of view. In order to facilitate such cooperation, it is necessary for scientists to open their scientific processes to the public. The web is an ideal environment for that. In this presentation, we show how web 2.0 applications can be used to implement open science 2.0 as described above. For instance, weblogs are used by scientists to reflect on their own experiences, to share new ideas, and to discuss scientific problems with the public. Wikis are used as lab notebooks, as platforms for preparing and reinforcing scientific presentations, and as environments for collaboratively writing scientific texts (as the one for this presentation, too). Twitter is used to share thoughts and to catch attention by promoting links to weblogs and wiki pages. Our arguments will be illustrated by many examples from the field of educational science and business studies. In addition, opportunities and threats of open science 2.0 will be discussed. |
version 2 BearbeitenPursuing the idea of open science, there are popularized magazines, tv shows, science centers, and further initiatives which help to promote understanding of scientific results to the public. But these approaches often only deliver products, but do neither reveal the processes which led to their creation nor establish a connection to those who created them. People do not get to know what problems had to be solved, what failures had to be endured and what was learned from these. Omitting such issues may leave a distorted picture of science, which may in turn lead to misunderstanding. Certainly, these approaches broaden the perception of scholarly work, but they do not help the public to learn to think scientifically. In addition, the unidirectional flow of information from science to public does not include a feedback channel in the opposite direction. Open science 2.0 means that not only the products of science are promoted to the public, but that the public participates in scientific processes. Scientists and practitioners work together in transdisciplinary projects ("mode 2 of knowledge production") solving problems collaboratively. Thus, practitioners learn how to think scientifically by participating in scientific projects, and scientists learn from the practitioners' point of view. In order to facilitate such cooperation, it is necessary for scientists to open their scientific processes to the public. The web is an ideal environment for that. In this presentation, we show how web 2.0 applications can be used to implement open science 2.0 as described above. For instance, weblogs are used by scientists to reflect on their own experiences, to share new ideas, and to discuss scientific problems with the public. Wikis are used as lab notebooks, as platforms for preparing and reinforcing scientific presentations, and as environments for collaboratively writing scientific texts (as the one for this presentation, too). Twitter is used to share thoughts and to catch attention by promoting links to weblogs and wiki pages. Our arguments will be illustrated by many examples from our experiences in the field of educational science and business studies. In addition, opportunities and threats of open science 2.0 will be discussed: What are the basic prerequisites to be met by the involved persons, what are the possible benefits and limitations of transdisciplinary research, and what impact does it have on the way scientists work? | |
Abstract (Director's Cut) BearbeitenFor generations, scholars have built their research on what others had discovered and argued before. Just as well, they referenced their sources and published their own findings, thus augmenting the knowledge of mankind. Anyone could read about their results in academic journals, books, or their digital counterparts on the internet. Despite this (more or less) open access to information, it is hard for those outside the scientific realm to understand what scientific thinking and working means. For instance, when former German secretary of defense, Karl-Theodor zu Guttenberg, was proven guilty of plagiarizing others' work for his doctoral thesis, many interviewees in public inquiries did not attach great importance to this issue - "Didn't we all once cheat in school?" It seems that outside of the proverbial ivory tower, only few actually know what is going on inside. So, pursuing the idea of open science, there are popularized magazines, tv shows, science centers, and further initiatives which help to promote understanding of scientific results to the public. But these approaches often only deliver products, but do neither reveal the processes which led to their creation nor establish a connection to those who created them. You can see the cake, but not the baking or the baker. People do not get to know what problems had to be solved, what failures had to be endured and what was learned from these. Omitting such issues may leave a distorted picture of science, which may in turn lead to misunderstanding. Certainly, these approaches broaden the perception of scholarly work, but they do not help the public to learn to think scientifically. In addition, the unidirectional flow of information from science to public does not include a feedback channel in the opposite direction. Open science 2.0 means that not only the products of science are promoted to the public, but that the public participates in scientific processes. Scientists and practitioners work together in transdisciplinary projects ("mode 2 of knowledge production") solving problems collaboratively. Thus, practitioners learn how to think scientifically by participating in scientific projects, and scientists learn from the practitioners' point of view. In order to facilitate such cooperation, it is necessary for scientists to open their scientific processes to the public. The web is an ideal environment for that. In this presentation, we show how web 2.0 applications can be used to implement open science 2.0 as described above. For instance, weblogs are used by scientists to reflect on their own experiences, to share new ideas, and to discuss scientific problems with the public. Wikis are used as lab notebooks, as platforms for preparing and reinforcing scientific presentations, and as environments for collaboratively writing scientific texts (as the one for this presentation, too). Twitter is used to share thoughts and to catch attention by promoting links to weblogs and wiki pages. Our arguments will be illustrated by many examples from our experiences in the field of educational science and business studies. In addition, opportunities and threats of open science 2.0 will be discussed: What are the basic prerequisites to be met by the involved persons, what are the possible benefits and limitations of transdisciplinary research, and what impact does it have on the way scientists work? Steinbruch BearbeitenHilfen BearbeitenZusammenfassung des Gutachter-Feedbacks Bearbeiten
Kontext BearbeitenDer Artikel wird verfasst für die Conference on Science and the Internet. Deadline für die Abstracts: 15. Januar 2012. Wäre natürlich cool, wenn wir dann schon fertig sind. :-) Ach so, ja: Englischsprachig muss er sein.
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