Why should students bother with open source software? Join us to discuss why via a viewpoint piece published by Diomidis Spinellis of Athens University and Delft University of Technology published in the July issue of Communications of the Association for Computing Machinery. [1] Here’s the introduction
Learning to program is—for many practical, historical, as well as some vacuous reasons—a rite of passage in probably all computer science, informatics, software engineering, and computer engineering courses. For many decades, this skill would reliably set computing graduates apart from their peers in other disciplines. In this Viewpoint, I argue that in the 21st century programming proficiency on its own is neither representative of the skills that the marketplace requires from computing graduates, nor does it offer the strong vocational qualifications it once did. Accordingly, I propose that computing students should be encouraged to contribute code to open source software projects through their curricular activities. I have been practicing and honing this approach for more than 15 years in a software engineering course where open source contributions are an assessed compulsory requirement. Based on this experience, I explain why the ability to make such contributions is the modern generalization of coding skills acquisition, outline what students can learn from such activities, describe how an open source contribution exercise is embedded in the course, and conclude with practices that have underpinned the assignment’s success
Spinellis, Diomidis (2021). “Why computing students should contribute to open source software projects”. Communications of the ACM. 64 (7): 36–38. DOI:10.1145/3437254
Wandering the Immeasurable: A sculpture at CERN by Gayle Hermick, picture re-used with permission from the artist
Even if you’re not a Physicist, there is plenty to see and do above and below ground at the European Organization for Nuclear Research (CERN). Home to the worlds largest experiment on what is arguably the worlds largest machine near Geneva in Switzerland, CERN is a very inspiring place to visit. Consequently, CERN and the Large Hadron Collider (LHC) feature in many guidebooks like The Geek Atlas [1], the Atlas Obscura, Lonely Planet and Tripadvisor.com. So what can you actually see and do at CERN?
Get a well paid engineering job. Good news for engineers, there are loads of jobs at CERN. What better way to explore a place than to work there? If you’re a student see careers.cern/students for details on summer internships and year long technical student programs. If you have already graduated, take a look at the CERN Fellowships and the doctoral student program. There are also plenty of opportunities for more experienced engineers described at careers.cern/professionals too. CERN’s mission is to “unite people from all over the world to push the frontiers of science and technology, for the benefit of all”. Part of that means providing opportunities for people from CERN’s 23 member states to learn new skills at CERN and take them back to their home country. For every research physicist at CERN, there are ten engineers. [2] To run their experiments, physicists rely on massive, novel and a very precise network of machines made with millions of parts, both moving and stationary. You need an army of engineers to build, test, run and develop such a complex machine, for example:
Mechanical engineers develop heating & cooling systems and mechatronics (there are quite a few robots at CERN)
Materials engineers test novel materials, metals, magnets, microscopes, superconductors, vacuums, X-ray diffraction and apply radiochemistry
Software and hardware engineers develop applications, virtualised infrastructure, distributed computing and databases using a wide range of programming and scripting languages. These applications manage data in one of the most highly demanding computing environments in the research world
Electrical and electronic engineers work on energy distribution, signal processing, microelectronics and radio frequency technology
Civil engineers and geotechnical engineers develop structures, roads, drainage, both above (and under) ground to accommodate all of the above
So CERN is full of engineers of every flavour. But if you’re not a physicist or an engineer looking for a job, there is still plenty to see and do. So let’s reboot our listicle again: seven things to do at CERN if you’re not a physicist, an engineer or job seeker:
Watch cosmic rays arrive from outer space: There are two permanent exhibitions which can be visited without booking and they both have free entry. One is housed in the aesthetically pleasing Globe of Science and Innovation (GoSI) and is called the Universe of Particles. Another is opposite the GoSI and called Microcosm. There’s plenty to see in both exhibits, including film projections, spark chambers showing cosmic rays and cloud chambers which allow you to visualise ionizing radiation.
Wander the Immeasurable with Gayle Hermick: Right outside the GoSI, sits an impressive sculpture made of 15 tonnes of twisted steel, stretched out over 37 metres in length and 11 metres up into the air. Covered in mathematical equations describing physical laws, the sculpture tells the story of Physics from Mesopotamia and Ancient Greece up to present day Higgs Boson and beyond. It’s a beautiful work of art to contemplate by Gayle Hermick. Having been inspired by equations the next thing you need to do is…
Crunch numbers using Einsteins famous equation: You can’t visit CERN without crunching some numbers. Many people will be familiar with Einsteins famous equation of mass–energy equivalence E=mc². What this means is that energy can be converted into mass (and vice versa) and the “exchange rate” (c²) is a very large number – the speed of light squared. So, you can turn a small about of mass into a HUGE amount of energy. Armed with your handy mass–energy calculator, you can crunch numbers, for example 1 kg = 90,000,000,000,000,000 Joules.
Thank the technology mothership: CERN is widely known as the the birthplace the Web, which we should all be thankful for. Many other technologies can trace their origin to CERN. Bent Stumpe and his colleagues developed the first touchscreens as early as 1973. [3,4] Cloud computing platforms such as Amazon Web Services, Google Cloud, Microsoft Azure have some of their roots in Grid Computing developed at CERN too. [5] Key pieces of widely used open-source software like Ceph and OpenStack have been co-developed at CERN. Where would we be without massive international collaborations? Find out more about how investment creates a positive impact on society through knowledge transfer, spin outs, startups and more at kt.cern. Many of these projects have an impact far beyond physics in areas such as medicine and consumer electronics. Thank you technology mothership. 🙏
Boggle at Big Data: Data speaks louder than words. Here is some random data for your mind to boggle on:
When switched on, some of the LHC detectors track up to 40 million events per second.
The LHC Grid computing generates 30 petabytes (10¹⁵ bytes) per year, with 300 petabytes of data permanently archived in its tape libraries as of October 2018.
The big loop underground is 27km long. Travelling very fast, close to the speed of light, a proton laps the circuit 11,000 times every second.
There are 100,000 scientists from over 100 countries working at CERN
More boggling can be done in the CERN data centre, especially the key facts and figures. [6] Anyone can explore and play with over two petabytes of Physics data at opendata.cern.ch
Contribute to the Grid: Talking of data, Physicists from all over the world work on data produced by the experiments. This requires supercomputers, very High Performance Computing (HPC) and Grid computing that no single machine can provide. This is why the Worldwide LHC Computing Grid (WLCG) exists. With the improvements of the LHC more and more computing power is required to crunch the data. Anyone can contribute by joining in the LHC@home project. Who knows? Maybe you can be a part of the discovery of the new mysterious particle or the proof that physicists have been struggling with for decades. CERN’s Grid builds on volunteered resources provided via the Berkeley Open Infrastructure for Network Computing (BOINC) middleware.
Book a free tour: While the two free permanent exhibitions require no booking, the free tours do and they offer much more. Tours are typically given by knowledgeable and enthusiastic staff. You can learn a lot from the permanent exhibitions, but a tour guide brings the place to life. Tours fill up quickly and provide access to restricted parts of CERN such as mission control, the ATLAS experiment, CMS cavern, synchro-cyclotron, the CERN data centre and more. [6] The cyclotron tells the story of CERN from 1957, when the first particle accelerator arrived in pieces on the back of a few lorries. Today it spans 27 km of France and Switzerland. How did that happen? Using lights and projectors, the exhibition brings the story to life in an illuminating way. At the time of writing, limited underground visits are possible as we are in the middle of the long shutdown 2 [7]. Tunnels are accessible but you’ll need to book a tour.
If you ever get the chance to visit.cern, it is well worth it. There is nowhere else quite like it. CERN is a truly inspiring place that demonstrates what can be achieved when thousands of people collaborate on a shared vision.
Acknowledgements
I’d like to thank current and former CERN technical students from the University of Manchester for their tours (both virtual and actual) of CERN and comments on drafts of this article: Raluca Cruceru, Simeon Tsvetankov, Iuliana Voinea, Grzegorz Jacenków, Boris Vasilev, Ciprian Tomoiagă, Nicole Morgan, Paul-Adrian Gafton, Joshua Dawes and Stefan Klikovits. Did I miss anything? Let me know in the comments or by email.
Thanks to Gayle Hermick for her permission to re-use the picture of her artwork in this piece.
DISCLAIMER: You can probably tell from reading the above that I am not a Physicist, unless you count a very rusty A-level from decades ago. Any factual errors in this article are the combined fault of me and my Physics teacher!
Did you know, CERN employs ten times more engineers and technicians than research physicists? home.cern/science/engineering Deadlines for applications are typically, end of January for summer internships and September and March for technical studentships, check careers.cern for details.
Bent Stumpe (2014) The ‘Touch Screen’ Revolution: 103–116. DOI: 10.1002/9783527687039.ch05 Chapter 5 of From Physics to Daily Life by Beatrice Bressan Wiley‐VCH Verlag GmbH & Co ISBN: 9783527332861
The first rule of journal club is, you do not talk about journal club. The second rule of journal club is, YOU DO NOT TALK ABOUT JOURNAL CLUB.* Discussions will go on as long as they have to. If this is your first time at journal club, you have to debate. Dress code: silly frocks and ridiculous hats are optional. Picture of my colleagues in the School of Computer Science ready for a graduation ceremony 2013, by Toby Howard.
So we’re starting a new Journal Club and Special Interest Group (SIG) for lecturers, teachers and course leaders in Manchester to discuss Computer Science Education (CSE). We’ll pick interesting papers, read them and then meet regularly to discuss them. It’s a bit like Fight Club but instead of beating each other up, we’ll “beat up” (review & critique) papers. Hopefully we’ll all learn something along the way. The first question to answer is, which papers should we discuss?
What this means is that there is plenty of evidence about what works (and what doesn’t) when teaching mathematics. In contrast, how to teach Computer Science, what should be taught and why, to whom and when are all open questions.
So, to get the ball rolling here are nine papers that tackle some of these open questions in Computer Science Education. We’ll vote on the three most interesting papers and read them before meeting to review them. Many of these papers are likely to be of interest to “educators” in its broadest sense. That means anyone teaching coding, computer science, tinkering, hacking and software/hardware engineering at any level.Which includes primary schools, code clubs, bootcamps, CoderDojos, hackathons, secondary schools, CPD programmes, K-12 education, lifelong learning, staff training courses, onboarding, induction, adult education programmes, return to work schemes and so on. If you’d like to join us we’ll be meeting in the Kilburn building, Manchester, M13 9PL (mosty likely first week of September, date and time tbc, drop me a line). Otherwise enjoy reading the insights below (DOI’s link to originals which may be behind a paywall, freely accessible versions are provided where available). Some papers are quite short, and have been selected for the topic they discuss rather than the quality of the content.
Twenty dirty tricks to train software engineers by Ray Dawson
A classic paper from Ray Dawson in the department of Computer Science at Loughborough University describing dirty tricks they use to introducing the frustrating realities of a software engineering development to students.
“Many employers find that graduates and sandwich students come to them poorly prepared for the every day problems encountered at the workplace. Although many university students undertake team projects at their institutions, an education environment has limitations that prevent the participants experiencing the full range of problems encountered in the real world. To overcome this, action was taken on courses at the Plessey Telecommunications company and Loughborough University to disrupt the students’ software development progress. These actions appear mean and vindictive, and are labeled ‘dirty tricks’ in this paper, but their value has been appreciated by both the students and their employers. The experiences and learning provided by twenty ‘dirty tricks’ are described and their contribution towards teaching essential workplace skills is identified. The feedback from both students and employers has been mostly informal but the universally favourable comments received give strong indications that the courses achieved their aim of preparing the students for the workplace. The paper identifies some limitations on the number and types of ‘dirty tricks’ that can be employed at a university and concludes that companies would benefit if such dirty tricks were employed in company graduate induction programmes as well as in university courses.”
Identifying student misconceptions of programming by Lisa Kaczmarczyk et al
This paper by Lisa Kaczmarczyk et al (formerly University of California, San Diego) recently came top of the ACM SIGCSE Top Ten Symposium Papers of All Time. In Lisa’s own words from the reinventing nerds podcast “The paper is sharing the results of a research study about misconceptions that novice computer science students have. Computer science is also a very abstract topic and the mistakes that students make are often baffling. The paper reports on the misconceptions that students have and why they have them. It’s important because this paper was the first to apply rigorous research methods to investigating misconceptions.” From the abstract:
“Computing educators are often baffled by the misconceptions that their CS1 students hold. We need to understand these misconceptions more clearly in order to help students form correct conceptions. This paper describes one stage in the development of a concept inventory for Computing Fundamentals: investigation of student misconceptions in a series of core CS1 topics previously identified as both important and difficult. Formal interviews with students revealed four distinct themes, each containing many interesting misconceptions. Three of those misconceptions are detailed in this paper: two misconceptions about memory models, and data assignment when primitives are declared. Individual misconceptions are related, but vary widely, thus providing excellent material to use in the development of the CI. In addition, CS1 instructors are provided immediate usable material for helping their students understand some difficult introductory concepts.”
Stride in BlueJ – Computing for All in an Educational IDE by Michael Kölling et al
This paper by Michael Kölling et al describes an Integrated Development Environment (IDE) that combines the best features of visual programming languages (blockly, scratch etc) with text-based programming (such as Python, Java, C etc) for use in BlueJ.org.
“In introductory programming teaching, block-based editors have become very popular because they offer a number of strong advantages for beginning programmers: They avoid many syntax errors, can display all available instructions for visual selection and encourage experimentation with little requirement for recall. Among proficient programmers, however, text-based systems are strongly
preferred due to several usability and productivity advantages for expert users. In this paper, we provide a comprehensive introduction to a novel editing paradigm, frame-based editing – including design, implementation, experimentation and analysis. We describe how the design of this paradigm combines many advantages of block-based and text-based systems, then we present and discuss an implementation of such a system for a new Java-like language called Stride, including the results of several evaluation studies. The resulting editing system has clear advantages for both novices and expert programmers: It improves program representation and error avoidance for beginners and can speed up program manipulation for experts. Stride can also serve as an ideal stepping stone from
block-based to text-based languages in an educational context.”
Kölling, Michael; Brown, Neil C. C.; Hamza, Hamza; McCall, Davin (2019). “Stride in BlueJ — Computing for All in an Educational IDE”: Proceeding SIGCSE ’19 Proceedings of the 50th ACM Technical Symposium on Computer Science Education 63–69. DOI:10.1145/3287324.3287462
Ten quick tips for teaching programming by Neil Brown and Greg Wilson
“Research from educational psychology suggests that teaching and learning are subject-specific activities: learning programming has a different set of challenges and techniques than learning physics or learning to read and write. Computing is a younger discipline than mathematics, physics, or biology, and while there have been correspondingly fewer studies of how best to teach it, there is a growing body of evidence about what works and what doesn’t. This paper presents 10 quick tips that should be the foundation of any teaching of programming, whether formal or informal.
These tips will be useful to anyone teaching programming at any level and to any audience.”
How to Involve Students in FOSS Projects by Heidi Ellis et al
Initiatives like Google Summer of Code (GSoC) and Git going in FOSS aim to get students involved in Free and Open Source Software (FOSS) projects, through paid work and online tutorials. Some courses use FOSS projects to teach software engineering, though these are fairly unusual. How can we get more students (and teachers) involved in FOSS projects? This paper by Heidi J. C. Ellis provides some guidance
“Software projects are frequently used to provide software engineering students with an understanding of the complexities of real-world software development. Free and Open Source Software (FOSS) projects provide a unique opportunity for student learning as projects are open and accessible and students are able to interact with an established professional community. However, many faculty members have little or no experience participating in an open source software project. In addition, faculty members may be reluctant to approach student learning within such a project due to concerns over time requirements, learning curve, the unpredictability of working with a “live” community, and more. This paper provides guidance to instructors desiring to involve students in open source projects.”
Ellis, Heidi J. C.; Hislop, Gregory W.; Chua, Mel; Dziallas, Sebastian (2011). “How to involve students in FOSS projects” Frontiers in Education Conference (FIE) DOI:10.1109/FIE.2011.6142994 (ironically, if there is an open access version of this paper, I can’t find it! Another nominee for the Open Access Irony Awards)
A methodology for using GitLab for software engineering learning analytics by Julio César Cortés Ríos et al
This paper by Julio César Cortés Ríos at the University of Manchester describes using GitLab to analyse and improve courses.
“To bridge the digital skills gap, we need to train more people in Software Engineering techniques. This paper reports on a project exploring the way students solve tasks using collaborative development platforms and version control systems, such as GitLab, to find patterns and evaluation metrics that can be used to improve the course content and reflect on the most common issues the students are facing. In this paper, we explore Learning Analytics approaches that can be used with GitLab and similar tools, and discuss the challenges raised when applying those approaches in Software Engineering Education, with the objective of building a pipeline that supports the full Learning Analytics cycle, from data extraction to data analysis. We focus in particular on the data anonymisation step of the proposed pipeline to explore the available alternatives to satisfy the data protection requirements when handling personal information in academic environments for research purposes.”
Scaling Introductory Courses Using Undergraduate Teaching Assistants
Teaching computer science to large classes requires typically requires armies of teaching assistants, demonstrators. Your TA’s need to know their stuff and should be able to deal with students in a fair and consistent way. This paper is a medley of opinions from Jeffrey Forbes at Duke University, David Malan from Harvard University, Heather Pon-Barry from Mt. Holyoke College, Stuart Reges from the University of Washington and Mehran Sahami from Stanford University.
“Undergraduates are widely used in support of Computer Science (CS) departments’ teaching missions as teaching assistants, peer mentors, section leaders, course assistants, and tutors. Those undergraduates engaged in teaching have the opportunity to deeply engage with CS concepts and develop key communication and social competencies. As enrollments surge, undergraduate teaching assistants (UTAs) play a larger role in student experience and outcomes. While faculty and graduate student instructional support does not necessarily increase with the number of students in our courses, the number of qualified undergraduate teaching assistants for introductory CS courses should scale with the number of students in our courses. With large courses, the significance of the UTAs’ role in students’ learning likely also increases. Students have relatively little interaction with the instructor, and faculty may have more challenges monitoring and supporting individual UTAs. UTAs have a major role in affecting climate in computer science courses. The climate in large courses has substantial implications for students from groups traditionally underrepresented in computing. This panel will discuss how undergraduate teaching assistants can serve as a scalable effective teaching resource that benefits both the students in the course and the UTAs themselves.”
What Are We Doing When We Teach Computing & Programming by Sally Fincher
Two related papers by Sally Fincher at the University of Kent, the first published in 1999…
“The academic discipline of computer science uniquely prepares students for future study by teaching the fundamental construct of its practice-programming- before anything else. The disciplinary argument seems to run that if a student is not versed in the practicalities, then they cannot appreciate the underlying concepts of the discipline. This may be true. However an analogous simulation would be if it were thought necessary for architecture students to be taught bricklaying before they could appreciate the fundamentals of building design. This argument is clearly flawed when compared to endeavours such as the study of English Literature, which makes no claim to teach the practice of producing work before the study of the products of others work. It is possible that this is an argument of disciplinary maturity-that all disciplines have passed through a similar phase. This paper examines the emergent approaches being defined, all of which address the central concern of the teaching of programming and its relationship to the learning of computer science. It examines: the “syntax-free” approach of Richard Bornat and Russel Shackelford, the “problem-solving” approach of David Barnes (et al.), the “literacy” approach of Peter Juliff and Owen Astrachan and the “computation-as-interaction” approach of Lynn Andrea Stein. These approaches are discussed both in their own terms, and also placed in a preliminary taxonomic framework for the teaching of programming.”
Modern learning theories emphasize the critical social aspect of learning. Computer science (CS) classrooms often have “defensive climates” that inhibit social learning and prevent the development of a community of learners. We believe that we can improve the social context of computer science learning by expanding CS learning beyond the single student in front of a display screen. Our theory is that the single student and single display inhibits collaboration and collaborative awareness of student work. In this paper, we present two case studies where we explored ways to make student work visible to peers. The first case study involved using a studio model for learning enabled by projection-based Augmented Reality (AR), and the second case study involves using a maker-oriented curriculum to make student work visible. Findings suggest the visibility of student work in CS classrooms helped support a community of learners: students collaborated, used each other as sources of inspiration, and felt more comfortable asking for help.
*”You do not talk about Journal Club” is an adapted quote from the 1999 film Fight Club, see below. I’m only joking, you are of course welcome to talk to anyone who will listen about Journal Club.
Talking of David Malan, you can see his talk on making CS50 scale when he visited Manchester in 2017
Alan Turing Binary code, Shoreditch High Street, London by Chris Beckett on Flickr (CC-BY-NC-ND license)
Over at democracy corner, Manchester Digital is interviewing all of its elected council members. Somehow, I got volunteered to be first interviewee. Here’s my two pence on one of the questions asked: “What do you think is biggest challenge we face as an industry?” (with some extra links)
Firstly, coding and “computational thinking” [1], needs to be understood as something that isn’t just for developers, geeks, coders, techies, boffins or “whizz kids” – as the Manchester Evening News likes to call them. Computational thinking, the ability to understand problems and provide innovative solutions in software and hardware, is a fundamental skill that everyone can learn, starting in primary school. As well as being fun to learn and practice, it is a crucial skill in a wide range of organisations in digital and beyond. Thankfully, the new computing curriculum in UK schools has recognised and addressed this, but it remains to be seen what the long-term impact of the changes in primary & secondary education will be on employers.
Secondly, as an industry, both the digital and technology sectors are seriously hindered by gender imbalance. If only 10-20% of employees are female, then large numbers of talented people are being excluded from the sector – bad news for everyone.
Is that reasonable – or have I missed the point? Are there more pressing issues facing the technology sector? Either way, you can read the rest of the interview at manchesterdigital.com/democracy-corner which will be supplemented with more interviews of council members every week over the next few months.
References
Wing, J. (2008). Computational thinking and thinking about computing Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 366 (1881), 3717-3725 DOI: 10.1098/rsta.2008.0118
Three kinds of Software: Enthusiast, Enterprise & Consumer by Aral Balkan
It’s getting pretty hard to do anything these days that doesn’t involve software. Our governments, businesses, laboratories, personal lives and entertainment would look very different without the software that makes them tick. How can we classify all this software to make sense of it all? The likes of this huge list of software categories on wikipedia are pretty bewildering, and projects such as the Software Ontology (SWO) [1] are attempting to make sense of swathes of software too. There’s lots of software out there.
Aral Balkan, one of the people behind the Indie Phone, has proposed a simpler classification which will appeal to many people. In his classification, there are three kinds of software (see picture top right), as follows:
Enthusiast software: like a classic car. We tinker with enthusiast software, in the same way motoring enthusiasts tinker with their classic cars. To the enthusiast, it is a joy when the software breaks, because that’s part of the fun, fixing it and getting it back on the road. However, you wouldn’t drive your classic car during your day job, or commute to work. Like a classic car, enthusiast software, is largely for weekends and evenings only. Raspberry Pi software is a classic example of enthusiast software made in garages by hobbyists.
Enterprise software: like a juggernaut truck. We use enterprise software, because our employers mandate that we do so. It might not be fun to drive, or work particularly quickly, but enterprise software is often a necessary evil to get work done on an industrial scale. Cynics will tell you enterprisey software is slow because the engineers have:
Cynics will also tell you, enterprise software has been made by architecture astronauts, purchased by clueless decision-makers who don’t have actually have to use the software themselves, but have been hoodwinked in notorious“vendor meetings” which could explain the unpopularity of some enterprise software. But that’s another story…
Consumer software: like a family saloon car. We rely on consumer software to get the job done, it is purely functional, does the job in a reliable (and boring) way on a daily basis, just like the vehicle you commute in. Consumer software can be found on your mobile phone and most consumer software is Application Software aka “Apps”.
I came across Aral’s classification at Wuthering Bytes last summer, a small and friendly festival of technology in the Pennines. Wuthering Bytes is running again next month, August 15th -17th and is well worth attending if you’re in the North of England and fancy having your bytes wuthered [2]. It’s a great mix of talks by the likes of Sophie Wilson and many others combined with hands-on activities in beautiful Happy-Hippy-Hacky Hebden Bridge for a bargain £10 per day. It’s software (and hardware) for enthusiasts (not enterprises or consumers). What’s not to like?
References
Malone, J., Brown, A., Lister, A., Ison, J., Hull, D., Parkinson, H., & Stevens, R. (2014). The Software Ontology (SWO): a resource for reproducibility in biomedical data analysis, curation and digital preservation Journal of Biomedical Semantics, 5 (1) DOI: 10.1186/2041-1480-5-25
Writing good code is often harder than it looks via Randall Munroe at xkcd.com
Manchester Digital is the independent trade association for the thriving digital sector in the North West of England. Last night they held their AGM and elections for new members of their council. I was encouraged to stand for election, and alongside 19 other candidates, had to give a two-minute “manifesto” in a husting / lightning-talk format. Here’s roughly what I said, from the perspective of software, hardware and developers, with some added links and a bit more polish:
The success of Manchester’s Digital economy is dependent on educating, recruiting and training a pool of talented developers to work in the region. As identified in the Manchester Digital skills audit,developers are often the hardest roles to fill, as many graduates and potential employees are drawn to other high-tech hubs like London, Silicon Fen and Silicon Valley, California for employment.
Addressing this issue is an important for Manchester Digital and requires closer collaboration between Higher education, Secondary education and employers. As a tutor at the University of Manchester, with responsibility for managing internships for students in Computer Science I am in a strong position to enable more collaboration between educators and employers. As a council member I would do this in four ways:
Encouraging students to consider employment in Manchester as their first job, by promoting internships and graduate vacancies with local organisations alongside traditional graduate programmes at larger multinational companies
These are key activities that will enable the continued success of Manchester’s Digital Economy and I ask Manchester Digital members to vote for me if they agree. Thank you!
Whatever the outcome, the AGM & hustings were great fun and it was good to catchup with old friends and meet some new people too. Hope to see some of you again the Manchester Digital BBQ on 11th July…
If you’ve built a personal library of scientific papers in Mendeley, you won’t just want to delete all the data, you’ll need to export your library first, delete your account and then import it into a different tool.
Disclaimer: I’m not advocating that you delete your mendeley account (aka #mendelete), just that if you do decide to, here’s how to do it, and some alternatives to consider. Update April 2013, it wasn’t just a rumour.
Exporting your Mendeley library
Open up Mendeley Desktop, on the File menu select Export. You have a choice of three export formats:
It is probably best to create a backup in all three formats just in case as this will give you more options for importing into whatever you replace Mendeley with. Another possibility is to use the Mendeley API to export your data which will give you more control over how and what you export, or trawl through the Mendeley forums for alternatives. [update: see also comments below from William Gunn on exporting via your local SQLite cache]
Deleting your Mendeley account #mendelete
Login to Mendeley.com, click on the My Account button (top right), Select Account details from the drop down menu and scroll down to the bottom of the page and click on the link delete your account. You’ll be see a message We’re sorry you want to go, but if you must… which you can either cancel or select Delete my account and all my data. [update]To completely delete your account you’ll need to send an email to privacy at mendeley dot com. (Thanks P.Chris for pointing this out in the comments below)
Alternatives to Mendeley
Once you have exported your data, you’ll need an alternative to import your data into. Fortunately, there are quite a few to choose from [3], some of which are shown in the list below. This is not a comprehensive list, so please add suggestions below in the comments if I missed any obvious ones. Wikipedia has an extensive article which compares all the different reference management software which is quite handy (if slightly bewildering). Otherwise you might consider trying the following software:
Citeulike.org, a web-based application owned by Springer, [update: citeulike is not owned by Springer, although they have sponsored them in the past] see also @citeulike
Papers, also owned by Springer and available on other platforms besides Mac, see also @papersapp
One last alternative, if you are fed up with trying to manage all those clunky pdf files, you could just switch to Google Scholar which is getting better all the time. If you decide that Mendeley isn’t your cup of tea, now might be a good time to investigate some alternatives, there are plenty of good candidates to choose from. But beware, you may run from the arms of one large publisher (Elsevier) into the arms of another (Springer or Macmillan which own Papers and ReadCube respectively).
Van Noorden, R. (2013). Mathematicians aim to take publishers out of publishing Nature DOI: 10.1038/nature.2013.12243
Hull, D., Pettifer, S., & Kell, D. (2008). Defrosting the Digital Library: Bibliographic Tools for the Next Generation Web PLoS Computational Biology, 4 (10) DOI: 10.1371/journal.pcbi.1000204
Attwood, T., Kell, D., McDermott, P., Marsh, J., Pettifer, S., & Thorne, D. (2010). Utopia documents: linking scholarly literature with research data Bioinformatics, 26 (18) DOI: 10.1093/bioinformatics/btq383
The Software Sustainability Institute www.software.ac.uk has launched a Fellowship programme that recognises outstanding UK-based researchers who use software. The Fellowships come with £3000 funding which can be used for travel, collaboration and running events.
Fellows advise the Institute on important software, evangelise software practices and champion the adoption of best-of-breed software. Fellows will contribute to the software blog, and are supported in advertising their own research.
A Fellowship Launch event will be held at the Digital Research 2012 in Oxford on 10th September 2012. Attendees at the launch event will receive free entry to the conference on 10 September and, if they choose to stay on, a 50% reduced fee for the rest of the conference. Applicants to the Fellowship Programme put themselves in an advantageous position if they have attended the workshop.
Who should apply
The SSI is seeking fifteen outstanding researchers at different stages in their career, from PhDs to Professors, and from a wide range of research disciplines in science, technology and engineering. Successful Fellows will have a demonstrable knowledge and visibility in their community and have excellent communication skills.
Funding
The £3000 funding is flexible and can be used for travel to conferences, setting up and running workshops, starting new collaborations or hosting/teaching at Software Carpentry training events.
Application details
The Software Sustainability Institute is a national facility that helps researchers and developers to build and use better research software.
The closing date for applications is Thursday 20 September 2012 at 5pm.
Fellowships last eighteen months and are available from the 1st of January 2012 through the 30th of June 2014.
Successful recipients of the Software Sustainability Institute’s Fellowships will be announced in November 2012.
Questions?
If you have any questions, please contact the Institute: info@software.ac.uk.
MEDIE is an “intelligent” semantic search engine that retrieves biomedical correlations from over 14 million articles in MEDLINE. You can find abstracts and sentences in MEDLINE by specifying the semantics of correlations; for example, What activates tumour suppressor protein p53? So just how useful is MEDIE and is it at the cutting edge?
At the Manchester Interdisciplinary Biocentre (MIB) launch yesterday, Professor Jun’ichi Tsujii gave a presentation on Linking text with knowledge – challenges for Text Mining in Biology. As part of this presentation he gave a demonstration of Medie: an intelligent search engine for Medline. This tool looks quite impressive if you experiment with some sample queries. I wonder what nodalpointers, especially hardened text-miners, natural language processing (NLP) nerds and computational linguists, make of Medie?
O'Really? 