O'Really?

July 17, 2019

Educating Computer Scientists: What should we discuss at #SIGCSE journal club?

fightclub

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?

Computer Science (CS) is a young and professionally immature subject, it has only been taught at undergraduate level since 1965 in the UK. Across the pond in America, the Association for Computing Machinery (ACM) Special Interest Group on Computer Science Education (sigcse.org) only started as recently as 1968, making it a very spritely fifty years young. On educational timescales, computer science is a whipper snapper! Fifty years is peanuts when you compare it to the millennia that mathematics has been taught for. In ancient Greece the earliest lessons were mathematics hence μάθημα (mathematics) means the lesson and derivatives like μαθαίνω (matheno) mean to learn or to know. While the greeks built some impressive analogue computers, digital computers and computer science as we now know it, did not exist in Ancient Greece. 🇬🇷 

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

This short paper from Neil Brown at King’s College London and Greg Wilson of software carpentry fame, is part of the popular Public Library of Science (PLOS) Ten Simple Rules series. The tips capture some ongoing research in listicle format.

“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 closely 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.”

….and the second published in 2015:

“Research on the cognitive, educational, and policy dimensions of teaching computing is critical to achieving “computer literacy.”

Making CS Learning Visible: Case Studies on How Visibility of Student Work Supports a Community of Learners in CS Classrooms by Amber Solomon et al

This is a paper by Amber Solomon et al from the Innovation and Technology in Computer Science Education (ITiCSE) conference is about reducing defensive and competitive (macho?) cultures in Computer Science  (via Mark Guzdials blog).

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.

References and notes

*”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

June 23, 2017

Nine ideas for teaching Computing at School from the 2017 CAS conference

CAS

Delegates at the Computing at School conference 2017 #CASConf17 answering diagnostic questions, picture by Miles Berry.

The Computing At School (CAS) conference is an annual event for educators, mostly primary and secondary school teachers from the public and private sector in the UK. Now in its ninth year, it attracts over 300 delegates from across the UK and beyond to the University of Birmingham, see the brochure for details. One of the purposes of the conference is to give teachers new ideas to use in their classrooms to teach Computer Science and Computational Thinking. I went along for my first time (*blushes*) seeking ideas to use in an after school Code Club (ages 7-10) I’ve been running for a few years and also for approaches that undergraduate students in Computer Science (age 20+) at the University of Manchester could use in their final year Computer Science Education projects. So here are nine ideas (in random brain dump order) I’ll be putting to immediate use in clubs, classrooms, labs and lecture theatres:

  1. Linda Liukas demonstrated some intriguing ideas from her children’s books and HelloRuby.com that are based on Montessori education. I shall be trying some of these out (particularly the storytelling stuff) at code club to keep girls involved
  2. Sue Sentance and Neil Brown from King’s College London gave an overview of some current research in pedagogy.  They discussed research questions that can be tackled in the classroom like (for example) do learners make more progress using visual programming languages (like Scratch and Blockly) or traditional text-based languages (like Python and Java etc)? Many of these research questions would make good projects for undergraduate students to investigate in secondary schools, see research on frame based editors, for example.
  3. Michel Wermelinger from the Open University demonstrated using iPython notebooks for teaching data literacy at the Urban Data School. Although I’m familiar with iPython, it had never occurred to me to actually use iPython in school for teaching. It is a no-brainer, when you think about it, even for primary, because you have your code, inputs and outputs all in one window, and can step through code execution instead of (or as well as) using more conventional tools like Trinket, Thonny or IDLE. Data literacy is fun to teach.
  4. Miles Berry from the University of Roehampton demonstrated Diagnostic Questions in Project Quantum. These are a collection of high quality quizzes to use interactively for example as hinge questions, where teaching is adapted depending on answers given, like this multiple choice question:
    Consider the following Python code:
    
    a = 20
    b = 10
    a = b
    
    What are the values of a and b?
    
    A: a = 10, b = 10
    B: a = 20, b = 20
    C: a = 30, b = 10
    D: a = 10, b = 20
    

    You’ll have to try these five questions to check your answer. The useful thing here is that DiagnosticQuestions.com (the platform on which this is built) allows you to see lots of responses, for example each answer (A, B, C or D) above was selected by 25% of participants. You can also view explanations which illuminate common misconceptions (e.g. the classic mistake of confusing assignment with equality) as well as providing a bank of free questions for use in the classroom.

  5. Mark Guzdial from GeorgiaTech discussed using learning sciences to improve computing teaching. He demonstrated predictive questions (e.g. ask students What do you think will happen when we run this code? before actually executing it) alongside what he called subgoal labelling. These are simple ideas (with proven benefits) that can be put to use immediately. I’ll also be trying the Live Coding (with Sonic Pi) and Media Computation he demonstrated asap.
  6. Laurence Rogers demonstrated Insight: Mr. Bit  this looks like a good app for using BBC microbits in the classroom, connected to a range of sensors, provided you’ve got access to iPads.
  7. A copy of Hello World magazine was in the conference bag. The summer 2017 issue has an unusual article from Ian Benson from Kingston University and Jenny Cane describing their use of the Haskell programming language to teach 5-7 year olds to reason symbolically and learn algebra before arithmetic with help from Cuisenaire rods. The Scratch Maths project at University College London are doing similar things, building mathematical knowledge using Scratch, rather than Haskell. These are experimental ideas you could try out on unsuspecting (junior) family members.
  8. Lee Goss from Barefoot Computing, described the free CPD for primary school teachers on offer from BT. I’ve signed up and hope to plug some of the shortcomings in the Code Club Curriculum.
  9. Richard Jarvis demonstrated appJar, a handy Python library for teaching Graphical User Interfaces (GUIs). That’s Jar as in Jarvis and Jam, not JAR as in Java ARchive BTW. I’ve not tried GUIs at code club yet, but appJar looks like a good way to do it.

There were lots more people and projects at the conference not mentioned here including tonnes of workshops. If you’re interested in any of the above, the CAS conference will be back in 2018. Despite the challenging problems faced by Computer Science at GCSE level, it was reassuring and inspiring to meet some members of the vibrant, diverse and friendly community pushing the boundaries of computing in schools across the United Kingdom. Thanks again to everyone at CAS for putting on another great event, I will definitely consider attending next year and maybe you should too.

July 31, 2015

Wikipedia Science Conference @WellcomeTrust in London, September 2nd & 3rd 2015 #wikisci

There is growing interest in Wikipedia, Wikidata, Commons, and other Wikimedia projects as platforms for opening up the scientific process [1]. The first Wikipedia Science Conference will discuss activities in this area at the Wellcome Collection Conference Centre in London on the 2nd & 3rd September 2015. There will be keynote talks from Wendy Hall (@DameWendyDBE) and Peter Murray-Rust (@petermurrayrust) and many other presentations including:

  • Daniel Mietchen (@EvoMRI), National Institutes of Health: wikipedia and scholarly communication
  • Alex Bateman (@AlexBateman1), European Bioinformatics Institute: Using wikipedia to annotate scientific databases
  • Geoffrey Bilder (@GBilder), CrossRef, Using DOIs in wikipedia
  • Richard Pinch (@IMAMaths), Institute of Mathematics and its Applications. Wikimedia versus academia: a clash of cultures
  • Andy Mabbett (@PigsOnTheWing), Royal Society of Chemistry / ORCID. Wikipedia, Wikidata and more – How Can Scientists Help?
  • Darren Logan (@DarrenLogan), Wellcome Trust Sanger Institute, Using scientific databases to annotate wikipedia
  • Dario Taraborelli (@ReaderMeter), Wikimedia & Altmetrics, Citing as a public service
  • … and many more

I’ll be doing a talk on “Improving the troubled relationship between Scientists and Wikipedia” (see slides below) with help from John Byrne who has been a Wikipedian in Residence at the Royal Society and Cancer Research UK.

How much does finding out more about all this wiki-goodness cost? An absolute bargain at just £29 for two days – what’s not to like? Tickets are available on eventbrite, register now, while tickets are still available. 

References

  1. Misha Teplitskiy, Grace Lu, & Eamon Duede (2015). Amplifying the Impact of Open Access: Wikipedia and the Diffusion of
    Science Wikipedia Workshop at 9th International Conference on Web and Social Media (ICWSM), Oxford, UK arXiv: 1506.07608v1

March 4, 2014

CoderDojo, CodingDojo or CodeJo?

CC-BY licensed picture of a Hacker Dojo by Mitch Altman.

A dojo (or a dōjō) is an event where people train to perform a given task. So for example, software engineers organise code dojos to hone their skills in making software. The term has become widely adopted, so much so, that you’ll often find many flavours of dojo in your local area. In Manchester, there are at least three variants and these often get confused, usually by me. So here’s a quick explanation of what the different dojos do and how they are different.

CoderDojo: @coderdojo & @mcrcoderdojo etc

CoderDojo.com is an open source, volunteer led, global movement of free coding clubs for young people. You’ll find Coder Dojos all over the world, the Manchester Coder Dojo meets once a month in The Sharp Project, and like many coder dojos is very popular and frequently over-subscribed.

CodingDojo: @uomcodingdojo & @codingdojodotco

A group of students at the University of Manchester organise a Coding Dojo @uomcodingdojo see fb.com/uomcodingdojo. They practise problems in TopCoder and other puzzles [1-5] in order to compete in the ACM International Collegiate Programming Contest. They do this because it’s fun, improves their skill and prepares them for the kind’s of problems that are commonly found in a Coding Interviews  – a variant of the infamous Microsoft / Amazon / Google / Apple / Facebook / Twitter interviews. [6,7]

(The Manchester Coding Dojo are nothing to do with codingdojo.com  an outfit in Seattle and Silly Valley who claim to “teach you programming in 2 weeks” see @codingdojodotco.)

Codejo: @manc_codejo

The Manchester Codejo is monthly coding meetup in Manchester, where developers improve their skills by performing Katas – exercises designed to improve coding ability through repetition. So at their last meeting for example, Gemma Cameron @ruby_gem recently ran a Codejo session on the Class-responsibility-collaboration card at manchester.techhub.com.

In other words…

So @coderdojo ≠ @uomcodingdojo ≠ @manc_codejo ≠ @McrCoderDojo etc. Hope this clears up some confusion…

References

  1. http://en.wikipedia.org/wiki/Dining Philosophers
  2. http://en.wikipedia.org/wiki/Eight queens puzzle
  3. http://en.wikipedia.org/wiki/Tower of Hanoi
  4. http://en.wikipedia.org/wiki/Travelling salesman problem
  5. http://en.wikipedia.org/wiki/Two Generals’ problem
  6. McDowell, Gayle Laakman (2011) Cracking the Coding Interview: 150 Programming Questions and Solutions Career Cup ISBN:098478280X
  7. Poundstone, William (2013) Are You Smart Enough to Work at Google? Fiendish Puzzles And Impossible Interview Questions From The World’s Top Companies Oneworld Publications ISBN:1851689559

August 20, 2012

Digital Research 2012: September 10th-12th at St. Catherine’s College, Oxford, UK

The Radcliffe Camera, Oxford by chensiyuan

The Radcliffe Camera, Oxford by chensiyuan via wikipedia

The UK’s premier Digital Research community event is being held in Oxford 10-12 September 2012. Come along to showcase and share the latest in digital research practice – and set the agenda for tomorrow at Digital Research 2012. The conference features an exciting 3-day programme with a great set of invited speakers together with showcases of the work and vision of the Digital Research community. Here are some highlights of the programme – please see the website digital-research.oerc.ox.ac.uk for the full programme and registration information.

New Science of New Data Symposium and Innovation Showcase  on Monday 10th: Keynotes from Noshir Contractor [1] (Northwestern University) on Web Science, Nigel Shadbolt (Government Information Adviser) on Open Data and a closing address by Kieron O’Hara (computer scientist) – with twitter analytics, geolocated social media and web observatories in between. Also the launch of the Software Sustainability Institute’s Fellows programme and community workshops.

Future of Digital Research on Tuesday 11th: Keynotes from Stevan Harnad on “Digital Research: How and Why the Research Councils UK Open Access Policy Needs to Be Revised” [2], Jim Hendler (Rensselaer Polytechnic Institute) on “Broad Data” (not just big!), and Lizbeth Goodman (University College Dublin) on “SMART spaces by and for SMART people”. Sessions are themed on Open Science with a talk by Peter Murray-Rust, Smart Spaces as a Utility and future glimpses from the community, all culminating in a Roundtable discussion on the Future of Digital Research.

e–Infrastructure Forum and Innovation Showcase on Wednesday 12th opens with a dual-track community innovation showcase, then launch the UK e-Infrastructure Academic Community Forum where Peter Coveney (UK e-Infrastructure Leadership Council and University College London) will present the “state of the nation” followed by a Provider’s Panel, Software, Training and User’s Panel – an important and timely opportunity for the community to review current progress and determine what’s needed in the future.

There’s a lot more happening throughout the event, including an exciting “DevChallenge” hackathon run by DevCSI, software surgery by the Software Sustainability Institute (SSI) and multiple community workshops – plus the Digital Research 2012 dinner in College and a reception in the spectacular Museum of Natural History in Oxford. Digital Research 2012 is very grateful to everyone who has come together to make this event possible, including e-Research South, Open Knowledge Foundation, Web Science, the Digital Social Research programme, our Digital Economy colleagues and the All Hands Foundation.

We look forward to seeing you at Digital Research 2012 in Oxford in September.

References

  1. Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A.L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M. & (2009). Social Science: Computational Social Science, Science, 323 (5915) 723. DOI: 10.1126/science.1167742
  2. Stevan Harnad (2012). Open access: A green light for archiving, Nature, 487 (7407) 302. DOI: 10.1038/487302b

June 15, 2012

Alan Turing Centenary Conference, 22nd-25th June 2012

Alan Turing by Michael Dales

The Alan Turing statue at Bletchley Park. Creative commons licensed picture via Michael Dales on Flickr

Next weekend, a bunch of very distinguished computer scientists will rock up at the magnificent Manchester Town Hall for the Turing Centenary Conference in order to analyse the development of Computer ScienceArtificial Intelligence and Alan Turing’s legacy [1].

There’s an impressive and stellar speaker line-up including:

Tickets are not cheap at £450 for four days, but you can sign up for free public lectures by Jack Copeland on Turing: Pioneer of the Information Age and Roger Penrose on the problem of modelling a mathematical mind. Alternatively, if you can lend some time, the conference organisers are looking for volunteers to help out in return for a free conference pass. Contact Vicki Chamberlin for details if you’re interested.

References

  1. Chouard, T. (2012). Turing at 100: Legacy of a universal mind Nature, 482 (7386), 455-455 DOI: 10.1038/482455a see also nature.com/turing

May 24, 2012

Physics or Stamp Collecting? Let’s hear it for the Stamp Collectors

An old stamp collection by DigitalTribes on Flickr

Are you a Physicist or a Stamp Collector? Creative commons licensed image via DigitalTribes on Flickr.

The Life Scientific is a series of interviews by Jim Al-Khalili of high profile scientists. It’s a bit like Desert Island Discs without the music and with more interesting guests. If you missed them on the radio, you can download the lot as a podcast. Here’s a good example of an interview with John Sulston on the Physics vs. Stamp Collecting debate [1].

Jim Al-Khalili:

“There’s this wonderful, I’m sure you’ve heard it, Lord Rutherford’s tongue in cheek quote that all science is either physics or stamp collecting. Very rude, very insulting of course and it was applying to the way 19th Century naturalists would classify the world around them. What you were doing was a similar sort of thing but down at the level of individual cells.”

John Sulston:

“Yes I mean I am a stamp collector by that definition and I freely admit that, that’s why…”

Jim Al-Khalili:

“I don’t want to be insulting.”

John Sulston:

“No, no, no it’s not insulting in the least, I am a stamp collector but stamp collecting with a purpose, I don’t want to collect all stamps, I like collecting stamps that people are going to use. So I collect patterns perhaps is what I do. And I make maps that other people can use for their own work and that’s true of the cell, and it’s true of the genome, and I think that’s my role, I don’t think I’m a very intellectual person but I certainly can through a sort of obsession and loving of sort of completeness make a map that other people find valuable. Whereas other people previously had only done little tiny bits of it, which weren’t joined up, so I had to do the joining up, that’s very appealing to me. But it works – it wouldn’t work at all if you were off on your own – that’s why the stamp collector thing is used in a pejorative sense because it means somebody all by themselves just obsessively collecting stamps but if you bring a map out and it becomes the basis for a lot of other people’s work, like my maps have, then it’s entirely different.”

So let’s hear it for the stamp collectors, aka the “other scientists”. They no longer have to live in the shadow of Ernest Rutherford‘s jokey insult about their physics envy.

References

  1. Birks, J.B. (1962) Rutherford at Manchester OCLC:490736835
  2. Ihde, A. (1964). Rutherford at Manchester (Birks, J. B., ed.) Journal of Chemical Education, 41 (11) DOI: 10.1021/ed041pA896
  3. Birks, J., & Segrè, E. (1963). Rutherford at Manchester Physics Today, 16 (12) DOI: 10.1063/1.3050668
  4. Goldhammer, P. (1963). Rutherford at Manchester. J. B. Birks, Ed. Heywood, London, 1962; Benjamon, New York, 1963. x + 364 pp. Illus. $ 12.50 Science, 142 (3594), 943-944 DOI: 10.1126/science.142.3594.943-a

March 15, 2012

Be nice to nerds … you may end up working for them

Thought for the day: be nice to nerds because you might end of up working for them.

This sound advice comes from DARPA defector and newly appointed Googler Regina Dugan (see picture below).

Regina Dugan by Steve Jurvetson

What’s that you say? You’re not sure exactly what a nerd is? There are many definitions but the graphic below sums it up better than the Oxford English Dictionary ever could.

Are you a nerd, geek, dork or dweeb?

But beware! Many self-confessed nerds may actually be dorks, dweebs or geeks. It’s a grey area out there in the Venn of Nerdery, not quite as clear cut as the diagram above. To be sure of treating nerds right, you’ll need to be nice to dorks, dweebs and geeks too! See video for details…

[Creative Commons licensed picture of Regina Dugan at TED via Steve Jurvetson]

November 24, 2009

Semantic Web Applications and Tools for the Life Sciences (SWAT4LS) 2009, Amsterdam

Snow in Amsterdam by Bas van GaalenLast Friday, the Centrum Wiskunde & Informatica (CWI) in Amsterdam hosted a workshop called Semantic Web Applications and Tools for the Life Sciences (SWAT4LS) 2009.

Following on from last year [1], the workshop proceedings will be published at ceur-ws.org and in a special issue of the Journal of Biomedical Semantics, but if you want to find out what happened in the meantime, take a look at the #swat4ls2009 hashtag on twitter. Twitter makes bloggers lazy (they blog less but tweet more), but thankfully Nico Adams has studiously blogged the workshop very extensively.

Disruptive Technologies Director (cool job title!) Anita de Waard from Elsevier was asking what were the conclusions of the workshop. So here is an incomplete summary: Roughly speaking, people agreed to disagree (again). Keynote speaker Barend Mons argued that redundant data should be eliminated through the use of “nano-publications” and micro-attribution in his entertaining but controversial keynote. Some people in the audience disagreed with this. Greg Tyrelle thinks that redundancy is a feature, not a bug, in the Web and we have to deal with it. Alan Ruttenberg argued that semantic web reasoners  are required to clean up and sanity check all the messy and noisy biological data but emphasised the importance of Computer Scientists learning to speak Biologists language.

The good thing about this workshop is its size: small, friendly but internationally attended. Thanks to M. Scott Marshall, Albert Burger, Adrian Paschke, Paolo Romano and Andrea Splendiani for organising another good workshop, hope to see you again next year (if not before).

References

  1. Burger, A., Romano, P., Paschke, A., & Splendiani, A. (2009). Semantic Web Applications and Tools for Life Sciences, 2008 – Introduction BMC Bioinformatics, 10 (Suppl 10) DOI: 10.1186/1471-2105-10-S10-S1 part of the special issue on SWAT4LS 2008

[CC-licensed picture of Amsterdam in the snow by Bas van Gaalen]

September 4, 2009

XML training in Oxford

XML Summer School 2009The XML Summer School returns this year at St. Edmund Hall, Oxford from 20th-25th September 2009. As always, it’s packed with high quality technical training for every level of expertise, from the Hands-on Introduction for beginners through to special classes devoted to XQuery and XSLT, Semantic Technologies, Open Source Applications, Web 2.0, Web Services and Identity. The Summer School is also a rare opportunity to experience what life is like as a student in one of the world’s oldest university cities while enjoying a range of social events that are a part of the unique summer school experience.

This year, classes and sessions are taught and chaired by:

W3C XML 10th anniversaryThe Extensible Markup Language (XML) has been around for just over ten years, quickly and quietly finding its niche in many different areas of science and technology. It has been used in everything from modelling biochemical networks in systems biology [1], to electronic health records [2], scientific publishing, the provision of the PubMed service (which talks XML) [3] and many other areas. As a crude measure of its importance in biomedical science, PubMed currently has no fewer than 800 peer-reviewed publications on XML. It’s hard to imagine life without it. So whether you’re a complete novice looking to learn more about XML or a seasoned veteran wanting to improve your knowledge, register your place and find out more by visiting xmlsummerschool.com. I hope to see you there…

References

  1. Hucka, M. (2003). The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models Bioinformatics, 19 (4), 524-531 DOI: 10.1093/bioinformatics/btg015
  2. Bunduchi R, Williams R, Graham I, & Smart A (2006). XML-based clinical data standardisation in the National Health Service Scotland. Informatics in primary care, 14 (4) PMID: 17504574
  3. Sayers, E., Barrett, T., Benson, D., Bryant, S., Canese, K., Chetvernin, V., Church, D., DiCuccio, M., Edgar, R., Federhen, S., Feolo, M., Geer, L., Helmberg, W., Kapustin, Y., Landsman, D., Lipman, D., Madden, T., Maglott, D., Miller, V., Mizrachi, I., Ostell, J., Pruitt, K., Schuler, G., Sequeira, E., Sherry, S., Shumway, M., Sirotkin, K., Souvorov, A., Starchenko, G., Tatusova, T., Wagner, L., Yaschenko, E., & Ye, J. (2009). Database resources of the National Center for Biotechnology Information Nucleic Acids Research, 37 (Database) DOI: 10.1093/nar/gkn741
Next Page »

Blog at WordPress.com.