- Big Data (6)
- Classlist (3)
- Crowdsourcing (1)
- Data Mining (3)
- Dataset Lists (1)
- Interviews (1)
- Jane Goodall (1)
- Knowledge Management (1)
- Logistics (1)
- Natural Language Processing (2)
- Paper versus Screens (1)
- Poetry (1)
- Project Ideas (7)
- Reproducibility (2)
- Research Paradigms (2)
- Research Surveys (3)
- Science (15)
- Scientific Articles (9)
- Search Engine Optimization (3)
- Security (1)
- Sport Metrics (2)
- Web Analytics (1)
Also check out the sister blog >>> http://researchmethodslinks.blogspot.ie/
Friday, November 9, 2012
Saturday, October 13, 2012
A tool for Twitter community visualisation, the Twitter Archiving Google Spreadsheet (TAGS), this new version has some coding improvements and new features including a dashboard summary and advanced tools for getting user profile information and friend/follower relationships for social network analysis.
You can get a copy by selecting the link below:
Thursday, October 11, 2012
Causation vs. correlation
How do you know if a study’s results answer the question it set out to ask? Sometimes an outcome is just a coincidence—there’s a correlation but no causation. Meta-analyses pool the results of smaller studies and filter signal from that kind of noise.
True size of the effect
Watch out for weasely language—a “threefold increase” might only be a shift from 1 percent to 3 percent. One recent paper reported that women’s mortality risk rose 133 percent. That sounds scary, but the elevated mortality rate was still just 1.9 percent.
Look at two key factors, the n and the p. The n is the number of subjects used in the study. Multifaceted experiments typically have fewer subjects than simple surveys. Genetics studies need a big n. The p value lets you know whether the result is “statistically significant”—it’s the probability of something occurring by chance alone. You want to see a p of less than 0.05. (Results can be statistically significant and still only show correlation, or have confounding factors.)
Conflicts of interest
Most journals now note this as a matter of policy. Was the company making the drug or product associated with the laboratory that did the study? Are any of the authors trying to sell a product? For example, the authors of a study exploring the effectiveness of “brain training” techniques on cognitive enhancement worked for the company that developed (and sold) those techniques. They disclosed this, but that’s still a red flag.
Wednesday, October 10, 2012
- Where do you start a big data project? Skunk works projects were a popular route and then those groups evolved to become dozens of employees and petabytes of data. Other options included the underserved business unit. Some companies had business leaders as sponsors.
- Leaders will have to take a few chances on big data projects. Translation: Trust your people, spend some money and take the leap.
- Use cases for big data abound. Among the possibilities:
- Network optimization.
- Fraud detection.
- Seeing what the customer experiences.
- Healthcare simulations.
- Consumer focused marketing efforts require more social networking analysis and predictive capabilities. Consumer data is inherently unstructured.
- Travel and expense management to make intelligent decisions about costs. For instance, a company could notice it is sending too many people to one conference with aggregated data across 200,000 employees.
- Marketing support and tracking of attrition rates in a subscriber-based business.
- Closer ties between partners and suppliers via collaborative data and insight sharing.
- Christine Twiford, Manager, Network Technology Solutions at T-Mobile, said analytics gave the wireless provider confidence that it could offer an unlimited data plan without crushing the network.
- Analytics and business intelligence are bridging into big data applications. Historical data from years back has been usable, said Michael Cavaretta, Technical Leader, Predictive Analytics & Data Mining at Ford. In the future, Cavaretta said Ford will focus on data from the vehicle, but the real win may be the stream of information through the manufacturing process.
- The big data Petri dish will be the healthcare industry. "There's a lot of incentive out there to use big data to improve healthcare," said Katrina Montinola, Vice President of Engineering at Archimedes.
- Facebook is another big data Petri dish. Facebook could use big data techniques to make more money---while treading carefully on privacy. Conversely, Facebook is a huge data set by definition. After all, one billion users are sharing gobs of data. Facebook data could "provide an X-ray view" of what's going on in a customer's head. Companies could optimize that data to improve experience. Montinola said that Facebook would provide an ideal population for clinical trials. Skytland said Facebook could be "an amazing platform for collective action."
- "Big data is the oil of the information age," said Nicholas Skytland, Program Manager, Open Government Initiative.
- Shared analytics services are commonly used as a way to harness big data and blend in predictive techniques.
- Storage will be an ongoing big data issue because data scientists are pack rats---even hoarders---but there's a budget limit. T-Mobile can only keep 10 days of its clickstream data, said Twiford, who noted the company is trying to process more information in flight. Storage limitations will result in sampling.
- As for data sampling, data scientists will ultimately make the call on what information is hoarded and what's sampled.
- Data scientists will be in high demand and serve as investigators that test hypotheses. Data scientists will be paired with business domain experts. What's unclear is how many of these data wonks you need. In many respects, we'll all be data scientists to some degree---or at least data literate. Twiford said there's a talent challenge. There's also a challenge in recruiting big data talent and companies should look beyond Silicon Valley.
- Big data talent is tough to find. One company appointed internal people with business knowledge and supplement with a partner who had statistic and analytics wonks available (consultants). The long-term talent strategy for this company is to recruit heavily from universities to build an analytic employee pool. Talent has to be able to use data.
- Visualization tools and crowdsourcing may alleviate the big data talent crunch, said Skytland. Perhaps "citizen scientists" will bridge the gap, said Skytland. Visualization tools can bring big data to the masses.
- Universities and retraining will also bridge the big data talent gap.
- Too much time is being spent preparing big data and not enough actually analyzing it. Discovery and decision-making is being short-changed for preparation. Data preparation should be automated.
- When pitching big data to business leaders you need to start with this question: What business questions need to be answered?
- Most corporate big data projects are in their infancy. As a result, many are looking to combine data warehouse information with other data to be prescriptive. One company was looking to build a data warehouse on steroids.
- Partner with companies that can provide visualization tools via APIs. Of course, you have to liberate your data and open it up first, said Skytland.
- NASA is planning missions that will collect 24 terabytes of data a day. "We want to make sense of that data and actually navigate it," Skytland.
- There are thousands of silos in corporate America and sharing data is the biggest challenges. Big data could be a way to bridge those corporate silos.
- Big data applications are rolling first at business to consumer questions because they tie together experience, sales and analytics. Social media and multiple channels also mean that companies need to look for patterns in streaming data, said James Kobielus, IBM's big data evangelist.
- Hadoop clusters are surfacing everywhere in corporate America. If 2012 was the year of enterprise Hadoop pilots, 2013 will a ramp of usage.
- NASA initially created its own big data systems, but is using more commercial applications ranging from Amazon Web Services and a cloud infrastructure.
- Big data isn't new, but now has reached critical mass as people digitize their lives. "People are walking sensors," said Skytland.
- Social media is hyped in big data applications, but the diary of consumers' lives is great market intelligence. Chief marketing officers are pushing social media and big data projects. Cavaretta said Ford is using social data because it goes beyond what consumers provide in surveys and "represents what they are thinking."
- IT practitioners said that they wanted the largest data sets possible. The idea is that companies wouldn't have to rely on samples. However, there's a business challenge in determining what information is worth keeping and what should head to the archive or tossed.
- Making archived data usable for big data projects is going to be a running challenge.
- Governments and the ability to provide datasets can create entire industries. Under this theory, governments will essentially be data providers as one of its primary functions.
- Twiford said that T-Mobile is using big data techniques to learn more about the preferences of no-contract customers, which don't offer as much profile information as contract ones.
- Data analytics as a service and data visualization as a service will become commonplace. Third party vendors will move toward big data as a service to make it consumable for the masses. Tech vendors to go this route are likely the big market share leaders today (IBM, SAP, Oracle, Salesforce.com).
Sunday, October 7, 2012
WHAT am I? Ah, you know it,
I am the modern Sage,
Seer, savant, merchant, poet—
I am, in brief, the Age.
Look not upon my glory
Of gold and sandal‐wood,
But sit and hear a story
From Darwin and from Buddh.
Count not my Indian treasures,
All wrought in curious shapes,
My labours and my pleasures,
My peacocks and my apes;
For when you ask me riddles,
And when I answer each,
Until my fifes and fiddles
Burst in and drown our speech,
Oh then your soul astonished
Must surely faint and fail,
Unless, by me admonished,
You hear our wondrous tale.
We were a soft Amœba
In ages past and gone,
Ere you were Queen Of Sheba,
And I King Solomon.
We lived in happy sloth,
And all that you did I did,
One dinner nourished both:
Till you incurred the odium
Of fission and divorce—
A severed pseudopodium
You strayed your lonely course.
When next we met together
Our cycles to fulfil,
Each was a bag of leather,
With stomach and with gill.
But our Ascidian morals
Recalled that old mischance,
And we avoided quarrels
By separate maintenance.
Long ages passed—our wishes
Were fetterless and free,
For we were jolly fishes,
A‐swimming in the sea.
We roamed by groves of coral,
We watched the youngsters play—
The memory and the moral
Had vanished quite away.
Next, each became a reptile,
With fangs to sting and slay;
No wiser ever crept, I’ll
Assert, deny who may.
But now, disdaining trammels
Of scale and limbless coil,
Through every grade of mammals
We passed with upward toil.
Till, anthropoid and wary
Appeared the parent ape,
And soon we grew less hairy,
And soon began to drape.
So, from that soft Amœba,
In ages past and gone,
You’ve grown the Queen of Sheba,
And I King Solomon.
Tuesday, September 11, 2012
John Kelleher recommends the "In Our Time" podcast series. The Science Archive is available online at: http://www.bbc.co.uk/radio4/features/in-our-time/archive/science
Highly recommeded are:
Baconian Science http://www.bbc.co.uk/programmes/b00jdb6c Karl Popper http://www.bbc.co.uk/programmes/b00773y4 The Scientific Method http://www.bbc.co.uk/programmes/b01b1ljm The Scientist http://www.bbc.co.uk/programmes/p00548jq
Monday, September 10, 2012
Monday, June 18, 2012
Over at Understanding Science, a team of UC Berkeley researchers, teachers, designers and web experts has assembled a fantastic list of some common misconceptions about science and how it works. It's a great overview of what science is and what science isn't, and definitely warrants a look (along with the rest of the Understanding Science website — a truly fantastic resource). We've included a few misinterpretations, along with their explanations, below. But you'll want to click through to the full guide.
MORE HERE >>>
Monday, May 28, 2012
- Each student has been allocated a maximum of 20 minutes.
- The 20 minutes will cover the presentation and the discussion/questions time.
- You will have a maximum of 12 minutes for your presentation. So practice to make sure you can say all that you want to say in the 12 minutes.
- You will be given feedback at the end. The feedback will fall into one of three outcomes. 1. Yes you can proceed to start your dissertation. 2. make the following changes by next week and you can proceed. 3. Your proposal & project idea is not ready yet. Keep developing it and you might be able to start in Sept.
- Please turn up 10 minutes early and wait outside the room. We will come out and let you know when you can come into the room
- Email me (brendan.tierney at dit dot ie) your presentation 2 hours before your presentation time. This will allow me to have your presentation open when you come into the room and we dont have to waste time on plugging in USB keys etc
Sunday, May 27, 2012
30th May 2012 12:00 Vincent McKenna, DT217A 30th May 2012 12:20 Andrej Bartko, DT230 30th May 2012 12:40 Robert Huczek, DT217A 30th May 2012 13:00 John Brogan, DT217 30th May 2012 13:20 Christina Shannon, DT217
30th May 2012 14:00 Chenje Cao, DT285 30th May 2012 14:20 Raj Kumar, DT286 30th May 2012 14:40 Brendan Cregan, DT230
30th May 2012 16:00 Jelena Haiduroua, DT230 30th May 2012 16:20 Garrett Duffy, DT286 30th May 2012 16:40 Liam Carey, DT217 30th May 2012 17:00 Tair Kuanyshev, DT285 30th May 2012 17:20 Lira Maricar Mariano, DT285
31st May 2012 10:20 Frank Kendlin, DT285 31st May 2012 10:40 Fatima Emmanuel, DT286 31st May 2012 11:00 Niall Dowdall, DT210 31st May 2012 11:20 David Marvroudis, DT285
31st May 2012 12:00 Victor Aduba, DT286 31st May 2012 12:20 Eloho Egivuferai, DT217A 31st May 2012 12:40 Olu Folarin, DT286
31st May 2012 14:00 Edward Robert Freyne, DT286 31st May 2012 14:20 Eamonn O'Brien, DT230 31st May 2012 14:40 Prasanth Joseph, DT286 31st May 2012 15:00 Thomas Bryne, DT285
6th June 2012 15:20 Gabriel Lawless, DT202A
11th June 2012 11:00 Leah Moriarty, DT217A 11th June 2012 11:20 Keith Ellman, DT285 11th June 2012 11:40 Liyi Wei, DT217A 11th June 2012 12:10 Marcus McQuiston, DT217
Tuesday, May 15, 2012
There might be some Data Analytics type dissertation projects using the methods covered in this article.
Saturday, April 21, 2012
Monday, April 16, 2012
Flustered pundits claim that blogging has changed writing forever, but they're wrong. You know what has really changed writing? Google search. Thousands of internet puppies are writing "content" that is perfectly optimized to rise to the top of search rankings. Search engine optimization (SEO) has become its own art, a genre designed to make writing algorithm-friendly and human-clickable. What has SEO done to our writing? Now Sean Gallagher over at Ars Technica has a smart, funny article about a new piece of consumer software, InboundWriter, which helps you turn any piece of writing into something that's optimized for search. The best part is that Gallagher actually ran his own article through InboundWriter, so his analysis of SEO is actually designed to be 99% optimized for SEO.
MORE HERE >>>
Monday, March 5, 2012
The BBC website provides advice on how to get the most out of the accessibility features and assistive technologies available for your computer, so that you can use the web in a more accessible way. Includes "how to" guides for people with vision and hearing disabilities.
Monday, February 27, 2012
Damian Gordon's MSc Project Ideas -- Software Development:
Also how about creating 3D representations of Escher prints, like this one for Picasso:
Friday, February 17, 2012
12th December 2011 by Ingo Frost, Kathrin Frank
The authors of this article go to the question of how organizations in 2020 to deal with knowledge. For this they have analyzed in a first step, national and international knowledge management conferences, publications and Internet publications to locate knowledge management visionaries. There are four visionaries are noticed because of your keynotes and their publications on knowledge management trends: David Griffiths, Dave Snowden, David Gurteen and Norbert Gronau. They are presented here together with their theories and visions for dealing with knowledge. At the end of these theories are compared and discussed.
How to find the interesting theories about how knowledge management could evolve?
One way to come closer to this question is to examine knowledge management conferences and find out who has kept the keynotes to knowledge management developments. These nationally and internationally significant knowledge management conferences, the keynotes were considered from the years 2010 and 2011. Of the 105 keynotes 10 authors have explicitly addressed by knowledge management trends. The work of these authors has been examined in the second step, further scientific publications on the subject and on their interactions with the Internet community (for example, activity on blogs, newsletters, etc.). Here, the four above-named persons are particularly noticed something out of the research, depending on other perspectives on knowledge management and support others in their daily process of implementing knowledge management in practice.
David Griffiths teaches at the University of Edinburgh in the field of learning and knowledge management and knowledge management is the founder of the consulting K3Cubed Limited. He has specialized in supporting organizations in dealing with knowledge and learning, lectures and talk about the topic to publish.
In teaching, he also deals with related issues concerning organizations, financial and production management.
Visions – theses about knowledge management trends
* Knowledge management is according to an international study technology still centered primarily understood and more operationally, and is still not the people at the center. This is the reason that there is a high level of dissatisfaction with knowledge management investments.
* Who wants to support organizations in dealing with knowledge should give up the technically inclined term knowledge management. Recognize organizations for other than technical challenges of knowledge management.
* Knowledge management should be seen as a strategic issue and support organizations in their current challenges, such as innovation, resilience, sustainability and growth (or even “healthy shrinking”).
* Knowledge management should be the heart of building the capacity for change. This can be stimulated and thinking forward-driving techniques such as scenario analysis can come to train.
* Knowledge management can drive needed impending paradigm shift in organizations.
* The role of knowledge in organizations is rising steadily since the 30s (the importance of intangible resources in organizations has grown from 30-40% to 90% with IT companies such as Google). Taking into account the long-term trends knowledge management can be defined as long-term task .
David Snowden, John is an expert on implicit knowledge and works as a lecturer, consultant and scientist. He is a visiting lecturer at the University of Pretoria, University of Canberra, University of Surrey and at the Polytechnic University of Hong Kong. In addition, Dave Snowden is the founder and scientific director of the Cognitive Edge Consulting Organization, which pursues an open-source approach to counseling: Materials and methods are freely accessible via the website. He has developed the Cynefin framework, which transmits the practical application of complexity theory to the topic of leadership in organizations.
As part of the Cynefin framework, problems are classified according to their nature and suggested an appropriate use of them:
* Simple problems based on clear cause-effect relationship: If a given initial situation is observed to take place on the basis of experience (“Best Practices”) an appropriate response.
* For complicated problems must be analyzed more intense situations before they can be responded to. There are often several ways to respond, which are similarly good (“Good Practices”).
* Complex problems are characterized by the fact that due to an initial situation, the effect of certain actions can not be predicted. Is thus viewed as an experimental approach to action (“try out, perceive, react”) proposed (“Emergent Practices”).
* Chaotic problems are such that no cause-effect relationships can be established. Thus, the recommended action is to act, perceive, react with the aim to stabilize the system. This experience created the sense of “practice novel”.
Visions – theses about knowledge management trends
* In the context of organizations should be distinguished from robust stable strategies: robust design (fail-save = drop resistant) should (save practicing safe-fail experimentation = fall) to be stable and thus krisenresistentem design.
* The management of knowledge is always voluntary and may never be enacted.
* We know only what we need to know. We react to perceived patterns (pattern-based intelligences), and no information processors (information processors) are.
If there is a real need for knowledge, very few people will refuse to share their knowledge.
* Tolerated failure shapes the learning process better than success: Organizations should accept failure in a particular context.
* Talking about our knowledge is something other than our own knowledge
* We know more than we can put into words and tell us more than we can write down.
* Everything is fragmented, chaotic people seek connection (messy coherence) and just not too much structure, since it is quickly outdated and costly to maintain. Thus, the approach Semantic Web – that is a clear, structured description of importance of Internet content – limited. 
David Gurteen has long been the software development manager and was with Lotus Development to ensure a uniform design of the Lotus products globally responsible.
Today he is an independent knowledge management consultant, speaker and moderator. He is in various fields of knowledge management present and organized regularly Knowledge cafes. He publishes on his blog (The Gurteen Knowledge Weblog) and on his website (The Gurteen Knowledge website) and reached its newsletter (The Gurteen Knowledge Letter) about 15,000 people.
Visions – theses about knowledge management trends
* The sharing of knowledge and social learning – now perceived as extra work – is a welcome and normal part of everyday work. Ponder the future workforce is no longer alone in my room, thinking aloud and jointly with others.
* Also work no longer takes place behind closed doors, but transparent and visible to everyone.
* Instead of forcing the employees IT tools, they select themselves out of the tools that would be most useful. Likewise, we will select the information that you need, instead of allowing themselves to heap indiscriminately with everything.
* Instead of controlling the people for fear of making mistakes, they get more creative freedom, and must bear more responsibility in return.
* Information is no longer concentrated and “protected”, but is open and accessible. The information flow is less regulated.
* The importance of context is more pronounced in the foreground. Rather than in isolation as information to examine the context, the flow circumstances / conditions more into consideration.
* The world is perceived as complex and varied. The simple cause-effect model has become obsolete and will have to give other approaches. 
* In today’s wealth grows at the (publicly available) information faster. It takes some time but mostly to understand the often complex and sometimes chaotic situations. Often helps to talk to others to make the many factual knowledge something useful – a methodological approach to this is the Knowledge Cafe. 
Norbert Gronau studied mechanical engineering and business administration at the Technical University of Berlin. He completed a doctorate on the “concept of a strategy-oriented management information system for decision support in production management” and habilitated with the theme “Sustainable industrial information systems architectures for organizational change.” He holds the chair of computer science and Electronic Government at the University of Potsdam. His research interests lie in the areas of operational knowledge management and versatile ERP systems. He is also scientific director of the Potsdam institute settled Center for Enterprise Research (CER).
Visions – theses about knowledge management trends
* Currently no organizational assignment of responsibilities typical of knowledge management in the organizational structure of enterprises is evident.
* Competence and experience of people can not be replaced by the use of computerized systems. Still can not provide the necessary creativity and intuition.
* In the area of inter-organizational issues of information security and protection against theft of intellectual property rights as major drivers of change have been felt. The assurance of intellectual capital is the task of knowledge management.
* With the increasing popularity of social media in their private lives and in the company’s internal and external use, there will be more experiments with Web 2.0 technologies and approaches, and remove the uncertainty about social media use in organizations.
* The bandwidth of the demand for knowledge management is significantly larger. More and more companies and public institutions is clear that the knowledge of their employees is a central element for competitive differentiation and represents the key to successful change is.
* For the exchange of knowledge between institutions-personal knowledge, there is support suitable conversation and transformation in organizational forms and spaces and times must be supported.
* Conversion pressure and demand of the employees generate new demands on IT. IT is insufficient competition threatens to fail by the knowledge holders. 
Is perceived – David Griffiths shows that managers with knowledge management is less important – but also more technically oriented. Knowledge in organizations takes on an increasingly larger role, becoming a strategic issue.
Dave Snowden brings a different perspective: Best Practices – a standard method for experiential knowledge – only works for simple problems. Complex or chaotic situations require a different approach: first try, then act and react at the end. He points out that existing structures do not help to address the issues and a climate that is more important, the failure must be allowed for.
David Gurteen states that can be complex or even chaotic situations most likely to work through personal interviews: these must be created for such opportunities.
Norbert Gronau finds that the range of knowledge management is much larger: in addition to social media, intellectual capital and the pressure change in the IT context plays an important, new role.
David Griffiths also emphasizes the role of knowledge in connection with the conversion ability. From the perspective of an organization to its environment changes rapidly and unpredictably – among others due to various crises at the national and international level. Therefore assumes an important role versatility. Knowledge in turn is the basis for organizations to change, because change can be better estimated with the common knowledge of all employees. If their knowledge and creativity used, new approaches – and thus sustainable innovations – the first place.
 David Griffiths: The future of KM (7 / 2011) – theknowledgecore.wordpress.com/2011/07/16/the-future-of-km
 Dave Snowden: Judgement & resilience, KM Asia November 2010 Keynote – www.cognitive-edge.com/presentationdetails.php
 David Gurteen: World 2.0, in: Gurteen Knowledge: 10 Years in KM, 2010
 Elizabeth Wagner: The Gurteen Knowledge café for David. In: Project Magazine, Issue 21/2011
 Norbert Gronau: Challenges and trends in knowledge management (KnowTech 2011 – Keynote, Bad Homburg)
Tuesday, January 31, 2012
Victor Aduba, DT286
Andrej Bartko, DT230
John Brogan, DT217
Kenneth Bryne, DT286
Thomas Bryne, DT285
Chenje Cao, DT285
Liam Carey, DT217
Brendan Cregan, DT230
Colclough Doran, DT230
Niall Dowdall, DT210
Garrett Duffy, DT286
Eloho Egivuferai, DT217A
Keith Ellman, DT285
Fatima Emmanuel, DT286
Olu Folarin, DT286
Edward Robert Freyne, DT286
Jelena Haiduroua, DT230
Robert Huczek, DT217A
Frank Kendlin, DT285
Tair Kuanyshev, DT285
Raj Kumar, DT286
Gabriel Lawless, DT202A
Lira Maricar Mariano, DT285
David Marvroudis, DT285
Vincent McKenna, DT217A
Marcus McQuiston, DT217
Eamonn O'Brien, DT230
Philip O'Donnell, DT286
Christina Shannon, DT217
Saturday, January 28, 2012
There's a secret code hiding in many a scientific research paper, but it's not the key to immortality or a way to turn maple syrup into rocket fuel. No, it's the code that tells you precisely what was going through the researcher's head as he or she was writing the paper. Fair warning: once you've seen what thoughts lurk behind these seemingly innocuous phrases, they cannot be unseen.
While I suspect that whoever is behind these good-natured jabs has written a lot of scientific papers themselves, I'd love to see them take on other academic disciplines and their best crutch phrases.
Wednesday, January 25, 2012
When it comes to old academic societies, there isn't an organization on Earth that can hold a candle to Britain's Royal Society. Founded all the way back in 1660, The Royal Society has been pumping out peer-reviewed scientific literature since 1665, when the first edition of Philosophical Transactions of the Royal Society made its debut.
And today, almost 350 years later, The Royal Society has opened up his historical archive of journals to the public, free of charge.
All told, the fully searchable online archive comprises around 60,000 scientific papers. And while complimentary access is limited to those articles published before 1941, don't let that distract you from the incredible collection of publications included in the archive.
Ben Franklin's original paper on his electric kite experiment? It's in there, dating back to 1752. Geological experiments conducted by a young Charles Darwin? Here you go. Isaac Newton's first scientific paper ever? That's there, too.
BBC has a handful of gems that they've already found in the archives, but don't forget, the collection is searchable, so be sure to check it out and see what other historic experiments you can dig up.
Friday, January 13, 2012
That's the rather counter-intuitive finding of mathematicians at the University of Vermont, who just last month used Twitter data to argue that global happiness had decreased over the last two years. And yet, whatever these short-term trends, English seems to remain "strongly biased toward being positive", as team member Peter Dodds puts it.
Of course, that might seem like such a huge statement that it's impossible. To reach that conclusion, they examined billions of words used in such diverse sources as the last twenty years of The New York Times, 50 years worth of music lyrics, Twitter, and the Google Books Project, which includes millions texts dating as far back as 1520. They then looked at the top 5,000 words for each of these, and then enlisted volunteers to rate on a scale of 1 to 9 the happiness of the 10,222 most common words taken from these four sources.
MORE HERE >>