Only 11% rely on data to make decisions! #BigData Confuses Most Marketers http://t.co/CxUnlMwq [American News Report]

The real challenge is figuring out your question! #BigData is a solution looking for a problem: Gartner http://t.co/W0pBlron [ITworld]

Great tips! The Best Content Marketing Is Free http://t.co/rOPv4IBM [Inc] #contentmarketing

We’re more fooled by noise than ever before. Beware the Big Errors of ‘Big Data’ http://t.co/cDbHLRCb [Wired]

Big Data Right Now: Five Trendy Open Source Technologies http://t.co/maGBIKwW [TechCrunch] #bigdata

What’s Your Time To Insight from Data? http://t.co/6TfxN9QO [Forbes] #data #analytics

Meet Your Company’s New Chief Customer Officer http://t.co/cDhVvcuaoG [Harvard Business Review Blog Network]

All links shared via Twitter – follow along!

The post Point-and-click: February 28th, 2013 appeared first on Walter Jessen Digital + Strategy.

Twitter is enormously popular today. Indeed, there are roughly 72 million active accounts tweeting some 400 million times a day. Because of this popularity, more and more businesses are including Twitter in their social media strategy.

The social networking service offers a widget, which enables you to put updates anywhere on the web or create a live stream for an event. You can embed on a web page all the tweets from a particular account, list or search result.

A consulting client of mine recently asked about the search engine optimization (SEO) benefits the Twitter widget, which is a great question when you consider all the key words from the widget that show up on a page.

The Twitter widget is created from javascript code, which is interpreted in the browser. If you right click on a web page that displays a Twitter widget and view the page source, it looks like html code, but that code isn’t there when a search engine looks at the page (that’s not exactly true, but hang with me a minute).

For a number of years now, Twitter has had individual widgets to show tweets from a specific Twitter account, favorites from a single account, tweets by those on a Twitter list, or a Twitter search result. In the fall of last year, Twitter replaced individual widgets with a new, unified interactive timeline widget. The new widget allows people to not only see tweets, but respond to them right from the widget.

We use the Twitter widget on the Biomarker Commons home page to show links and discussion around biomarkers and personalized medicine. Check out how the new widget looks (left) compared to the old widget (right).

Back to the question about the SEO benefits of the Twitter widget and page html code. You can use Google Webmaster Tools to see what the Googlebot sees: sign in, select your website (you have to have previously added your site), Health >> Fetch as Google, fetch the homepage (or other page if the widget isn’t on your homepage), and then click on the “Fetch Status” link “Success”.

Here’s what the Googlebot sees when it looks at the widget on Biomarker Commons. Notice the <script> code at the end:

<h2>On Twitter</h2><div class="content"><p><a class="twitter-timeline" href="http://feeds.feedblitz.com/~/t/0/0/digital-strategy/~https://twitter.com/search?q=biomarker+OR++OR+%22personalized+%22" data-widget-id="305364624532963328">Tweets about "biomarker OR biomarkers OR "personalized medicine""</a></p><script>!function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="http://www.walterjessen.com//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs");</script></div>

The Twitter widget is generated by javascript in the browser, so it isn’t content that is indexed by a search engine and thus has no SEO benefit.

By the way, if you’re using the old Twitter widget, it’s time to upgrade. The old widget uses the application programming interface (API) v1.0. Twitter will start running ”blackout tests” for API v1 on March 5th, 2013, and over the next few weeks, will be announcing additional blackout tests and a more detailed schedule regarding the retirement of API v1.

The post Does the Twitter Timeline Widget Improve SEO? appeared first on Walter Jessen Digital + Strategy.

ScienceOnline‘s preeminent annual meeting takes place in North Carolina every January. As I did for the first two days of the conference, below is an analysis of Twitter data for day three.

First, some statistics

The tweets were collected between 12:00am and 11:59pm on Saturday, February 2nd. In total, there were 6,719 tweets (14% more than day one and 5% more than day two) consisting of 120,655 words from 1,261 people. Just like #scio13 day one and #scio13 day two, the top tweeter was Janet Stemwedel (Twitter: @docfreeride) with 214 tweets! Here are the top 10 Twitter users and their number of tweets:

Most conference attendees using Twitter actually tweeted very little: 1,076 people (85%) tweeted less than 10 times, one hundred fifteen people tweeted 10-20 times, 54 people tweeted 21-49 times, and 16 people tweeted over 50 times.

Let’s focus on retweets. Retweets are a way of saying “yeah, I like that” or “I agree!” and for the purposes of this analysis come in two forms: they can be a simple rebroadcast (e.g. RT: “original tweet”), which we’ll call a RT without conversation, or a retweet with comments back to the original tweeter (e.g. Agreed! RT: “original tweet”), which we’ll call a RT with conversation. Thirty nine percent (39%) of #SCIO13 day 3 tweets were retweets. Of those, 11% (300 of 2652) were a RTs with conversation. The top five retweeters were Bora Zivkovic (Twitter: @boraz) with 63 retweets, Janet Stemwedel (Twitter: @docfreeride) with 50 retweets, Chris Pires (Twitter: @jchrispires) with 42 retweets, Matthew Francis (Twitter: @drmrfrancis) with 38 retweets, and Adrienne Roehrich (Twitter: @fiainros) with 37 retweets.

#SCIO13 Day 3 tag cloud of tweets

As I’ve written before, I’ve always had a thing for tag clouds. I find tag clouds a useful visual representation of data; if they’re designed right, tag clouds can also look really good.

From 120,655 words extracted from the #scio13 day 3 tweets, 9,193 were unique. I calculated the frequency of all 9,193 words and then “cleaned” the data, removing all words less than 4 characters, numbers, and words that were either common words (such as “that”, “from”, “with” or “have”) or gibberish (consisting principally of url strings from shared links).

The top 100 terms were then imported into Wordle and a weighted tag cloud was generated. Feel free to download any of the files below and reshare.

Here are the top 10 terms from the tag cloud above:

All data and images are avaliable for download: low-resolution image, high-resolution image or raw data set of 100 terms with frequencies.

The post Visualizing ScienceOnline 2013 Tweets Day Three appeared first on Walter Jessen Digital + Strategy.

ScienceOnline’s preeminent annual meeting takes place in North Carolina every January. I did an analysis of Twitter data for day one of ScienceOnline 2013 and wanted to do the same for day two.

First, some statistics

The tweets were collected between 12:00am and 11:59pm on Friday, February 1st. In total, there were 6,363 tweets (10% more than day one) consisting of 112,693 words from 1,302 people. Just like #scio13 day one, the top tweeter was Janet Stemwedel (Twitter: @docfreeride) with 138 tweets! Here are the top 10 Twitter users and their number of tweets:

Most conference attendees using Twitter actually tweeted very little: 1,135 people (87%) tweeted less than 10 times, ninety-six people tweeted 10-20 times, 57 people tweeted 21-49 times, and 14 people tweeted over 50 times.

Let’s focus on retweets. Retweets are a way of saying “yeah, I like that” or “I agree!” and for the purposes of this analysis come in two forms: they can be a simple rebroadcast (e.g. RT: “original tweet”), which we’ll call a RT without conversation, or a retweet with comments back to the original tweeter (e.g. Agreed! RT: “original tweet”), which we’ll call a RT with conversation. Forty percent (40%) of #SCIO13 day 2 tweets were retweets. Of those, 12% (301 of 2559) were a RTs with conversation. The top five retweeters were Bora Zivkovic (Twitter: @boraz) with 76 retweets, Janet Stemwedel (Twitter: @docfreeride) with 46 retweets, Matthew Francis (Twitter: @drmrfrancis) with 43 retweets, Chris Pires (Twitter: @jchrispires) with 29 retweets, and Genegeek (Twitter: @genegeek) with 28 retweets.

#SCIO13 Day 2 tag cloud of tweets

As I’ve written before, I’ve always had a thing for tag clouds. I find tag clouds a useful visual representation of data; if they’re designed right, tag clouds can also look really good.

From 112,693 words extracted from the #scio13 day 2 tweets, 9,444 were unique. I calculated the frequency of all 9,444 words and then “cleaned” the data, removing all words less than 4 characters, numbers, and words that were either common words (such as “that”, “from”, “with” or “have”) or gibberish (consisting principally of url strings from shared links).

The top 100 terms were then imported into Wordle and a weighted tag cloud was generated. Feel free to download any of the files below and reshare.

Here are the top 10 terms from the tag cloud above:

All data and images are avaliable for download: low-resolution image, high-resolution image or raw data set of 100 terms with frequencies.

The post Visualizing ScienceOnline 2013 Tweets Day Two appeared first on Walter Jessen Digital + Strategy.

ScienceOnline’s preeminent annual meeting takes place in North Carolina every January. I’ve been archiving all the tweets from this year’s conference. Yesterday, I tweeted out simple stats on Twitter usage over the course of the day. Last year I created a tag cloud of ScienceOnline2012 tweets and decided this year I would do the same for each day of the conference.

First, some statistics

The tweets were collected between 12:00am and 11:59pm on Thursday, January 31st. In total, there were 5,752 tweets consisting of 102,843 words from 1,333 people. The top tweeter was Janet Stemwedel (Twitter: @docfreeride) with 124 tweets! Here are the top 10 Twitter users and their number of tweets:

Most conference attendees using Twitter actually tweeted very little: 1,187 people (89%) tweeted less than 10 times, ninety-five people tweeted 10-20 times, 41 people tweeted 21-49 times, and 10 people (listed above) tweeted over 50 times.

Let’s focus on retweets. Retweets are a way of saying “yeah, I like that” or “I agree!” and for the purposes of this analysis come in two forms: they can be a simple rebroadcast (e.g. RT: “original tweet”), which we’ll call a RT without conversation, or a retweet with comments back to the original tweeter (e.g. Agreed! RT: “original tweet”), which we’ll call a RT with conversation. Over one-third (36%) of #SCIO13 tweets were retweets. Of those, 12% (219 of 1869) were a RTs with conversation. The top five retweeters were Chris Pires (Twitter: @jchrispires) with 42 retweets, Drug Monkey (Twitter: @drugmonkeyblog) with 41 retweets, Bora Zivkovic (Twitter: @boraz) with 34 retweets, Christie Wilcox (Twitter: @nerdychristie) with 31 retweets, and S. Bodman (Twitter: @sciwhat) with 27 retweets.

#SCIO13 Day 1 tag cloud of tweets

As I’ve written before, I’ve always had a thing for tag clouds. I find tag clouds a useful visual representation of data; if they’re designed right, tag clouds can also look really good.

From 102,843 words extracted from the #scio13 day 1 tweets, 8,445 were unique. I calculated the frequency of all 8,445 words and then “cleaned” the data, removing all words less than 4 characters, numbers, and words that were either common words (such as “that”, “from”, “with” or “have”) or gibberish (consisting principally of url strings from shared links).

The top 100 terms were then imported into Wordle and a weighted tag cloud was generated. Feel free to download any of the files below and reshare.

Here are the top 10 terms from the tag cloud above:

All data and images are avaliable for download: low-resolution image, high-resolution image or raw data set of 100 terms with frequencies.

The post Visualizing ScienceOnline 2013 Tweets Day One appeared first on Walter Jessen Digital + Strategy.

I finally carved out some time to review the upcoming ScienceOnline2013 program and choose the sessions I want to attend.

As I did last year when I selected ScienceOnline2012 sessions, I posted my tentative schedule below. Writing this post forced me to think about why I wanted to attend each session and gave me the chance to look up each of the moderators (ScienceOnline is also about networking, and I think it’s a good idea to identify people I’d like to meet).

My focus this year is on data, publishing, citizen science and media.

Are you attending any of the sessions below? Let’s make sure to connect at the conference: leave me a comment below, send me message on Twitter, or use the website’s contact form.

Wednesday, January 30th

1:00 pm — 4:30 pm @ NRC (straight from the airport)

Workshop: Designing Effective Visualizations with R

Speakers: Carl Boettiger and William Gunn

The right presentation of data can make even complex ideas simple to grasp. In this workshop, attendees will learn how to build up an effective visualization from the primitives of shape, size, and color. No prior programming experience is required. This workshop will teach you the essential data-wrangling skills you need to move beyond the spreadsheet and into more efficient data analysis and more beautiful information design. Everyone who attends will leave being able to scrape data from the web, load it into R, create a simple yet elegant visualization, then publish their work so that others can reproduce it. Essentials of data preparation and reproducible workflows will be emphasized and several real-world examples and case studies will be discussed.

6:00 pm — 9:00 pm @ NRC

Opening Event

We will open the conference with a Wed night event at the NC Museum of Natural Sciences Nature Research Center in Raleigh (6-9 PM). It’s an amazing venue. The museum is a short walk from the Marriott/Sheraton.

We will start at 6pm. We will have light appetizers (cheese, fruit, vegetable crudités, finger sandwiches) and drinks (Kentucky Bourbon Barrel Ale and wine). Bora, Anton, and I will welcome you with a toast to the event and then encourage you to explore and start your conversations!

We encourage you to purchase some more substantial food in the Daily Planet Café as you stay for the evening. Their entire menu will be available. At 7:45ish, our very own Brian Malow (the Science Comedian will entertain you from his home stage of the SECU Daily Planet (a 3-story theatre inside the large globe you see outside the museum!), which is a focal point of the Nature Research Center.

Thursday, January 31st

BUS A2: Load 8:10am; Depart 8:15am

9:00 am – 10:00 am @ McKimmon Conference Center

CONVERGE: Welcome & instructions for the day

CONVERGE: Social Media is Out of This World

10:00 am — 10:30 am

Break

10:30 am — 11:30 am @ Room 7b

Leading Scientists Towards Openness

Moderators: Sean Ekins and Antony J Williams

This session will discuss what open science means and how we can encourage it, if indeed we need to.

Questions:

• How do we define openness – Open Access, Open Data, Open Science?
• Are there obvious benefits to openness in science?
• If yes, what are the blocks towards openness? Tools, Systems, IP concerns, organizational support.
• Do scientists have to be fully open or is partial or part time open?
• What are incentives to move scientists towards openness
• Do journals, patents, IP all prevent openness?
• Do open journals promote open science or not?
• What projects can we launch at SciO13 and monitor/measure for impact of Open Science
• Which prominent open scientist can we invite to scio13?

11:30 am — 12:00 pm

Break

12:00 pm — 1:00 pm @ Room 6

Summing it Up: The Data on the Cutting Room Floor

Moderators: Cristy Gelling and Mindy Weisberger

How many times have you asked yourself, “Can I say ‘Cryptomonads are a group of photosynthetic/algal cells,’ or must I make note of that one genus that isn’t photosynthetic and makes it hard to say what exactly they are?” Well, you’re not alone. In scientific publication and in science communication, one of the great challenges is streamlining the message at the expense of at least SOME of the data. But lending a hat-tip to ALL the data makes for unwieldy sentences—exemptions, exceptions and uncertain language add up to difficult reading. Not all the data can be represented, but how do you incorporate it into a coherent message? How do you decide what to emphasize and what to omit? How much qualifying is ‘too much’? While some choices may be more subjective than others, this session will address best practices for assembling summaries that are the most accurate representation of the data.

Questions:

• How do you generalize without misrepresenting the data?
• How does one organize the transformation of raw image data (eg. micrographs) to a summary diagram?
• What sorts of details are permissible to omit?
• How does the target audience shape which details stay and go?

1:00 pm — 2:30 pm

Lunch

2:30 pm — 3:30 pm @ Room 6

Summing it Up: The Data on the Cutting Room Floor

Moderator: Maggie Koerth-Baker

Uncertainty is something scientists take for granted. There’s always a possibility that your results could be wrong. There’s always a possibility that the situation will change. There’s always questions you can’t answer yet, and always details still undelved. Trouble is, the public doesn’t know that. For many people, results are facts and unknowns are failures (or, at least, good reasons to mistrust the experts). This disconnect between what science actually is and what the general public believes it to be creates serious communication problems, and makes it hard for people to know how to apply scientific data — both in their personal lives, and in public policy. To bridge that gap, bloggers and journalists need to do a better job of building an understanding of uncertainty into our work. But how? Come to this session to hear our stories, share yours, and help curate a list of tips, tricks, and resources that everyone can use. Proposed hashtag: #SciOUnknown

Questions:

• There’s stuff we know. Stuff we don’t know. And stuff we don’t know we don’t know. How do you talk about unknown unknowns in science?
• Science is uncertain. Do you think the public understands that? Share your thoughts on what we don’t know, and how to talk about it.

3:30 pm — 4:00 pm

Break

4:00 pm — 5:00 pm @ Room 3

Blogging for the Long Haul

Moderators: Sci Curious and Zen Faulkes

The oldest science blogs are just hitting their ten year blogiversaries. A lot of blogs have come and gone in that time. Will you still be blogging in 5 years? 10 years? 20 years? What does it take to write a blog (or other online project) for the long haul? Many creative people have at one time or another faced the dreaded “writer’s block” or its equivalent. How do you break out of creative slumps, dry spells, and blocks so that you do not disappear from the scene? What are the warning signs that you disconnect entirely? Is there a good balance between the rush to say something current, to be the first, and writing something of substance, that people will remember? Are you confident that someone will be able to read your blog ten years from today? And would they find anything worth reading?

Questions:

• Do you expect to still be blogging in 5 years? 10 years? 20 years? What strategies you use to keep a blog going for years, or even decades?
• When is it worth it to disconnect from the online conversation and focus? What are the warning signs that you’ve spread yourself too thin?
• How can you beat – or, better yet, avoid – a dry spell or writer’s block?
• Would all the stuff you’ve blogged survive a change to a new platform or – horrors – the company going under?
• What are the long term rewards of creating a long term project? How much traffic do posts get years after you’ve written them?

7:00 pm

Evening Social Event

Friday, February 1st

BUS A2: Load 8:10am; Depart 8:15am

9:00 am – 10:00 am @ McKimmon Conference Center

CONVERGE

10:00 am — 10:30 am

Break

10:30 am — 11:30 am @ Room 8

What’s News in Citizen Science? Perspectives, People, Projects, and Platforms (part I)

Moderators: Darlene Cavalier and Caren Cooper

Citizen science describes science-society collaborations that span a wide spectrum of activities under many different names, disciplines, scales, physical places around the world, and places in history. Citizen science is also called volunteer science, community-based research, street science, do-it-yourself (DIY) science, public participation in scientific research (PPSR), participatory science, web-mapping, crowd-sourcing, and more. It can be global and exclusively online via games and solving puzzles, crowd-sourcing information, or data transcription. It can be exclusively offline, such as connecting people with nature or science locally. Most commonly, citizen science involves people collecting or observing in their real world geo-referenced location and submitting the information into an online database via computer or mobile technology. From astronomy to zoology and conservation to urban planning, citizen science allows professionals and amateurs to co-produce knowledge. Session moderators will provide historic and modern-day context of citizen science and review the scope of projects and platforms/technologies that provide new frontiers for citizen science.

Questions:

• Only collecting data? What scope of activities/projects qualify as #citizenscience? #scio13
• Only helping scientists? Managers, urban planners, claims adjusters…who uses the data? #scio13 #citizenscience
• #citizenscience isn’t new: what frontiers do communication technologies open for citizen science? #scio13
• Is knowledge co-produced via #citizenscience more special than knowledge via regular sci method? #scio13
• What disciplines/professionals are involved in #citizenscience? #scio13
• What types of story angles emerge from each #citizenscience project? #scio13
• How are participants recruited for #citizenscience projects?
• Can we trust #citizenscience data? #scio13
• Beyond peer-reviewed outcomes of co-produced knowledge, where to dig for #citizenscience stories? #scio13
• Is a scientific result more/less newsworthy if it came about from #citizenscience methods? #scio13
• What online tools/platforms enable #citizenscience engagement in hypotheses, protocols, data collection, data sharing, analyses? #scio13
• Evaluating select #citizenscience tools/platforms: what are their benefits/ limitations?

11:30 am — 12:00 pm

Break

12:00 pm — 12:15 pm @ Room 4

Blitz: Tools and technologies powering new frontiers for citizen science

Moderator: Darlene Cavalier

12:40 pm — 12:55 pm @ Room 7a

Blitz: Comprendia – Getting Financial Support For Your Blog Without Selling Your Soul

Moderator: Mary Canady

1:00 pm — 2:30 pm

Lunch

2:30 pm — 3:30 pm @ Room 7a

Telling Visual Stories with Data: A Guided Tour of Data Visualization

Moderators: Peter Aldhous and Lena Groeger

How do we understand data? In an age of ever-exploding amounts of information, we face the age-old challenge of making meaning out of complex subjects. Because our eyes can process vast amounts of data quickly, visualization is one key tool in helping us see the big picture, and can be a critical tool for communicating science. But data visualization is more than just word clouds and pie charts, and is informed by a long history of information design, computer science and statistics. This session will explore the process of visualization – how to acquire, question, filter and represent data into clear and powerful visual stories.

Questions:

• What are some design principles that inform data visualization?
• What are some tips, tricks, and tools that can help with telling visual stories?
• What’s the difference between an infographic and a data visualization?
• How can I use data visualization in science?
• What questions should I keep in mind as I make a visualization?
• How do I decide what form a visualization should take?
• What role do colors and typography play in my data visualization?

3:30 pm — 4:00 pm

Break

4:00 pm — 5:00 pm @ Room 8

Sticking with it for the long haul: Building community and maintaining long-term engagement in citizen science (part III)

Moderators: Holly Bik and Caren Cooper

Many large-scale citizen science projects excel at generating public excitement about their work and engaging participants in data collection. Yet, increasingly project organizers aim for much more than a one-off data contribution by participants – we want to engage citizen scientists in the whole process of science, from hypothesis generation through analysis and development of next steps, including future projects. Unfortunately, the process of science can be slow, twisted and even arduous, with long lag times between initial participation and return of results. How do we keep participants interested and engaged during the interim? Can we build communities of interest around projects as a means for maintaining long-term engagement with our citizen scientists? We hope to draw diverse voices into this conversation, hearing from participants and organizers of other engaged online communities (#NASAsocial; Personal Genome Project; DIY, maker and gaming communities come to mind…)

Questions:

• What are the hallmarks of an engaged community rallied around citizen science? Or do we just know it when we see it? (Useful to consider for evaluation of projects)
• How can we improve dialogue with citizen scientists? Are social media and blogs enough?
• What lessons can we learn from other science (and non-science!) organizations who’ve successfully engaged communities? (Think community groups, political campaigns)
• What tools do you use for building community and effectively fostering communication among members of your group?
• Grassroots or top-down? What’s the best way to facilitate community-building within citizen science organizations?
• What can we do in the interim (specific examples!), during the lag time between steps in the scientific process, to sustain participant interest?

6:00 pm

Dinner with friends

Saturday, February 2nd

BUS A2: Load 8:10am; Depart 8:15am

9:00 am – 10:00 am @ McKimmon Conference Center

CONVERGE

10:00 am — 10:30 am

Break

10:30 am — 11:30 am @ Room 7b

24/7 Health: The role of mobile technology in healthcare

Moderators: Pascale Lane and Judy Stone

As smart phones and tablets permeate the market, many people carry a potential all-knowing personal assistant that can help them learn about health, remember their medications, and track their diet and physical activity. Apps now bring HIPPAA compliant connections to providers and medical information. On the other side, providers have access to more information than ever before. How can we maximize these systems to increase health? What new models can be developed to help people and providers?

11:30 am — 12:00 pm

Break

12:00 pm — 1:00 pm @ Room 6

How do you actually get a book written?

Moderators: Maria Konnikova and Katherine Sharpe

So, you have a great idea for a book. Or at least you think you do. But is it a book, or just another article? How can you tell the difference? And once you do, how do you go from the idea to the actual book? What’s the process like, and how is it different from every other writing assignment you’ve taken on? How do you take a massive amount of information and turn it into something not only readable but a joy to read? And how do you stay sane—and excited—in the process? Writing a book can be one of the most rewarding things you’ll ever do. But it can also pose a challenge to your skills and your peace of mind?? Veteran and aspiring authors are invited to join Katherine Sharpe, author of “Coming of Age on Zoloft,” and Maria Konnikova, author of “Mastermind: How to Think Like Sherlock Holmes,” in a discussion of how to tackle writing’s ultimate long distance event.

Questions:

• How do you know which idea is “the one”?
• What makes a book different from a long article?
• How do you know if you’re in trouble—and what do you do if you are?
• What are the resources available to you, and when is the right time to use them?
• What do you need to know about writing a book proposal?
• What should you know going in? / What do you wish you’d known going in?
• Authors in the house: what would you do differently next time?
• How can you get the most out of your relationship with your editor?
• How do you know when to stop researching and start writing (or should you do them at the same time)?
• A happy writer is a good writer? (How do you take care of yourself under pressure?)
• How do you balance writing with your other commitments?
• What do you do if writing your book isn’t enough to pay the bills?
• I delivered my first pass manuscript. Now what?

1:00 pm — 2:30 pm

Lunch

2:30 pm — 3:30 pm @ Room 3

Life in the Venn — What Happens When You’re Forced to Wear Many Hats?

Moderators: Jonathan Eisen and Ed Yong

Increasingly, people in the science world seem to play multiple roles. Some are scientists and journalists. Others are journalists and PIOs. Some teach with one hand, research with the other, and blog with their faces. How do we handle the tensions between roles that can have conflicting priorities and values, and how do we partition our different identities online?

3:30 pm — 4:00 pm

Break

4:00 pm — 5:00 pm Room 1 c/d

CONVERGE: Closing

The post Planning for ScienceOnline2013 appeared first on Walter Jessen Digital + Strategy.

What does success mean to you?

I’ve been crazy busy this year. As I take a break with the Thanksgiving holiday, I’ve had the chance to reflect on my work, success and the art of living.

Success means different things to different people. To some, it means pursing a passion. To others, it means doing what you’re competent at. And yet to others, it means doing something that’s valued (opportunity).

If you have competency and passion, but lack opportunity, you have a hobby. If you have competency and opportunity, but lack passion, you’re going to be bored and underperform. If you have opportunity and passion, but lack competency, then you’re a novice and need training and experience.

The key to success

The key to success is finding that sweet spot where your passion, competence and market demand intersect. If you can find that spot, you’re in a position where your job enriches your life and your life enhances your job.

The goal of success and the art of living should be a career in which you can’t believe people actually pay you to do your job. I heard a quote recently by the Chinese Taoist philosopher Lao-Tzu, which I think says it all about work-life integration:

The person who is a master in the art of living makes little distinction between their work and their play, their labor and their leisure, their mind and their body, their education and their recreation, their love and their religion. They hardly know which is which. They simply pursue their vision of excellence at whatever they do, leaving others to decide whether they are working or playing. To them, they are always doing both.

Truly words to live by and a great way to wrap up this post: pursue excellence in everything you do.

The post Success and the Art of Living appeared first on Walter Jessen Digital + Strategy.

ScienceOnline is a non-profit organization that facilitates conversations, community and collaborations at the intersection of Science and the Web. They do this through online networks, projects and face-to-face events (both global and grassroots).

Since 2007, ScienceOnline has held an annual conference in the Research Triangle area of North Carolina, hosting scientists, students, educators, physicians, journalists, librarians, bloggers, programmers and others interested in the way the World Wide Web is changing the way science is communicated, taught and done.

I’ve attended the annual ScienceOnline conference since 2010 and I’ve had the privilege to moderate three sessions over the years:

• ScienceOnline2010: The Intersection of Medicine 2.0 and Science 2.0
• ScienceOnline2011: Marketing Yourself in Science
• ScienceOnline2012: Drowning in Information! How Can We Create Organization and Balance

I was literally ‘hooked’ on ScienceOnline the first year I went. The conference immediately became and continues to be the one event I have to attend every year. Not only is the topic of science communications important to me, once you attend an unconference style meeting, you’ll hate going to conferences that use a traditional format. Indeed, the best discussions are outside the lecture hall, so why not replace the lecture with those conversations? This is one of the many things that ScienceOnline does, and it does it incredibly well.

Planning and the wiki

After ScienceOnline2010, I asked Bora and Anton if there was anyway I could help in the planning and development of ScienceOnline2011. There was, and I began helping with the ScienceOnline conference planning wiki, which is used every year to solicit, document and organize session ideas, and to develop the program for the upcoming meeting.

I’m helping to setup, organize and manage the ScienceOnline2013 wiki again this year…and this year we’re going to try something different.

With 10 time slots (each having 7 sessions) as well as additional workshops and blitz sessions, cramming everything into the sidebar isn’t an efficient way to structure the wiki’s navigation. I came up with a naming scheme last year to try and keep everything in order and quite honestly I thought it was a mess. So here’s my idea for this year:

For the Program, there are 12 “top level” pages linked from the navigation sidebar (see the image at right). These include the 10 time slots, Workshops, and Blitz Sessions. Each top level page will provide attendees with a high level overview of session dates/times, titles, moderators (with links to their Twitter pages, if available),  and room numbers. For example, the Session 1 page will list the 7 different sessions available during the first time slot (Sessions 1A-1G). Although it will take two clicks to navigate to the details of a specific session, in the end everyone will find it faster to navigate since they don’t have to scroll through multiple session descriptions. A similar structure is also in place for the Workshops.

I’m also coding in direct links back to the top level pages on each of the specific session pages. This gives readers the option of clicking in page to return to the top level session page or program page, or alternatively they can select a destination from the wiki sidebar. The direct links are clearly boxed, colored in ScienceOnline orange, and centered on each of the session pages (typically near the bottom of the page). Lastly, I’m coding in a button so users can quickly Tweet each page. That way, as moderators add session information and/or others post comments, it’s simple to let the #scio13 community know there’s new content.

Please let me know your thoughts on these ideas, as well as any other suggestions you have for making the wiki better, in the comments section below.

One last thought: if you’re like me and you find the discussions at ScienceOnline valuable, if the conference is near or at the top of your “go-to meeting list” every year, I encourage you to share your time and/or your money to support the ScienceOnline organization. The registration cost for this year’s conference is $200, but the actual cost per person to cover all  expenses is much more. The ScienceOnline organization relies on sponsors, supporters and participants — you and me — to make each meeting successful. With a little bit of help in some way from each of us, together we make ScienceOnline even better than it was before.

The post Navigating the ScienceOnline2013 Wiki appeared first on Walter Jessen Digital + Strategy.

I’m a big fan of the AMC show Mad Men, so the title of a recent article on Information Week really got my attention.

According to Webtrends, an almost 20-year-old Web analytics company that provides web, social, and mobile analytics and other software solutions related to marketing intelligence, the ability to consume and extract actionable information from massive data sets is key to a winning market strategy.

Webtrends works with more than 3,500 clients — including BMW, Microsoft, T-Mobile, and Toyota — to help companies draw insights from huge data sets to deliver marketing messages to consumers.

According to Webtrends’ CMO Martin Doettling:

The skill set required today to succeed is so different than in the past. In the old days, marketing was driven by who had the better creative. Today, the success of marketing depends on who has the better math.

Consumer segmentation is very granular today, and organizations that focus on marketing are struggling to keep up with the consumer, said Doettling. Those companies who leverage big data to understand consumer behavior distinguish successful marketers from those who are left behind.

I couldn’t agree more. I recently started offering web and social media analytics as part of my consulting to help businesses and organizations better leverage their data — both big and small — to make data-driven decisions and take action. Indeed, the future of marketing is already here: today’s successful companies are those that leverage consumer information to better segment, target and communicate with their customers.

See the full story

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The report suggests that the challenges facing sales teams today isn’t about data access, but rather what they can do with the data to drive sales growth.

The study found that sales reps struggle just to find the information they need to close deals. More than 80% of respondents feel challenged by the amount of data available and the time it takes to research prospects before making a call. Sales people may search as many as 15 different data sources including their CRM (customer relationship management) systems, Twitter, Facebook, LinkedIn, search engines, and other business information providers to find information on customers and prospects.

Although 80% of respondents have implemented a CRM system, only 44% believe it is effective at helping them find internal information (what a CRM was designed to do!), and almost 80% find it ineffective at helping them find external company information. More than half of companies surveyed rely on their sales reps to do research themselves as they lack the capability to bring together internal AND external information. Given the reliance on sales reps to do their own research, perhaps not surprisingly 89% of reps feel they miss opportunities because they can’t keep up with an endless stream of information on sales prospects.

Big data for sales organizations isn’t simple

From the perspective of new technologies and capabilities, Andris A. Zoltners, Professor Emeritus of Marketing at Northwestern University’s Kellogg School of Management, PK Sinha (co-founder with Zoltners of ZS Associates, a sales and marketing consulting firm) and Sally Lorimer recently suggested in a Harvard Business Review article that big data for sales forces may be overhyped. The trick isn’t simply gathering and mining big data, it’s what you do with it that’s really important.

According to Zoltners, Sinha and Lorimer, critical that companies use big data to provide insight on several types of customers that can help sales reps answer key questions such as ‘which customer to target’ or ‘which offers maximize value for each customer.’ Moreover, for big data to be successful for a salesforce, it must create customer-level insight that both provides salespeople with information and simultaneously helps sales leaders make decisions. Lastly, the processes of collecting, cleaning, organizing and maintaining big data shouldn’t be minimized; these are challenging and expensive tasks.

Big data has great potential for sales organizations. According to the CSO Insights report, 35% of respondents have implemented technology to bring both internal and external information to sales reps, and their win rates are almost 8% higher than companies without the technology.

Check out the infographic created by Lattice Engines showcasing why all sales departments should care about Big Data.

Via: Why Big Data is a Big Deal for Sales

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