{"id":4637,"date":"2016-02-17T11:00:03","date_gmt":"2016-02-17T16:00:03","guid":{"rendered":"https:\/\/www.bu.edu\/federal\/?p=4637"},"modified":"2016-02-19T11:38:09","modified_gmt":"2016-02-19T16:38:09","slug":"show-me-the-data","status":"publish","type":"post","link":"https:\/\/www.bu.edu\/federal\/2016\/02\/17\/show-me-the-data\/","title":{"rendered":"Show Me the Data"},"content":{"rendered":"

First BU Data Science Day draws cross-disciplinary crowd<\/h2>\n
\"Azer<\/p>\n

Azer Bestavros, director of the Hariri Institute for Computing and Computational Science & Engineering (center), and the cochairs of Hariri\u2019s first BU Data Science Day, Prakash Ishwar (left) and Dino Christenson (right), were delighted by the large, cross-disciplinary crowd that came together to talk about how data science is transforming research.<\/em><\/p>\n<\/div>\n

Azer Bestavros<\/a>, founding director of the\u00a0Rafik B. Hariri Institute for Computing and Computational Science & Engineering<\/a>, was practically giddy. It was the first BU Data Science (BUDS) Day<\/a> and the Photonics Center ninth-floor conference room, where the institute was hosting the event, was standing room only.<\/p>\n

\u201cI thought there might be 80, 90 registrants,\u201d said Bestavros, a College of Arts & Sciences professor of computer science and head of BU\u2019s Data Science Initiative<\/a>, welcoming the participants with\u2014what else\u2014data. \u201cThey told me there were 262. I was shocked\u2014really?\u201d<\/p>\n

Not only that, but the data science geeks\u2014faculty and students from physics, mathematics and statistics, computer science, electrical and computer engineering, systems engineering, biostatistics\u2014were there with people from the humanities and the social sciences as well as from CAS, the Questrom School of Business, Sargent College of Health & Rehabilitation Sciences, the College of Engineering, the College of Communication, the School of Social Work,\u00a0the School of\u00a0<\/span>Public Health,\u00a0the School of\u00a0<\/span>Law, and\u00a0the School of\u00a0<\/span>Medicine.<\/p>\n

Bestavros had the data. The registrants were from 66 different disciplines, departments, and offices across the University, including the libraries, Information Systems and Technology, and Career Services. It was the sort of diverse, cross-disciplinary crowd that Bestavros and event cochairs\u00a0Dino P. Christenson<\/a>, a CAS associate professor of political science and a former Hariri Institute Junior Fellow, and Prakash Ishwar<\/a>, an ENG associate professor of electrical and computer engineering, had hoped to draw.<\/p>\n

\u201cWhy are you here?\u201d Bestavros asked his crowd. \u201cIs it because of the whole \u2018data science is the sexiest job\u2019 thing? Maybe it\u2019s about how you\u2019re going to make a ton of money. Maybe it\u2019s about the data that\u2019s coming at us and we don\u2019t know what to do with it; we\u2019re drowning in it. Maybe a lot of you are here to figure out how you can float.\u201d<\/p>\n

Or maybe they had all come together, on a wintry Friday morning at the end of January 2016, because they knew \u201cthat data science has become the common language of all disciplines.\u201d Data science breaks down the walls between disciplines, said Bestavros\u2014\u201cat least we can talk, at least we can all be in the same room.\u201d<\/p>\n

For the next seven to eight hours, faculty, students, and staff connected through data science, brainstorming about its possibilities, reporting on how it was transforming their work in an astonishing array of disciplines\u2014physics, neuroscience, health analytics, cancer research, genomics, the social sciences, marketing, law, even art history. They raised big questions: Can a robot learn how to teach physics? How do you know you can trust the data from crowdsourcing? How can you bring all these different networks together with the right information to actually improve people\u2019s lives?<\/p>\n

\"Boston<\/p>\n

Jos\u00e9e Dupuis (right), an SPH professor of biostatistics, fields an audience question after her talk about using large genomic data sets to understand the genetic architecture of diseases such as type 2 diabetes. Other panel speakers were Jason Bohland (GRS\u201907) (left), a SAR assistant professor of health sciences and speech, language, and hearing sciences, and Eric Kolaczyk (center), a CAS professor of mathematics and statistics.<\/em><\/p>\n

A newcomer\u2019s question: \u201cWhat is data science?\u201d Christenson explained: \u201cData science is a broad term\u2014perhaps overly broad\u2014used to characterize a number of different fields, including political science, that are interested in the systems and processes for extracting knowledge from data. It uses statistical and computational tools to collect, curate, store, analyze, model, and visualize various types of data.\u201d<\/p>\n

Addressing the audience before lunch, Gloria Waters<\/a>, vice president and associate provost for research, commended Bestavros for the interdisciplinary community of scholars he has assembled at the Hariri Institute. She said that the day\u2019s events\u2014the talks, the poster sessions\u2014demonstrated \u201cthe excellence, the depth of work\u201d in data science at BU. She noted that data science is one of BU\u2019s \u201cresearch peaks,\u201d an area that Waters, along with President Robert A. Brown and Provost Jean Morrison, are committed to investing in and excelling at.<\/p>\n

\u201cIt\u2019s absolutely clear we have world-class faculty in basic science\u2014in math and statistics, computer science, electrical and computer engineering\u2014and faculty who are doing amazing work in applications of data science,\u201d Waters said. Recruiting additional top data science faculty is a primary goal of the Data Science Initiative that Bestavros is leading, she added.<\/p>\n

At the event, 12 faculty panel speakers from multiple disciplines spoke for 10 minutes each about how their data-driven research related to one of three broad themes: vision, networks, and health, markets, and policy.<\/p>\n

Kicking off the panel focused on vision and visual-data-driven research, Jodi Cranston<\/a>, a CAS professor of Renaissance art, made the case for small data. \u201cMost scholars in humanities fear big data because it involves technology,\u201d she said. She gave a quick slideshow tour of her Mapping Titian<\/a>\u00a0project, an archive and teaching web application that documents the relationship between the artwork of 16th-century Venetian Renaissance artist Titian and their changing locations and historical context (the project was funded, in part, by the Hariri Institute).<\/p>\n

\u201cYou could think about how movements of artwork are affected by disease, natural disasters, population changes, economic crises, political events,\u201d Cranston said. \u201cRecognizing the potential wide applicability of small data in the humanities helps strengthen the human underlying all humanities research.\u201d<\/p>\n

\"Gloria<\/p>\n

\u201cIt\u2019s absolutely clear we have world-class faculty in basic science\u2014in math and statistics, computer science, electrical and computer engineering\u2014and faculty who are doing amazing work in applications of data science,\u201d said Gloria Waters.<\/em><\/p>\n

Advances in brain imaging have produced a treasure trove of data for neuroscientists. \u201cI study the brain, and the brain is a great problem for big data because the brain has one billion neurons,\u201d said Michael Hasselmo<\/a>, a CAS professor of psychological and brain sciences and director of BU\u2019s Center for Systems Neuroscience<\/a>, beginning his vision talk. Hasselmo explained how he is studying the coding of space and time by neurons in rats as part of his work in understanding memory in humans.<\/p>\n

\u201cI\u2019m an algorithms guy,\u201d said another vision panel speaker, Brian Kulis<\/a>, an ENG assistant professor of electrical and computer engineering, who works on machine learning and big data analysis. Kulis defined machine learning as \u201ca set of tools used to make predictions from data.\u201d These tools are useful in many areas, he said, from driverless cars to robotics.<\/p>\n

Margrit Betke<\/a>, a CAS professor of computer science, uses big data to help visually impaired people with things such as navigating busy intersections on foot, reading medication instruction labels, and setting the temperature control in their apartments. She explained how she and a team of students\u2014with the aid of crowdsourcing\u2014insert tags of text on images on a web page. A visually impaired person \u201ctakes a photo of their temperature control, uploads it to the internet, and then some friendly person in the world will type the answer back to them: \u2018This is your temperature setting.\u2019\u201d<\/p>\n

\"W.<\/p>\n

W. Evan Johnson, a MED associate professor of medicine and biostatistics, underscored the role of team science in his work tracking cancer tumors and drug response in cancer cells. He said he wants to use biological big data to improve what happens in the clinic for patients.<\/em><\/p>\n

Betke ticked off a few of her other current collaborations: she and Stan Sclaroff, a CAS professor of computer science, are designing a machine-learning text recognition system. She is working on cell tracking with Joyce Wong, an ENG professor of biomedical engineering. She and a team of biologists are tracking and analyzing the behavior of bats in caves in Texas.<\/p>\n

Collaboration was the mantra of the day. \u201cWe live and die by our collaborations,\u201d said W. Evan Johnson<\/a>, a MED associate professor of medicine and biostatistics, who underscored the role of team science in his lab\u2019s work in tracking the evolution of cancer tumors and drug response in cancer cells. Some collaborations are more successful than others, he said.<\/p>\n

Biostatisticians are after \u201cthe best method to do something,\u201d he said. Biologists, on the other hand, \u201cwant to be the first person to discover something.\u201d The two goals\u2014best and first\u2014don\u2019t always converge. The key, he said, is to find collaborators who want to contribute their skills to a joint project and who understand what\u2019s in it for everyone involved.<\/p>\n

Johnson, whose research falls at the intersection of statistics, computing, biology, and medicine, said his two teenage sons deserved some of the credit for motivating his research. \u201cThey get a kick out of telling people, \u2018My dad\u2019s a doctor, but not the kind that helps people,\u2019\u201d he said to laughter from the audience. \u201cI\u2019ve made it my goal to do something that helps people,\u201d he went on. \u201cHow can we use biological big data to inform and influence how patients are treated in the clinic?\u201d<\/p>\n

During a break, Bestavros noted the multitude of ways the speakers managed to collect the data for their research. Michael J. Meurer<\/a>, a LAW professor, for example, purchases the data he uses to study patent trolls. For his research into the sharing economy, Georgios Zervas<\/a>\u00a0(GRS\u201911), a Questrom assistant professor of marketing, a computer scientist, and a Hariri Junior Faculty Fellow, analyzes publicly available data from sources such as Airbnb and federal, state, and municipal websites.<\/p>\n

\"Twenty<\/p>\n

From schools and colleges across the University, 26 students participated in the data science poster session. Rajita Menon (GRS\u201918), a doctoral candidate in physics, presented her work on microbial interactions in the human gut.<\/em><\/p>\n

\u201cIt starts with getting the data, cleaning the data, scraping the data,\u201d Bestavros said. \u201cWe have to worry about security and privacy, then we have to worry about doing the analytics. We mine it for information that advances our understanding, and we check if our findings make sense. Finally, we have to communicate this in very different ways.\u201d<\/p>\n

Speaking of communication, 26 students from colleges and schools across the University\u2014public health, medicine, engineering, business, communication, arts and sciences\u2014participated in the day\u2019s poster session<\/a>. Sahar Abi Hassan (GRS\u201919), a doctoral candidate in political science, presented her work on interest groups and the Supreme Court. Abi Hassan said she had been introduced to data science through her department\u2019s required Quantitative Methods 1 course. \u201cFrom there, I just became fascinated with data science and its great potential for social sciences,\u201d she said. \u201cWorking with data allows me to find patterns in political and social phenomena that otherwise would be hidden.\u201d<\/p>\n

Commending Abi Hassan\u2019s work, Bestavros said he hoped the day had demonstrated the importance of data science and education. \u201cIf you\u2019re a student in political science or sociology or marketing or business or journalism and the whole area is now going to become data-driven, you need to learn at least the basics of data science,\u201d he said. \u201cIt\u2019s not something that only computer scientists need to learn. Data touches everything we do.\u201d<\/p>\n

A version of this article was originally published in <\/em>BU Research<\/a>.<\/p>\n

Author,\u00a0Sara Rimer. Photos by Dave Green.<\/span><\/em><\/p>\n

<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

First BU Data Science Day draws cross-disciplinary crowd Azer Bestavros, director of the Hariri Institute for Computing and Computational Science & Engineering (center), and the cochairs of Hariri\u2019s first BU Data Science Day, Prakash Ishwar (left) and Dino Christenson (right), were delighted by the large, cross-disciplinary crowd that came together to talk about how data […]<\/p>\n","protected":false},"author":7048,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[8],"tags":[34,96,109,63,62,48,13,141,93,107,5,32,27,44],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/federal\/wp-json\/wp\/v2\/posts\/4637"}],"collection":[{"href":"https:\/\/www.bu.edu\/federal\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bu.edu\/federal\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/federal\/wp-json\/wp\/v2\/users\/7048"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/federal\/wp-json\/wp\/v2\/comments?post=4637"}],"version-history":[{"count":3,"href":"https:\/\/www.bu.edu\/federal\/wp-json\/wp\/v2\/posts\/4637\/revisions"}],"predecessor-version":[{"id":4640,"href":"https:\/\/www.bu.edu\/federal\/wp-json\/wp\/v2\/posts\/4637\/revisions\/4640"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/federal\/wp-json\/wp\/v2\/media?parent=4637"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bu.edu\/federal\/wp-json\/wp\/v2\/categories?post=4637"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bu.edu\/federal\/wp-json\/wp\/v2\/tags?post=4637"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}