>> all caps and long, c-span takes on a road to the white house. we have access with the candidates and town hall meetings. news conferences, rallies and speeches. we are taking your comments on twitter facebook and phone. as always, every campaign event we cover is available on our website at c-span.org. the c-span networks feature weekend is full of politics nonfiction books in american history.

the pope's visit to the united states continues today as he travels from new york to philadelphia. live coverage starts at 4:30 p.m. eastern time. pope francis will speak at independence hall. at independence hall it attends the festival families which is part of the world meeting of families. moving to our road to the white house coverage, join a sunday evening at 6:35 eastern as harvard professor and presidential candidates talk about their decision to run for president. and his suggestions to change the political system. and on c-span twos book tv tonight at 10:00 p.m. fox news host bill o'reilly speaks with booknan on his latest killing reagan, an inside look at ronald reagan's political career and the challenges he faces following assassination attempt. on sunday afternoon at 1:00 author and investor doug casey sits down with pope tv in las vegas to discuss his latest book

on politics and economics. in american history tv on c-span3 today starting at 7:00 eastern time. we are live from gettysburg college to mark the 125th anniversary of president eisenhower's birth discussing his military and political career with his grandchildren. sunday afternoon, at 4:00 on filmmerica and archival documenting the 1963 visit of the king and queen of afghanistan to united states. it includes a meeting with president kennedy and a parade through washington dc get our complete weekend schedule at c-span.org. undersecretary of commerce for economic affairs marc dobbs addresses and all day data transparency conference in washington. of how someles agencies like the census bureau, in cities like chicago are using data information to connect communities.

this is 45 minutes. good morning. my name is herschel i am the president of information. i am here to work on the act. as a public and private partnership dedicated to improving government with the application of information technology. provides an ethical form for government and industry executives. we have volunteers from dozens of companies and government but with why people,

panels, and conferences. act i acted.org/data at. i -- introduce arching keynote speaker dr. mark dobbs. for the past three years he served as secretary for economic affairs in the department of commerce. in that role, he a three responsibility. first, mark led the economic administration which includes two of the nation's preeminent organizations. the census bureau and the bureau of economic analysis. these agencies collect and produce information on the united states dynamic and economy. they publish data on the citizens businesses and leaders. analysisu of economic have over 10,000 employees and have a budget of over $1

billion. the second responsibility is being a top economic advisor. they speak extensively on a wide variety of subjects. innovation, immigration and education. his contribution was often about what data can be used to better understand the issue at hand. his responsibility was leading the congress department and data transformation. datade sure the federal was optimized to benefit american businesses, policymakers and people. dr. dom served as the chief economist for the department of commerce. as chief economist he frequently met with business leaders from across the country. listening to their concerns insights and u.s. economy. part two joining commerce he a guide forde monetary reserve systems. he is the leading researcher and expert in innovation

productivity wages, manufacturing and price management. bachelor's in mathematics from the university of maryland. and a phd in economics from the university of wisconsin. basically, throughout his career he either use the data to answer questions or he has made data available sardis can do likewise. he is a data geek. if that introduction was not enough to convince you of that, the fact that he has three separate computers is a testament to that fact. join me in welcoming dr. mark dobbs. [applause] >> thank you for inviting. we're going to sit here for just a second. we will see if this works. there we go. i will say next slide. if we can go to the first slide, what i would like to do is talk

for 25 minutes. we can then open it up to conversations. the main thing i want to talk about today is dated in our country and what role the data transparency coalition fits into that. live in exciting times. if you look at this map, it is a map of street closures in downtown washington dc. this ison i am showing that 10 years ago producing this map would have been really difficult. this map exemplifies a lot of the points that our speakers spoke about. there is a lot of data now. making maps like this is a lot easier than it used to be. there is a huge demand for geospatial information. people always want to know what is happening and where. and how that relates to other points geographically speaking. so, if we think about this

industry we have also seen a huge explosion of the tools to make these maps. we've also seen a huge explosion and the people who have the skills to make these maps. so, it is basically a trifecta. you have people with the correct skills. you have the right tools. and you have the data. with all that combined you produce a better outcome. in this case you can now in today's world produce more and more maps against information that people really need. so when you look at these maps today you need to keep in mind that 10 years ago making these things is very difficult. today it is much easier. again, the concept behind making these maps is difficult. the summary, . it is a picture of my cat.

are at the tipping point. if you think about the data revolution we are at the tipping point of a society. when we think about what is happening over the past few decades will we have really seen is a huge explosion and computer technology. now, with those key components in play we can really take advantage of a huge explosion of data that is occurring. how quickly as is going to happen you go how quickly will we see the benefits of this? that depends on a few things. first it depends on how quickly we make imported data accessible. and why sake sensible, you have about different concepts about the data being in a format. there is a lot of buzzword bingo. also what i have seen repeatedly in application after application

from across this is a wide variety of data. it is not only that you just need the data, you actually need the people who know how to analyze data. int is something that we are short supply of. i will talk about that more later. one reason that people are getting so excited about this is that you always see these graphs. these graphs always have a certain flavor to them. these graphs always have on the vertical axis some measure of data volume. sometimes it is some word you never heard before white terabytes, or something like that. that is always somewhere people use. some huge amount of data. youhe horizontal axis always have why. these graphs have been in the past a predictor of the future. you make a line that shows how much data there is.

the amount of data that is usable by people is accelerating. and usually the arguments that we hear fork celebration that is accessible is first you do not have all the open government data efforts. to everything about the private sector the private sector is gathering and processing more information than ever. what gets people really excited about the future is the internet affect. how much data will be able to be together in sensors. those lines are going to be very huge. so, there is a huge amount of information. information on governments whether it is information on the private sector, whether it is information from somewhere else. the scientific committee for instance. so, the question that i would like to talk to what about is why do we care? basicallyo important? with the data we want something

from it. so, the previous speaker spoke about how we want more sunlight. into how government works. we want better information about how the government is spending its money. i'm an economist. that is my background. i deal with these questions. it is not just can we have more insight, but how is a squid to help our country? if we are thinking about all of this data. dealing with whether we have better knowledge of our citizens what i would like to do is use this simple model. i will go through three simple steps. i'll start with the last one first. it is going to be data, the outcome model. how do we go from data to get these outcome that we want. and then we will simplify it. so, what i would like to do is start at the end and then it go to the beginning.

at the end we want better outcomes. outcomes to be in three buckets. the first one is a call smarter government. speakersthe previous talk about government being better be more efficient. being able to do its mission. we want to do that with less resources. so that is a huge goal. especially given how big the government is. we have another government with trillions of dollars. you have state and local governments. we actually do a census of state and local government. i want to think about a number. how many state and local governments are there? there are 50 states. there are 3000 counties. at any of more after that. everybody think of a number. the number is 91,000. there are 91,000 local governments out there.

there is one federal government 50 cigna governments 3000 county governments. there are 91,000 state and local governments. that is huge. when what smarter government. not just our government but what the previous speakers are talking about. secondly for my macroeconomics expected we want to benefit from the data. they can benefit in two ways. one, they can be more efficient. they can be more competitive. theyby people in this room have businesses in the data like that allow the company's to be represented here. the industry that is important and growing that has a reparative advantage will have a trade surplus. these are jobs that pay very well. this is an industry that we want to support. finally as we heard earlier we

want more benefits of data. of data always think about these three buckets better government, more competitive businesses stronger business community that is where economy grows. or do we want more informed citizens? when we get to the preceding steps we have the data. how do we analyze it? first we have the software tools. we look at the map that we presented in the beginning. one company has most of the market. it makes geospatial data standardized. it is very easy to make these maps. there are a lot of other tools out there.

the first 30 minutes was kind of fun. after that it gets frustrating. i think i'll just hire somebody to do that. the second thing is to think about computer hardware. we have file and storage capacity. we think of these as a commodity. 10 years ago it was a lot more expensive. but the price has really fallen. finally the point of talking about before, human capital. human capital that is an economic race. what it means is the skill of our workforce, we need not a scientist and programs, we also need people to understand what is going on. so, if we got all of the financial data across with government agencies in a standardized format you still need to know people who understand how the government actually works. and, if you can get really large data sets the bigger the data set the more correlations you

will find just by chance. ok? as we get more data you will have more correlations. how do you filter those out to figure out what is going on? that is a large subject matter expertise. why talk to people and health care in the private sector while talking people who are working on criminal justice you can have the best scientists in the world but they have to be couple of knowledge of what is actually happening in the industry. you know, one example of this is where you have that limit. where you have the common sense. i will tell a data joke. there are not a lot of data jokes out there, so forgive me. it is below bar. there are three statisticians narrow hunting. they are out one morning. it is a beautiful day. and they see a buck. 100 yards away. the first data titian gets out his rifle looks at the shot squeezes the trigger. the bullet goes five t -- feet

to the left of the deer. the second set of titian lines shot, rifle takes a bullet goes five feet to the right. the stirred 10 edition packs of his rifle and says looks like we hit it. example ever you need people who not just look at data and understand it they actually have to understand what is really going on. anyone who has any other data jokes let me know. i only have one other i can tell you about later. again, we're looking at goals here that we get better outcomes. it looks like you have a better government. we have to analyze data. need is data transparency coalition's we need the data itself. we need the building blocks.

we use the word integrity often. that is how we know are the data comes from. there is a lot of had data out there. there is an agency i used to oversee. they pride itself on producing high-quality data. exploding yous have to get those answers. we have all the data sets. so it is one thing. is you have to make your data sets easy to find. depending on the day you are it is hard to find information. it exploded in this data revolution. how to make these things

easy to find. and then the ability to merge data this relates to the standard. combining data is where we get the real value. it is when you combine data from here to hear and put those things together. that is where you get thing. there is information on what roads are closed. there is information on the maps to d.c.. combining this things presents a good visual for everybody. as far as how this will impact their community. ok so that is the simple model. i think that all this data stuff there so many words out there. than in the first bucket in when of data accessibility

you do not know what is in the they aret of commerce the folks who monitor us. they're the folks who monitor our ocean. they monitor the solar activity. just their weather data alone. of how dothis problem you get 30 terabytes of data? so, they are working with the private sector. that is a huge physical challenge. how do you make this data accessible? it is a huge problem and we will talk more about that later. they are the good folks who produce the number of gdp. i think a lot of us heard about that.

what are the interactions with the rest of the world? leaving the gdp that is a simple number. they literally release 5 million data point. it is a tremendous amount of information. it is very hard to get this. how can make information easy to get? how can use a data customer quickly find that information? the census bureau is the definitive source for information about the people. the census collects data on people. they care about everybody in our country. when you see data from a lot of these private sector sources the you always have to question is

how is this data representative of the country? pollster whove a does not have access to cell phones, that is a big issue. these numbers can be skewed. think about the last election, there were a lot of polls that were really off. when you are looking at data about people and you're looking at it from the sources, there is a huge question about quality of information. the census does a great job of that at the date is very hard to find. what can we do to make it much easier to find? what is your community look like echoed if you are in the washington dc area it is what does your church look like echoed how does that compare to another church? do they have characteristics you are looking for. you should be able to find that fairly easily. we have pto.

and you are an inventor are making invention at all sorts of things which is hugely important for the economy you have to look at the database. right now, a lot of the data is very unstructured. it is not very readable. data that we have is nonpublic. so come i think for a lot of the data many companies are asking for the financial conditions in terms of financial interactions. there is a strong analogy with the pen trademark. they are sitting on a bunch of data that has not been opened up yet. these are some of these efforts that we are doing with the department of commerce. we want to get the data out there so people can find it. let's talk about the analysis of data. i mention one of the biggest issues we have is a country and the private sector is having a hard time hiring people who have the skills of looking at this

data. so when we looked at this and there were a lot of people in our society, over 10 million, who are really kind of data intensive on their day to day job. there are many people the workforce to work for employers and there are 20 or 30 million people -- 20 million or 30 million people. 10 million people are very data intensive. our society will become more and more data intensive. we need to develop more people with the skills who can actually dataat data and gather sets from it. it goes well belong the shelf. in the department of commerce finding people with the ability to take large data fax and produce something intelligent to that is very hard to do. so, when i talk to my friends in the private sector, salaries are really high. we have to do a good job of educating people.

so, better outcomes. as i said, smarter government. now, we can talk about smarter government's holy long. if i'm thinking from an economic point of view about where we were really use the data a lot, where data can really help data often really helps where there is a lot of uncertainty. we have all had experiences in the health care sector for ourselves. right now, sharing information across the health care industry is very difficult. precision medicine is somewhat impeded by the ability to share information. that is righta for huge improvements. is about 20% of the gdp. this is huge. so if we can improve health care just a little bit we could make

it more efficient. a good friend of mine works in a criminal justice area. there is so much that we do not know about the criminal justice system. when we think about all of these records, and how they do not talk to each other. the criminal justice system is much worse. if you think about all of your state and local law enforcement agencies, even within those agencies data does not work with one another. 3, a celebrated july 4. my car was stolen from my house. i call the police, and they come anyone ever had a car stalled before? the police assume you forgot where you parked it. so, once you get over that and you tell them you were not drinking, and that should drive roger neighborhood to see if they can find it my car action was stolen. then they think it was taken to

a chop shop or it was a joy ride. i was like ok fine. i talked my neighbor. and it's in my car was stolen also. what i did was i went to the government website and the one part of the government that works really well as parking tickets. right? everyone knows this. they are really efficient. she's is what you need to do is go on the website and see if your car gets a parking ticket. if it has a parking ticket that means it was not in a chop shop. sure enough, it did it got a ticket for the license plate removed. the ticket told me exactly where the car was. i went there but the car had been moved. but the data and systems of the parking folks in the d.c. government do not talk to the police department. so, the person issuing the ticket had no idea that the ticket they were issuing to the car that was stolen.

that set an example of the criminal justice system where you have these data systems that are not talking to another at all. there's so much room for improvement. when we think about we have all these big questions today about incarceration what we should do. what our laws should be. one of the effects of all those laws you go we really do not know. it is amazing that we are making such profound decisions by people's lives. in area where we do not know much at l. we're also making big steps with that. we have emerging data. one of the last things i was able to do, was to start this process of merging data with data on their employment outcomes. why do we care about that? we really want to know what happens to veterans when the and

to the workforce. we want to know how that impacts them on how me tors of duty they did. how long your tors. what kind of service he did. what service you are in. we want to know the positions between all of these things. know what the veterans programs should be saved. we do not know how efficient they are. we do not know the outcomes of all these programs. much aboutnow very the efficacy of all these programs. maybe they are all great. a british be funded more. maybe there are some that are having outcomes that we do not like. we just do not know. but by merging the systems together we can find out. i let mentioned, with more competitive businesses. growingomy has been 2.5% for the last few years. one of the big questions we have out there is productivity

growth. most of you probably do not think about it that much. the thing about how fast the economy grows is how fast the labor force growth. how efficient our economy is becoming. so, how efficient are we becoming? we are seeing that productivity growth has been averaging 1%. that is really stumping the growth. while we growing faster? we have a data revolution. there's this big issue we have. maybe the issues that we have all of these businesses and they really cannot get material access to the data. from a macro perspective that is a huge question. so, how much all of the status of that we are talking about, how much can this improve the u.s. economy. i will throw out a rough few rough numbers.

there are a lot of studies that talk about trillions of dollars in trillions of dollars. i find those numbers hard to understand. i studied economy for most of my career. i cannot understand a trillion dollars. maybe warren buffett can. he has yet to adopt me. you focus on these numbers but limited them in context. when you think that all of this data stuff, if this can improve the economy by 1%. think about the type of government we could get from this. think about the improvements we would get the private sector. 1%, that is not much. 1% of gdp is a hundred $75 billion. again, 107 $5 billion. that is hard to relate to. it is such a big number. that is $543 per person. that is up $1300 for typical american household. that is a lot. the media talks about income at $5,200.

that is just if we can improve the economy 1%. let's be a little more optimistic. years thisxt few data revolution will improve our economy by 5%. i still think this is actually a conservative estimate. if we improve it by 5% and you get into one trillion dollars. again, that is a concept that is hard to understand. his exit $700 per person. again, there are about 2.4 people in each household. all of a sudden you're talking over $6,000 per household. so, that is why everything that you are doing, everything that everybody out there is doing in the data space is so important. because the better the information that we have. the better decisions we can make. we can get better outcomes.

our businesses become more productive. they will thrive in the data space. importantly, is we have better citizens that become more informed. would know that that is important as well. let me repeat the main take away. we are at a tipping point. we have more and more data. have groups that advocate to make it accessible. but, how quickly we reap these benefits, these benefits are actually huge. think those numbers are conservative. we will get a huge improvement in the quality of lives. we have to make our data more and more accessible.

we have to invest in this country and the skills that we can take advantage and leverage this kind of data revolution. so, with that thank you. [applause] >> ok thank you. we have time for 10 minutes of questions. i will start out with the first one. you just finished six years and government. in advocating for fact-based decisions. but advocating for high-quality data, what is next? >> this is unfortunate, i do not work for government anymore so i do not care, more seriously, one thing i'm thinking about doing is writing a book. what i would like to do its book

is talk about all of these different areas where data can really improve the quality of our allies. it can really improve our perception of the country. what i noticed across all these event areas, what they are talking about accessibility of data. or the spending side. whether you are talking about health care data, there are all of these common challenges. how do you get all of this data together while maintaining privacy? we have anhand ability to take the data from all these different aspects of our lives, combine it so we can answer these important questions, think about the veterans example, how can we do that? , and maintaining privacy with the perception of privacy? is gettingn public very concerned that the about information the government has on them and also with the private sector has on them.

we don't want to use this data on people for good. , ii had data on veterans could combine that with their labor market, if i can look at their credit scores, i could look at how much debt and they have to whether they can make their mortgage payments. i can better design veteran policies. i can better design programs that are in the public defense. that way they have better outcomes. to do that, i'll have to combine data from a lot of different forces. our society is grappling with the big question about how do you do that, while maintaining privacy? and this perception of privacy on the one hand people giving a lot of private data, their personal data to private companies like facebook. they know a lot about me. facebook provides me service in return. to the government doing this, or even the private sector getting more data on us, there is a real fear. i think we need to find a balance.

the more data we have come of the better decisions we can make. the more data we have the better we can heighten society. how do we change the conversation to do this? this is something i would like to really work on. that if we cannk leverage all the information out there, we can really move the social media: quite a bit. -- neil quite a bit. >> if you have a question we have a few microphones. >> hello i am paul with the center for organizations. i go back to your domes model. one of these things i noticed was that was absent was in the very beginning the envisioning or the hypothesis making before this data is examined are collected. so, to the extent that data analysis, and data decision-making is a science, to

what extent does there have to be active manipulation in terms of service manipulation to get the information you need? to make sure the decisions are the correct decisions. >> that is a great question. when it comes to hypothesis testing, that is very hard. is where you really need the expertise. and, you will find lots of correlations. phrase we have all heard this is correlation does not equal causation. there are many examples of that. will happen is that you have seen this before. it is a process that goes back and forth. data, and you say what hypotheses can we touch with that data? we think what is it that do i want? you go collect that data. and then has anyone used the data before. they say that was really cool.

however the number of questions begins to multiply. so, i think as a country we tend to be more adept at saying ok this of the information we have. this is what we can learn from it. we also have to ask the questions of the hypothesis that we cannot answer. sure that we make come at it from both ways, from hypothesis of data and the data back to the hypothesis. >> out of the room. way over there. run, run. >> hello. i think it a lot of really good points. you said 91,000 local governments. the potential impact of every citizen the country. usually when we talk but up and data we talk about the national level. or a broad scale. in your opinion, what are ways to make this work the way that every citizen or business even the smallest local government should consider how they change

their policies in terms of making data acceptable. that way they can improve the local outcomes. so, this is fascinating. i think we have a lot of groups here to represent the local government. we spoke to lots of different local government organizations. and, what the previous speaker said was that some big cities released data in a very good way. there is one or two companies here. localorked a lot with governments and to make their data accessible. i think local governments are still in the early stage of management. what do people want? i, would leadnd to chicago. and, they have this active , would you call the

neck of hack a sans. these once a month. there would bring in people, it's a here is our data, do what you will. i think they found that sometimes there were data sets were people said there's not much use for that. sometimes there were data sets that they found very interesting. of for instance one example good local governments of in chicago is that if you take a picture of a puzzle, you send it into the works department. it works with the department's website. they are accountable for filling it out. whense, everybody knows that pothole was posted onto the website. that was a great example of making information available and accountable to addressing the concerns. is thatlenge we face

with some local governments. many of them do not have the resources to do the same thing. we talk about keeping did open and analyze. governmentsse local are just really hamstrung. one of the biggest drags that we have on our economy, and the recession with in the state and local government sector. they are really hurt because of the housing crisis. the property values went down. so, i think what is happening with the state and local government level is that you have some that are really in the vanguard. some that are not. the ones that are not there not because they are hamstrung. so, maybe what we really need is a standard suggestion the best practice. now that we have been

doing this for a few years with some of the larger entities, i think we're the best practices. i've spoken to many of these local government agencies. they get this, at the state local government level, i think it is the human capital strength that they need. >> here in front. >> thank you so much. i am helen. i am the director of intergovernmental relations for the association of government accounting. one of the questions that i have in the human capital aspect that came up in the last question is relevant to this. all of this data stuff as you mentioned is taking place at the are time where people getting frustrated with the cost of higher education. we needhe same time,

people trained in this data stuff. what implications do you think that has for our educational system, in terms of the best way to educate people. people who are knowledgeable on the data stuff? >> one thing the administration pushed on the federal level is the committee college system. if you look at community colleges across the country, i think they are doing an increasingly better job working with local businesses to match the skills of workers with businesses. when you survey businesses would you often see is that there is a skill mismatch issue. the business says we are not hiring because we cannot find people at the correct skills. so, how many millions of people are in that mismatch category? it is literally in the millions. so, when we are thing and i get any skills.

we have to think outside of the traditional four-year college degree. also there is the concept that society always presages -- pushes his lifetime learning. how can you any skills? i think this is a data processing our language. that, is therised number of online courses. they basically do not cost anything. that requires a certain amount of dedication. and also, i happen to know a lot of people who know about this. they can get pointed in the right direction. but, fundamentally we know that the cost of higher education has been raising for the past few decades. it is a drain on the economy. it is very defined. i think one of the big answers to your question is the commuter college system. it is really huge. you see also at colleges in your

first year now, you take a computer programming course. it is a way to think. it is something that everybody should be familiar with. when i was in high school i took this for instance. that was accepted, that was not the rule. what can we do to teach kids today something about coding. when i was undersecretary you travel around a bit. there are a lot of these camps were kids would make an app. it makes it really fun for kids. i think the way computer science used to be taught was done in a really nerdy way. it was very exclusive. is this not where you get your education. , how this stuff is taught. it is very fascinating. different people respond differently to different types of education.

>> that was great. thank you. that was great to wrap up. our keynote. thank you. [applause] >> today, our live coverage of pope francis continues in philadelphia. at 4:30 p.m. eastern he will speak at independence hall. at 7:30 he will talk about the festival of families. you can see both of the events live here on c-span. on thursday the senate intelligence committee heard from nsa director and u.s. cyber command or admiral michael rogers. he addresses the massive data breaches at sony pictures at how they're dealing with terrorist threats, and how to make the nsa more proactive in terms of threat response. this is one hour 25 minutes.