To start your search click on Get Started in the center of the page or Search in the top Menu selecting the option: Start a Search.
On the following page you can start your search in two ways: by choosing your profile (there are three available profiles: Entrepreneurs, Development Agents or Students and Professionals) or by one of the three available search items (search by products or by occupations, e.g.).
Search by profile:
Select one of the three available profiles. A selection box will open and you will be able to choose exactly what you are looking for on the search box by writing a keyword or by selecting one of the available questions. After selecting the desired question, click on Advance. Specify your search on the next option. There will be other options in the heading, surf between them to choose exactly what you want by clicking on the options opened under the heading and click on Advance. Your search results will be displayed on the following page.
I am an Entrepreneur and I would like to know how many Wholesalers are there in Recife.
I start a search by profile by choosing my profile: Entrepreneurs.
I click on the most appropriated question to my doubt: How many establishments in the Activity X are there in the Locality Y?
I click on advance.
I would only like to know about the Wholesalers, so I search wholesale by typing it on the textual search.
I select Wholesale and click on Advance.
As I would like information specifically of the city of Recife, I select the option Localities in the top menu. I type Recife on the search box and select Recife following by Advance.
My search results will be shown on the following page.
Search by topics:
Select one of the available options, e.g. Products. Select on the heading one of the options (Sections or Positions in the case of Products). Right below you will be able to start a search by keyword on the search box or by locating the desired item and clicking right on it. After choosing the item your search will be displayed on the following page.
I would like to know about the commercialization of hats in general in Brazil. I click on the option Products and type Hat on the search box of the positions tab. I select hats and wait for the next page to load.
My search results will be shown on this next page.
On the top menu of the homepage click on Search followed by the option View Rankings.
On the following page, you can select one of the available options on the menu of the center of the page to build the desired ranking.
The first line of the ranking is sortable. You can select one of the titles to sort in an ascending or descending order.
On the top menu of the homepage click on the option Search followed by Make Graphs.
On the top menu of the homepage click on the option Search followed by Database Download.
Select the desired database.
Choose the year of reference.
It is not necessary to choose a filter but if you would like to filter by location and/or course, select one of the options on the selection boxes available on the Filters field.
Click on the Download button located on the right bottom of the page. The download will start promptly.
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Fill out the form by typing all the required information with your name, e-mail, subject and the desired message.
Click on the Send button located below the Message box.
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Click on Studies on the top right menu of the homepage.
Click on the Publish a Study button located on the left menu.
On the following page, you must fill out all the required fields. Do not forget to indicate the Title, Language, Author(s), Keywords, Category/Theme and the Description/Draft of the study.
You must also send us a PDF file of your study by clicking on the Select File button. On the select file dialogue box find and select your file.
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Click on Blog or News on the top right corner menu of our homepage and that is it! You will have access to our blog and news.
Check out our news and blog and feel free to leave a comment and share all the information you want.
No. DataViva is a totally open data visualization platform and therefore does not demand any type of registration. The login area was created to improve the interaction among the site users and its developers. In this area is possible to save graphs, visualize your search history among other tools. So, if you would like further information and have access to your search history in our site, register now. When you log in you will also receive our newsletter.
We would like to broaden our partner network and make DataViva even better. To be our partner click on Partners on the top menu of the homepage. Check out the main topics of interest for partnerships within the DataViva project and click on Be a partner. The partnerships are formalized through a specific instrument and always after a Public Call. On the page Be a Partner you will have access to the opened Calls and the previous Calls.
If your idea for partnership is not in any of the Opened or Previous Calls contact us on the Contact link located on the top right corner menu of the page.
You can download any graph built on our site. You only need to click on the floppy disk symbol (Download this Visualization) located on the top right corner of the built graph.
The database was provided by Ministério do Trabalho e Previdência Social (MTPS) – the Brazilian Ministry of Labor and Social Security – and Ministério do Desenvolvimento, Indústria e Comércio Exterior (MDIC) – the Brazilian Ministry of Development, Industry and Foreign Trade. DataViva presents data related to the exports of 1,256 products of the Brazilian Secretariat of Foreign Trade – Secretaria de Comércio Exterior (SECEX/MDIC) – 865 occupations in 427 economic activities of the Annual List of Social Information – RAIS/MTPS – and enrollments of 236 Technical Courses and 255 Higher Education Courses of INEP/MEC.
Open Data refers to data that is available and can be used freely by anyone, without restrictions or control mechanisms.
The databases used in DataViva are updated annually.
Since the 90’s, the term “Big Data” has been used to describe a huge volume of data that challenges the capture, processing, analyses, and computational storage limits. The goal is to generate knowledge from this set of complex data. It is not enough to have access to this big amount of data, it is also necessary to know how to understand it, so that the potential of Big Data materializes.
The "Product Space" is a methodology created by professors Cesar Hidalgo (MIT Media Lab) and Ricardo Hausmann (Harvard Kennedy School) which allows a greater understanding of the productive knowledge a nation has, based on their exports. The capabilities or abilities they have include a range of factors like: capital, labor, technology, institutions, infrastructure, and social relations, among many others. The more productive knowledge a location has, it can produce and export more products, and more complex ones. In a graphic way, the "Product Space" shows the connections among products exported worldwide, based on the probability of co-exportation. This probability is also used to reveal the number of capabilities, or productive knowledge, these products share. Products that are very connected and have many shared capabilities tend to be in the center of the network (the Product Space), where there is a higher concentration of complex products – in other words, products that demand a higher number of abilities to be produced.
Users’ personal information will not be disclosed, nor will it be used in the platform. The purpose of logging in is to allow discussion in the Contact Us section and to bookmark specific apps for later viewing (using the "Star" button on each app).
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The Data app is in a Pivot Table format that allows direct access to the raw data used in the platform, offering users the possibility to manage the data according to their own interests and aims. It works in a simple way, the user selects one database, the year and the variables they would like to see and clicks “Build”.
Data based on exporting municipalities register products exported from the county of origin of exports. In turn, data on producer states record exports to the Brazilian state that produced the product, which is not necessarily the same state of the municipality from which the product was exported. This difference is present in DataViva and is the reason why two different values for the total exports of a state can be shown in the visualizations (note the description in the title of the application to know which record is being showed). (Translation of a question asked in portuguese)
Yes, there is API documentation for dynamic queries, follow the link: https://github.com/alexandersimoes/dataviva/wiki/Api (Translation of a question asked in portuguese by Raquel Camargo)
The system was built using Python technology with the development framework called Flask. All calculations are done using Python with scientific libraries such as NumPy. The display of graphics is done via HTML 5 and CSS3, through D3Plus library, D3 framework based on Java Script language. (Translation of a question asked in portuguese by Osvaldo Carvalho)
The RAIS microdata is not available for download in DataViva. For technical questions, the platform provides only aggregated data and metadata for some of the analysis variables (stock employed by the municipality, average salary, wages, ungrouped yet to economic activity and occupation). However, the MTE provides microdata to download on its page, go to: http://portal.mte.gov.br/portal-mte/ (Translation of a question asked in portuguese by Valter Eduardo)
The distance of a given economic activity to a location c is calculated as the sum of all proximities between c and other activities that exist in C, but having RCA greater than 1. This number is normalized by dividing it by the sum of all the nearby activities that exist in the location c for economic activity p. To the formula for calculating the distance, please refer to the book The Atlas of Economic Complexity (page 54) Available in http://atlas.media.mit.edu/publications/. (Translation of a question asked in portuguese by Bruno Gonçalves Ferreira Santos)
Annual Social Information ReportMinistry of Labor and Employment - MTE
RAIS is an annual administrative record conceived to supply the necessities of control, statistics and information for governmental entities in the social area. It constitutes a fundamental instrument to attend legal norms and is important to characterize and track the formal labor market. It depicts the Brazilian formal market by data provided by all businesses based on their standing on December 31st of the previous year. This includes data about employees and industries, among others. Currently, according to IBGE, RAIS covers about 97% of the Brazilian formal market.
DataViva presents information about the number of jobs, wages and number of establishments. The level of aggregation, in geographic terms, is available for Brazil, States, Mesoregions, Microregions and Municipalities; in sector terms, Sections, Divisions and Classes, according to the National Classification of Economic Activities (CNAE); and in terms of occupations, Main Groups and Families, following the Brazilian Occupations Classification (CBO 2002).
Foreign Trade Secretariat DatabaseMinistry of Development, Industry and Foreign Trade - MDIC
The SECEX/MDIC database allows historic analyses of the Brazilian international trade behavior, one of the most important indicators of economic development. It depicts and evaluates the commercial movement of the country with all of the others nations in the world, comprising import and export transactions. It also constitutes a basic instrument to decision making and helps determine economic guidelines by the government. Moreover, the database enables the agents involved in these activities to better plan their actions by analyzing empiric export and import data, enhancing the opportunities to develop international trade.
DataViva presents monthly information about Brazilian exports and imports since 2000. The main variables are: value, producing state, exporting municipalities, and origin or destination (country). Data is available for the following aggregations: in geographical terms, Brazil, States, Mesoregions, Microregions and Municipalities; and by products in Sections and Positions, according to the Harmonyzed System (HS Code).
National Institute of Educational Studies Anísio Teixeira - INEPMinistry of Education - MEC
This is the main basic education information collection instrument, covering its different stages and types: regular education (children's education and elementary and high school), special education, and youth and adult education. The School Census collects data on institutions, enrollment, teaching functions, movement and school performance.
DataViva presents information on the number of enrollments, by year for all basic education, aggregated by county, microregion, mesoregion or states. Data on vocational courses can also be viewed, in this case specifying the course in the same geographical levels of basic education. Schools are also divided by type of administrative category and the courses can be filtered by period of day.
The Higher Education Census gathers information on higher education institutions, their undergraduate courses on campus or distance, sequential courses, openings offered, registration, tuition, freshmen and graduates, in addition to information about professors, in different forms of academic organization and administrative category.
DataViva provides information about students (freshman, enrollment and graduates) for all higher education courses, organized by location or by universities. The aggregation levels for the locations are municipality, microregion, mesoregion and state. The universities (and other academic organizations) are also broken down by type of administrative category.
United Nations Commodity Trade Statistics DatabaseUnited Nations Statistics Division
The United Nations Commodity Trade Statistics Database (UN Comtrade) has detailed data about imports and exports informed by statistics authorities of about 200 countries or areas. UN Comtrade is considered the most comprehensive international trade database available, with more them 1 billion records. The database is constantly updated. As soon as new data is received from national authorities, they are standardized by the United Nations Statistics Division and then added to UN Comtrade.
DataViva uses the follow information to make international comparisons: origin and destination of exports and exported value detailed by position. It is important to observe that the data is not available for visualization, being used only to calculate some indicators in DataViva.
The Tree Map is a descriptive visualization which allows visualizing participation, in percentage terms, of the different variables available in DataViva. For example, this visualization allows analyzing the importance of a product in the exports of a location. Tree Maps are built with blocks that are proportional to the participation of selected categories in total, and grouped by colors representing the major groups for each variable (or another color coding selected by the color filter).
The logic of the Tree Map is the same used in a pie chart or other visual representation of distribution. The use of squares grouped by major groups in order of importance allows a quick view of items with greater participation in the respective large group, in which it is contained, enabling a fast and simple analysis of the percentage of participation.
One of the visualizations, for instance, shows the participation of each of the products in Minas Gerais export basket, revealing quickly and easily the significant participation of the product Iron Ore in the exports of the state. Several other views are possible, using the variables available in the platform such as economic activities, occupations, localities and intersections between these variables.
The Stacked visualization allows analyzing the growth of a variable over time. Built as an area chart in which the height of each line represents its share in total or gross, this view follows the same color pattern of the other visualizations, facilitating the identification of large groups to which each item belongs. Therefore, this visualization facilitates an understanding of the growth patterns and trends of any of the variables available in DataViva.
The purpose of this visualization is to allow the visualization of the data in a time series, revealing product, economic activities, occupations or localities with greater participation over time and its history of growth or decrease, either in gross or percentage.
One of the visualizations, for instance, is for economic activities of Minas Gerais, revealing the overall growth of the state economy and which sectors had the greatest contribution to this growth since 2002. Like the other visualizations, you can modify the data displayed for any of the basic variables available in DataViva (products, activities, occupations) and their intersections with localities all over Brazil at different levels (regions, states, mesoregions, microregions and municipalities).
The Geo Map is a descriptive geographical visualization that enables an analysis of the spatial distribution of the variables available in DataViva. Using a heat scale, it shows the municipalities with the largest (in red) and lowest (blue) values, and allows navigation both to zoom in and out, as to see more information about a selected municipality. This visualization aims to reveal the geographic distribution of the data.
One of the visualizations, for example, shows the economic activities in Minas Gerais by municipality, showing its concentration in the Metropolitan Region of Belo Horizonte. As in other visualizations, you can change the visualization to the desired variable with the filters.
The Network visualization displays the original Product Space, using the same network of products created by professors Hidalgo and Hausmann based on worldwide exports. It represents the connections between products in terms of the probability of co-exportation of these, and is the basis of the theory of economic development proposed by these professors from MIT and Harvard, respectively. In DataViva one can also visualize the “Industry Space”, a representation of the connections of all Brazilian economic activities based on their shared occupations.
This visualization allows highlighting, in the Product Space or the Industry Space, all products or activities in which a region has Revealed Comparative Advantage (RCA>1). Therefore, one can see where are the products or activities in which a region has comparative advantage, if these products or activities are in the central region of the network (are more complex) and what are their connections.
This is a prescriptive visualization that reveals interesting ways for the economic development of a region based on the Product Space theory. According to this theory, a region must move (gain comparative advantage) to products or activities located in the center of the network, starting from those products or activities in which it already has comparative advantage.
One visualization, for instance, on DataViva, is the Industry Space of Minas Gerais, allowing to quickly learn in what activities the state has comparative advantage and in which categories they are (from the same color pattern used on all visualizations).
For a better understanding and interpretation of this visualization, it is recommended to check the terms and basic concepts of the Product Space theory.
The Rings is a prescriptive visualization that allows viewing a product, industry or occupation in isolation, making it easier to navigate round its primary and secondary connections, which can be a bit difficult in the Network visualization. It also shows those products, activities or occupations in which the selected location has revealed comparative advantage (RCA> 1).
This is important because, according to the Product Space theory, having comparative advantage in a product means that the region has the expertise to produce it and the knowledge that is shared in the production of connected products. Thus, one can visualize, quickly and easily, if the product has many connections and if these are with products that the region already has comparative advantage, which would facilitate its development, because it means that much of the productive knowledge needed is already present.
Similar to other visualizations, Rings uses a standard color pattern that lets one see of which big group a product, industry or occupation belongs, as well as other groups with which it is connected. Correctly understanding the concepts of the Product Space theory is fundamental to interpret this prescriptive visualization.
One of the visualizations, for instance, shows the connections for biologists in Minas Gerais, therefore we can analyze the occupations connected to biologists directly or not.
The Scatter visualization is another prescriptive visualization which allows comparing the distribution of economic activities and exports of a location based on the relationship between two variables (one on the X axis and another one on the Y axis). This graph facilitates the analysis and definition of the more interesting activities and products for the economic development of a region by putting together two indicators of the Product Space theory.
For example, to determine which product would be more interesting for the development of a location, one can use the Scatter visualization to analyze simultaneously the indicators of complexity and distance of a product from the current production structure of this location. Products with higher complexity and lower distance will be located in the same quadrant of the graph and those would be, in principle, the ones with the greatest potential for the location.
One visualization, for example, shows the economic activities of Minas Gerais and its plot distribution considering the distance (x-axis) and the unique occupations (y-axis). Note that Construction is the group of activities with the highest number of unique occupations and one of the smallest distances to the state, while Financial Services & Insurance is the group with the smallest number of unique occupations and greater distance. Hence, the visualization allows easy analysis of the activities and products of a region from the intersection of two of the indicators calculated based on the Product Space theory.
As in other prescriptive visualizations, it is recommended to know the terms and concepts of the Product Space theory to make a correct interpretation of the visualization.
The eighth DataViva visualization aims to facilitate comparison between two different localities and works the same way as a scatter plot. Each locality compared occupies one of the axes of the graph and the values of selected variables are distributed in the same scale, creating a diagonal line where the values are equal. We can thus compare the values of the variables available between two localities (municipalities, regions and states) in a simple and visual way.
One of the visualizations is a comparison of exports from Minas Gerais and Rio de Janeiro, revealing that Mineral Products is a leading category for both states, with very similar values, since they are located near the diagonal line of the graph. Some other products like Arts and Antiques are exported significantly more by Rio de Janeiro state, while products such as Precious Metals are exported mostly by Minas Gerais.
These comparisons can help with finding other reference localities or determining the most interesting localities for a particular investment or economic activities which are more concentrated in certain regions. Compare creates visualizations with the main variables available in DataViva (products, activities, occupations) and reveal or confirm hypotheses about differences or similarities in the variables selected between two Brazilian localities.
The Occugrid deals specifically with RAIS data regarding occupations in Brazil. The goal is to show graphically which are the main occupations employed in various economic activities, their importance to each industry and the number of employees who work in these activities. Prescriptive in nature, this visualization compares the location in question with a reference calculated from the definition of other similar localities in terms of economic structure. Consequently, it enables, in a single visualization, the ability to know what are the main occupations of an industry, how many professionals work in comparable localities, how many professionals work in the region, and how many of them work specifically in that region and industry.
This type of visualization allows an analysis of the labor market of a region, the professions needed to develop an industry, and, in conjunction with other visualizations about economic activities and occupations, links occupations and economic activities (which may also be related to the products they manufacture). It is also an initial step towards an analysis of human capital training needs in a locality, revealing shortcomings of qualified personnel and its importance for the economic activities analyzed.
Unlike the other visualizations, the Occugrid allows only one type of output, because it was created especially for the analysis of occupations (and related economic activities). However, the output can use different parameters and types of grouping. One of the possible visualizations shows the average number of jobs per establishment for Restaurants in Minas Gerais.
The Line visualization allows analyzing the change of a variable over time. This view follows the same color pattern of the other visualizations, facilitating the identification of large groups to which each item belongs. Therefore, this visualization facilitates an understanding of the growth patterns and trends of any of the variables available in DataViva.
Like the other visualizations, you can modify the data displayed for any of the basic variables available in DataViva (products, activities, occupations) and their intersections with localities all over Brazil at different levels (state, region, municipality).
One of the visualizations, for instance, is for economic activities of Minas Gerais, revealing the overall growth of the state economy and which sectors had the greatest contribution to this growth.
The Box Plot visualization allows analyzing the change of a variables range across a series of distinct points. Each box represents the IQR, or Interquartile Range for a series of data. This range is defined by the first and third quartiles, with a bisection line repesenting the median. Whiskers extend from the IQR to show the minimum and maximum values for the data series.
This visualization is helpful when showing wage distribution over time, or age distribution across different education levels. As example, we can take the wage distribuition in Minas Gerais. Even having a discrepancy of data for the maximun and minimum value is possible to understand the wage distribution for most of employees.
The Bar Chart visualization allows analyzing values as a histogram. The y-axis represents the frequency of occurances in each bucket display on the x-axis. The buckets are calculated from two times the standard deviation above and below the mean value.
This visualization is helpful when showing wage distribution for a single filter, such as location or occupation. One possible visualization, show the wage distribution in Minas Gerais. It shows the total employees (the frequency represented in y axis), for which wage range (wage data represented in x axis). Therefore, is evaluated the employees number for which wage range.
Product Complexity (PCI)
The Product Complexity Index is based on two main concepts: diversity and ubiquity. Diversity refers to the number of products that the region exports with comparative advantage. Ubiquity is the number of regions that export a given product with comparative advantage. The index is based on the idea that more complex products are produced and exported by a smaller number of regions, while requiring more productive knowledge to be manufactured. Therefore, more complex products are those produced by few regions that produce different products.
Economic Complexity (ECI)
The Economic Complexity Index measures the diversity and complexity of a locations's economy. It is calculated by taking the average complexity of the products a location exports with international comparative advantage, weighted by their share in the location's overall exports.
If it is of interest, the formulas for the calculation of these indices can be found at: https://atlas.media.mit.edu/atlas/
Distance is a measure of how far the current production structure of a region is in relation to a given product, signifying the difficulty of this region to achieve a comparative advantage in this product. The idea here is that each product requires a set of capabilities, which may or may not be shared in the manufacture process of other products (proximity). Products closest to other products in which the region already has comparative advantage will be more easily developed - because some of the required knowledge is already present in the region. Distance is a measure that reflects the amount of new capabilities that a region needs in order to manufacture and export a product with comparative advantage, meaning that the greater the distance, the more knowledge that needs to be acquired and the longer (or more difficult) it will be to have advantage in the export of this product.
In DataViva, distance is calculated considering both world trade (International), and just Brazilian exports (Domestic).
The number of unique municipalities where a given variable is present.
The number of unique 6-digit CNAE industries that are present for a given variable.
The number of unique 4-digit CBO occupations that are present for a given variable.
The number of unique HS4 products that are present for a given variable.
Export Destination Diversity
The number of unique import countries that are present for a given variable.
Effective diversity is the diversity of a given variable corrected for the share that each unit represents. For instance, if a location exports two products and each of these represents a 50% share, then the effective diversity is 2. However, if these shares were 99% and 1%, then the effective diversity would be 1.058, which is close to 1, since this is a location that exports primarily one product.
The importance of an occupation shows how often this occupation is employed by establishments of a given industry. The number of employees is not considered, just that the establishments of an industry employ the occupation. It is a calculation percentage, for example, if the importance of an occupation is 0.4 in an industry, this means that 40% of the establishments in this industry employ that occupation.
Opportunity Gain is an index that measures the increase of economic complexity that a product will give a region, meaning, the contribution of a given product to the complexity of the region economy. In other words, the Opportunity Gain measures the new capabilities that will be acquired by a region if it develops comparative advantage in a given product. The idea behind this index is that each product can contribute in varying degrees to the economic development of a region, adding new capabilities and, consequently, reducing the distances of other products (that have shared knowledge) in relation to the economic structure of the region.
In DataViva, Opportunity Gain is calculated considering both world trade (International), as just Brazilian exports (Domestic).
For economic activities, it is calculated only for Brazil. This calculation is made considering the diversity of occupations, meaning that the Opportunity Gain reveals the contribution of a new industry (development of comparative advantage) to reduce the distance in relation to other activities with a high diversity of occupations.
The proximity between two products is the main index used for the creation of the Product Space, being a measure of the probability of product co-export. Using global export data, it estimates the probability of a product being exported by a country that also exports another specific product. This calculation is made for all products of the standard international trade classification (HS 4-digit level). The products most likely to be co-exported are considered connected in the network, based on the assumption that they share capabilities required for their manufacture.
To build the "Industry Space" and the connections between occupations the same reasoning is used. The proximity of the industries is calculated based on the probability of co-occupancy between two activities, meaning that it is a measure of the probability of two industries having the same occupations, and therefore requiring common capabilities. Similarly, the proximity of occupations is calculated based on the likelihood of these being employed in the same industry, revealing a productive knowledge that is used in various sectors of the Brazilian economy.
The Revealed Comparative Advantage (RCA) shows the share of exports in a region of a given product in relation to the participation of this product in the world trade. In other words, the RCA measures if the share of a product in the exports of a region is larger or smaller than this product participation in the international trade. If the participation is equal, the RCA will be 1, meaning that the region exports exactly the "fair share" for all regions (an average share of the total exports divided by the number of regions). When the RCA of a region is larger than 1, it means that this region exports, in percentage terms, more than the "fair share", meaning that it has a comparative advantage in the export of this product in relation to other regions.
In DataViva, the calculation of the RCA is made considering the global trade (International), and just Brazilian exports (Domestic). For industries, the RCA is calculated only for Brazil, following the same participation logic. An RCA greater than 1 in an industry means that the region has a larger share than the average in that industry, in terms of number of employees.
Estimated Employment is a reference to the number of jobs, by occupation, in a given industry. This reference is calculated by defining similar regions to the region examined, and then finding the average number of jobs in these regions for the select industry.
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