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open data

  • Glossary

"Open data"

This glossary explains various keywords that will help you understand the mindset necessary for data utilization and successful DX.
This time, we will introduce new ways of thinking about data, including how data is being used throughout society and how it will become increasingly important in the new relationship between local governments and residents in the IT era.

What is open data?

Open data is an initiative to make data freely available and publicly available, thereby facilitating widespread use of data.
There is a lot of data in the world created by public institutions and other organizations, but before the advent of the Internet, it was not being fully utilized in society. Efforts have been made to make such data available online so that it can be widely used and useful in society, and the data made public through such efforts has become widely known as open data.

How to utilize data held by public institutions in society

What image comes to mind when you hear the term "open data"? Many people may think of it as data that is publicly available on the internet and can be used for free. Open data is not just data that is publicly available, but also data that is "publicly available with consideration for open (free) use," i.e., without any restrictions on data use.

Furthermore, open data is an important "concept" for realizing a society in which data is utilized as the world becomes increasingly IT-based. It is a concept that is likely to become important in the future, whether we are using data to engage in data analysis or creating an environment in which data can be utilized.

Large amounts of data held by public institutions

Even before the advancement of IT, public institutions such as government ministries and local governments had a lot of data. For example, the Geospatial Information Authority of Japan surveys and creates maps of the entire country of Japan. Public surveys such as the population census compile statistics on where in Japan people live (gender, age, etc.), and how many of them there are. In addition to the results of social surveys, there is also a lot of data, such as the results of scientific surveys (for example, weather observations, oceanographic surveys, and space exploration).

Much of this data is also useful for private sector use. For example, map data and weather forecasts are useful in many ways, and there is a lot of data that can be put to use, such as being able to refer to data on the age and gender of people living near a certain station, which can be used to determine in which areas your company's products are likely to sell.

This data was created with the tax money of the Japanese people, and it would be preferable for the data to be widely used for the development of the Japanese people and Japan, rather than simply being stored. If that is the case, then unless there are circumstances that prevent the data from being made public, such as privacy concerns, it would be desirable for it to be made widely available and used.

Furthermore, there are times when "data that can only be prepared by public institutions" is necessary for the development of society. There is "data that can only be produced by public institutions," such as data that requires extremely large-scale activities, such as surveys across the entire country of Japan, and there are also times when "data provided by neutral and reliable public institutions" can be useful because it can be used with everyone's trust and is used as a common foundation for social activities.

Publication via the Internet

Useful data created by public institutions has been around for a long time, and it has been made publicly available for use by society. However, before the IT age, this data was often made public in paper form, and even though it was made public, it was not easily accessible.

However, we now have the Internet. If public institutions continue to digitize data they hold and make it available online, a much larger number of people than ever before can access the data. Around the turn of the 21st century, a global movement began to gain momentum to "make data held by public institutions publicly available on the Internet in principle." This movement came to be called the "open data movement," and the data that was made public came to be called "open data."

In Japan, too, since the 2010s, the concept of open data has become widely known and efforts have been made to promote it by the government and local governments, and now a large amount of data is made public and available for use.

Open data in future data utilization

Currently, efforts to utilize data are becoming increasingly popular in business. When we think of data utilization, the first thing that comes to mind is efforts to collect and analyze data within a company, but the use of open data is also important in business.

Business is not something that can be done by one company alone; it is necessary to understand customers and markets, in other words, to understand "the world." Data created by public institutions is exactly "data about the world." For example, if you want to know about the people living in Japan, or the state of the Japanese economy in each industry, you should be able to obtain data from open data in a volume and with a level of accuracy that would be impossible to obtain through your own data collection.

Utilizing open data to realize the future

If we imagine a future where IT advances and entire cities are digitized, the intelligent city of the future will see "data being used freely throughout the city." For example, a large amount of data will be used throughout the city, such as information on transportation and other information related to movement within the city, weather, congestion, and the current state of the city, such as construction and accidents. A situation in which data is used throughout the city will mean that a large amount of data is made public as open data and used in an advanced manner.

Open data can also be a means for local governments to realize "new relationships with residents."

First, data disclosure is a means of achieving transparency and efficiency in government administration. If the state of the world is made public through data and the actions of public institutions are made public, residents will be able to use the data to judge for themselves whether what the government is doing is appropriate.

It will also become possible to approach the "digitalization of government administration" from a different perspective than before.

Traditionally, local governments have attempted to develop websites (or their own smartphone apps) so that various administrative procedures can be carried out online. However, this approach takes time and money, and in reality, the services created by local governments are often not easy to use.

Instead, local governments should make the original administrative data itself available as open data (or administrative-related APIs).ico-external-link.svg) and residents can use the released data in creative ways, which could lead to a new relationship between the government and residents.

For example, if you ask what day of the week garbage collection is, the conventional way is for local governments to post the information on their websites (which users have no choice but to put up with even if it's difficult to use), but it should be possible to make raw data about garbage collection available as open data, and have residents create apps that can read and use that data conveniently. This would be more convenient for residents than before, and would reduce administrative costs for the government.

If such data disclosure were to progress beyond local government boundaries, it would become possible to open a smartphone app anywhere in Japan and instantly find the nearest garbage collection point using GPS location information, and even to have an app that would check garbage collection days, how to sort garbage, etc. In this way, citizens could participate in government through the use of data, potentially making the world more convenient, without incurring any costs to the government.

Such a future could come true for your business.

These "possibilities for new relationships" are not limited to local governments. For private companies, too, "new relationships with business partners and customers" through open data and APIs are likely to expand in the future, and companies should be able to work on disclosing their own data as a way to make this happen.

However, open data is fragmented

Open data has a lot of potential, but it can be difficult to actually use it. In any case, many things are "disjointed," and it is often time-consuming to utilize it.

How "falling apart"

Because the data was created and made public by various organizations, the methods of publication, data formats, and data contents vary. Data may be provided in a variety of ways, such as by manually downloading it from a web page, via API, FTP, HTTP, or as an email attachment. Data formats also vary, including Excel files, CSV files, XML files, and PDF files.

Even after receiving the data, it's still a lot of work. It's common for Excel files containing the same data to have different formats depending on who created them. There can also be many differences in the data itself, such as differences in Japanese character encoding, date data formats, Japanese and Western calendars, numerical values with different units, whether numbers are comma-separated or not, the number of significant digits in the data, yen and dollar conversions, and prices excluding and including tax.

Data analysis can require the effort of referencing a large amount of data, determining the necessary parts, and collecting them. For example, if market forecast data is divided into files by fiscal year and weather forecast data is divided into files by year, and you want to combine and analyze them, it can be a bit of a hassle. There's also the hassle of having to check when the data is from (not all of the data is necessarily the latest).

The reality of open data utilization is that data is used in a fragmented manner

In other words, utilizing open data means collecting and utilizing data that has been made public in various ways all over the Internet. Since open data comes from various places in the world with fundamentally different circumstances, it is inherently difficult to resolve this disparity in advance.

For this reason, before engaging in data analysis using open data, it is often unavoidable to go through the effort involved with the "disjointed data," such as investigating or deciphering how the data is stored, converting the data according to its intended use, and combining multiple pieces of data. How to deal with this can be a key factor in utilizing open data.

Useful "connecting" technology for utilizing open data

In other words, in order to promote the use of data using open data, it is necessary to create a data usage environment that can effectively process ``disparate'' data, efficiently obtain the necessary open data, and be able to process and convert the data as needed.

Furthermore, when using data such as open data, data analysis often requires trial and error. If preparing the data each time you try to analyze it from a different perspective requires time and effort, it may be difficult to deepen your data utilization.

In other words, in order to utilize open data and realize its potential, it is desirable to have a data infrastructure in place that can efficiently collect such disparate data and utilize it smoothly and efficiently.

Please utilize "connecting" technology

There are methods that allow you to efficiently develop data environments that connect to a wide variety of systems and data on the cloud, read, process, and transfer data as needed, all with just a GUI.These are "connecting" technologies such as "DataSpider" and "HULFT Square," also known as "EAI," "ETL," and "iPaaS."

Can be used with GUI only

Unlike regular programming, there is no need to write code. By placing and configuring icons on the GUI, you can achieve integration with a wide variety of systems, data, and cloud services.

Being able to develop using a GUI is also an advantage

​No-code development using only a GUI may seem like a simple compromise compared to full-scale programming. However, being able to develop using only a GUI allows on-site personnel to proactively work on cloud integration themselves. On-site personnel are the ones who know the business best.

Full-scale processing can be implemented

There are many products that claim to allow development using only a GUI, but some people may have a negative impression of such products as being too simple.

It is true that things like "it's easy to make, but it can only do simple things," "when I tried to execute a full-scale process it couldn't process and crashed," or "it didn't have the high reliability or stable operating capacity to support business operations, which caused problems" tend to occur.

"DataSpider" and "HULFT Square" are easy to use, but also allow you to create processes at the same level as full-scale programming. They have the same high processing power as full-scale programming, as they are internally converted to Java and executed, and have a long history of supporting corporate IT. They combine the benefits of "GUI only" with full-scale capabilities.

No need to operate in-house as it is iPaaS

DataSpider can be operated securely on a system under your own management. With HULFT Square, a cloud service (iPaaS), this "connecting" technology itself can be used as a cloud service without the need for in-house operation, eliminating the hassle of in-house implementation and system operation.

Related keywords (for further understanding)

Keywords related to data integration and system integration

  • EAI
    • It is a concept of "connecting" systems by data integration, and is a means of freely connecting various data and systems. It is a concept that has been used since long before the cloud era as a way to effectively utilize IT.
  • ETL
    • In the recent trend of actively working on data utilization, the majority of the work is not the data analysis itself, but rather the collection and preprocessing of data scattered around, from on-premise to cloud. This is a means to carry out such processing efficiently.
  • iPaaS
    • A cloud service that "connects" various clouds with external systems and data simply by operating on a GUI is called iPaaS.

Are you interested in "iPaaS" and "connecting" technologies?

Try out our products that allow you to freely connect various data and systems, from on-premise IT systems to cloud services, and make successful use of IT.

The ultimate "connecting" tool: data integration software "DataSpider" and data integration platform "HULFT Square"

"DataSpider," data integration tool developed and sold by our company, is a "connecting" tool with a long history of success. "HULFT Square," a data integration platform, is a "connecting" cloud service developed using DataSpider technology.

Another feature is that development can be done using only the GUI (no code) without writing code like in regular programming, so business staff who have a good understanding of their company's business can take the initiative to use it.

Try outDataSpider/ HULFT Square 's "connecting" technology:

There are many simple collaboration tools on the market, but this tool can be used with just a GUI, is easy enough for even non-programmers to use, and has "high development productivity" and "full-fledged performance that can serve as the foundation for business (professional use)."

It can smoothly solve the problem of "connecting disparate systems and data" that hinders successful IT utilization. We regularly hold free trial versions and hands-on sessions where you can try it out for free, so we hope you will give it a try.


Why not try a PoC to see if HULFT Squarecan transform your business?

Why not try verifying how "connecting" can be utilized in your business, the feasibility of solving problems using data integration, and the benefits that can be obtained?

  • I want to automate data integration with SaaS, but I want to confirm the feasibility of doing so.
  • We want to move forward with data utilization, but we have issues with system integration
  • I want to consider data integration platform to achieve DX.

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