Research on open data application
strategies
September 2020
Summary
With the progress of global digitization and the rapid explosion of
emerging technologies, the type, quantity and value of open data have
shown a rapid and massive upward trend, driving the rapid rise of the "data
economy" industry. Countries around the world are paying attention to
emerging technologies. For the development of the industry, we should
actively expand data openness and utilization, and propose relevant policies
and promotion measures in response to the development needs of the data
economy, so as to activate open data for private value-added applications
and strengthen the overall data economy development and output value.
Therefore, how to use limited government resources to promote the
effective commercial application of agency data, integrate private creativity
and improve existing policies to seek the greatest public interests, and then
enhance the economic value of data, are important issues facing
government departments.
This study analyzes the current open data application trends and policies in
advanced countries, and discusses the current challenges faced by open
data in China. It provides suggestions on promotion strategies from the
aspects of data, policy, organization, technology and environment, and
hopes to serve as a guide for the government to open data in the future.
Reference for policies and related implementation strategic planning.
Keywords: open data, data governance, data economy
I
1. Origin and purpose of research
1. Origin of research
In recent years, due to the rapid development of emerging technologies, the
type, quantity and value of data have shown a rapid growth trend. The
importance of data in economic development has continued to increase.
Meteorology, disaster prevention, transportation, oceans and medical care,
etc., can all be accessed through data. Exploration and analysis help the
development of emerging technologies, and even derive new industrial
systems and create new industrial economic models. Open data is an
important foundation for the development of the above trends.
Governments around the world have proposed in response to the
development needs of the data economy. Relevant and corresponding
policies and promotion measures are required to activate open data for
private value-added applications and strengthen the overall data economic
development and output value.
In the era of data economy development, how to use limited government
resources to promote the effective commercial application of agency data,
integrate private creativity and improve existing policies to seek the
greatest public interests, and then enhance the economic value of data are
important issues facing government departments. subject.
In summary, this research period analyzes the international open data
development trends and policies, and discusses the current challenges faced
by domestic open data, in order to formulate open data application
promotion strategies and put forward implementation suggestions for active
data utilization to meet the needs of private data. , promote the expanded
use of open data and drive the further development of the data industry.
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2. Research purpose
The expected goals of this study are stated as follows:
(1)
Discuss the issues involved in the application of open data from the
perspective of data economy and industrial development.
(2)
Analyze international open data application trends and current status of
the dilemma of promoting open data, and propose open data application
promotion strategies.
(3)
Provide specific and feasible suggestions for the future development
policy of open data.
3. Research methods
This study uses literature analysis and comparative research methods to
explore the research questions. First, through literature analysis, we explore
the economic characteristics of data, discuss foreign open data trends,
related policies and application issues, and sort out the issues involved in
domestic open data, as a reference basis for this study to propose an open
data application strategy. .
Then, through comparative analysis and research, we observe the
characteristics of open data application development in internationally
advanced countries, and then review the current status and difficulties of
domestic open data promotion, refer to foreign experience, and propose
strategic frameworks and promotion strategies related to domestic future
development. And based on this, the final conclusions and suggestions are
put forward to help promote open data-related applications and drive the
development of the data economy in the future.
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2. Open data application strategy
1. Strategic Structure
Based on the characteristics of the data economy, international open data
application policy trends and the current challenges faced by the country,
find out the direction of future promotion strategies.
"Main Activities" refers to the EU data value chain, and the main
activities of open data application include four types of activities: data
collection and creation, data storage and integration, data analysis and
processing, marketing and distribution, and data utilization. These activities
will vary according to the role of the data. Show varying importance. For
example, for data providers, data analysis and processing, marketing and
distribution are the most important; while for data users, data utilization
may be the focus.
"Support activities" are auxiliary to the main activities, supporting the
main activities through a series of different promotion mechanisms in terms
of policy, technology, organization and environment.
Through the mutual complementation of main activities and support
activities, we will achieve overall economic growth, service application
innovation, and implement the core spirit of open government, transparency,
public participation, and agency accountability.
2. Promotion strategy
Based on the planning of the above strategic framework, this study
develops relevant promotion strategies from the data, policy, organizational,
technical and environmental aspects as follows:
(1)
Data surface:
A. Data collection and creation:
a. When developing systems and establishing data, organizations
should first consider the need for open data: open data design should
be incorporated into each process of the organization's information
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system design, such as: system data field specification design, data
quality and security, system data interface, etc. This enables data
opening planning to be completed at the early stage of system design,
effectively reducing future processing costs.
b. Automatic or semi-automated data collection and processing process:
The core key to the issue of open data is the source of the data. Only
when the data itself is sufficient and correct can the next step of data
processing be carried out. In order to improve the speed of data
acquisition, organizations should increase the speed of data creation
and update frequency through automatic or semi-automatic data
collection and processing processes, so as to help conduct large-scale
assessments and grasp overall data resources in a short period of
time .
B. Data storage and integration:
a. Agencies should establish a mechanism for long-term storage and
integration of basic data: data accumulation is a long-term,
continuous task. If you want to take full advantage of the benefits
that open data can bring, you must plan a storage and integration
mechanism, and plan the follow-up at the beginning of the
establishment. The update and security mechanism allows data to be
accumulated over a long period of time and provided for future
analysis.
b. The storage and computing environment should be oriented towards
cross-agency cooperation and cloud resource integration: When
developing data applications, the storage and computing environment
architecture is a very important cost consideration. The overall
domestic resources are limited, and subsequent development should
be oriented towards cross-agency cooperation and integration. Cloud
resource integration is carried out to avoid repeated establishment of
software and hardware facilities by agencies.
C. Data analysis, processing, marketing and distribution:
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a. Focus on the availability and security of open data: The focus of the
organization should not only increase the number of open data, but
also confirm the data quality through procedures before uploading to
the open data platform, and ensure the safety and risk of data
operations to improve the usability of open data.
b. Agencies should release data that meets the needs of the public:
Open data still allows the outside world to expect the potential value.
Agencies can use data mining tools in a timely manner to find hidden
correlations in huge data and release valuable data sets.
c. Active promotion of data set updates: Data users all want to know
the updates of open data sets. They can send data update notifications
to users who are willing to leave their contact information on the
open data platform, and create update records for reference.
d. Integrate the same type of data across agencies: Check whether there
are parts of the currently open data set that can be merged. In
addition to simplifying data maintenance operations, it can also make
it easier for those who need the data to find and use it.
D. Data Utilization:
a. Pay more attention to the feedback from data users: There should be
corresponding user feedback and accountability mechanisms for
individual data sets, and handle user feedback to avoid data quality
problems from continuing to exist, thereby limiting the use of open
data.
b. Practical cases of promoting data application: Agencies can
cooperate with schools or citizen groups to organize workshops or
achievement exhibitions. When the development of data utilization
presents many good services and results, it can promote more private
industries to be willing to invest in data application development,
and government agencies will also Pay more attention to the value of
open data, actively understand private needs and respond to the data
application needs of external users .
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(2)
Policy aspect:
A. Strengthen the relevance of existing laws and regulations: Laws and
regulations are the cornerstone of policy implementation. Laws and
regulations provide agencies at all levels with a basis for compliance.
Facing various challenges in the current situation of open data, we
should refer to international trends in a timely manner and strengthen
the existing legal system through public-private collaboration. and
related specifications .
B. Develop an open data quality assessment mechanism: Each agency
should develop a quality assessment mechanism for business
management open data and set up an audit team to standardize internal
open data quality improvement plans and set quantitative indicators and
target achievement rates. If the plan is to Within 2 years, the number of
data sets must be increased by 20% and the 3-star format must be
increased by 10%.
C. Civil servant data analysis functional training plan: At the beginning of
the implementation of open data, the basic concepts of open data
application should be established for government agency personnel,
and physical or digital courses such as data processing, data analysis,
and data visualization should be organized. Through institutionalized
education and training programs, public sector colleagues can
effectively improve their data management capabilities and understand
the concepts of data collection, production, storage, release and
application, so as to cultivate correct open data concepts.
D. Establish a high-value data evaluation process: In order to meet the
needs of private data applications, a set of high-value data identification
and evaluation operations should be established to facilitate the
government to release data of potential value. Stakeholders and citizen
groups should be consulted on the actual situation of data openness.
Needs and current status to ensure that open data is in the public
interest and meets needs.
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(3)
Organizational aspect:
A. Enhance cross-agency cooperation and data circulation: The spirit of
open data application is to effectively integrate data sources in the same
field for joint use. Each data set has corresponding investment costs for
agencies. With limited resources, cooperation and sharing between
agencies is particularly important. It will also be more convenient for
the public to develop innovative services using data in the same field.
B. Shape the government's proactive open culture: Design relevant
incentive systems through government service quality awards or smart
government action plans to encourage agencies to integrate open data
and data governance concepts into policy design; or use the results of
open data as a basis for applying for government budgets or projects
The conditions for subsidies enable data management to be fully
implemented in government administration.
C. Strengthen the awareness and promotion of senior civil servants: The
promotion of policies in the public service system is usually more
effective from the top down. The support of senior civil servants of the
agency can help colleagues who actually implement open information
to enhance the concept of proactive openness. This can be done through
current examinations The high-level civil service training designed by
the Academy and the Civil Service Manpower Development Center has
introduced external experts and scholars to conduct relevant seminars
to strengthen senior civil servants’ understanding of the open
information policy.
D. Complete reward and punishment system: Praise the agencies that
perform well in their implementation, and reward those who have
outstanding performance in open data, so as to increase the willingness
of government agencies to open data; in addition, if the agency's
execution results are not good, it should also be punished
Announcement to avoid continued poor performance of the agency.
(4)
Technical aspect:
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A. The data format must be machine-readable: The format of the agency's
open data set should mostly produce plain text files such as CSV or
JSON. If most of the data is uploaded in PDF or Word format, data
users must manually convert these data into the development
application service Required file format.
B. Ensure that data is real-time and uninterrupted: For example, weather
and traffic information are time-sensitive. Once the service is
interrupted, real-time weather or bus dynamic information cannot be
displayed. Therefore, government data supply should focus on network
stability and system service availability .
C. Establish government data standards: By formulating standard names
and standard codes for each exclusive field, as well as data standards
such as open data field specifications and lengths, as open data
principles for government agencies, data collectors can follow the
principles at the source of data generation. Collecting data with certain
attributes and formats also allows data users to easily understand the
meaning of the data and conduct subsequent data analysis and
application.
D. Expand the application of open application programming interface
(Open API): Open API is the current development trend. Through the
implementation of Open API by organizations, future information
services can gradually achieve the effects of machine readability,
machine writing, and open format. Different technologies will be more
open. It can be fully connected and can provide various data application
services more conveniently and extensively.
E. Construct a systematic data infrastructure: Through systematic data
processing and management, it helps to reduce the burden of open data
implementation colleagues on file conversion and integration, including
data import, file creation, processing and export of data, etc. Processed
through system automation; subsequent data statistics and analysis can
be directly sent to the system, and directly converted into an open data
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set for public use.
(5)
Environmental aspect:
A. Encourage new startups to invest in data applications: In order to
promote innovation, entrepreneurship and investment, and create a
high-quality data economic ecology, relevant competent authorities can
provide innovation subsidies such as entrepreneurship, research and
development, branding, and innovation cultivation in the field of open
data application through industrial development incentives and
subsidies. and investment subsidies such as rent, salary, interest, and
vocational training.
B. Strengthen market incentives for open data applications: In addition to
organizing various data application competitions to stimulate the energy
of innovative data applications, the government can even
commercialize tutoring works or provide APIs to allow the public to
gradually deepen and add value to original creativity and ideas.
Promote private use of government open data.
C. Promote industrial transformation and development of data
applications : With the continuous growth of huge amounts of data
and the rise of Internet of Things and artificial intelligence
technologies, the government should help promote the transformation
of operators in different industrial fields and invest in the development
of data value-added application services , and assist in reviewing
the performance of operators and providing relevant data
technologies. consultation, or encouraging industry players to
transform through tax exemptions and other measures to accelerate the
development of a data innovation service ecosystem .
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References , conclusions and recommendations
The promotion of open data in many systems has gradually become in line
with international standards. However, with the rapid development of
information technology, there are still many issues and challenges that need
to be overcome. We hope to complete the development blueprint of the
country's overall data economy and continue to effectively promote
openness through public-private collaboration. Data operations promote
cross-agency cooperation and data circulation, improve government
governance efficiency, meet people's livelihood needs, and strengthen the
power of the public to supervise the government to create open data
economic output.
After focusing on the analysis and discussion of relevant strategic aspects,
in order to further promote the development of the data economy, this study
puts forward the following suggestions for promoting the open application
of data in the future :
1.
Promote the open data legal system to keep pace with the times:
Although basic operating principles have been established for the
current legal framework for open data, with the evolution of technology
and society, it is necessary to refine existing regulations in a timely
manner. The short-term goal can be to first revise the existing
administrative rules to cover the procedures for handling public
suggestions and data. Issues such as usage types and the relationship
between relevant rights and obligations ; the mid- and long-term goals
are to establish legislation to strengthen digital governance at the legal
level and complete the data sharing application environment .
2.
Strategic planning for open data functional training:
Not all the main promoters of open data in the agency are
information personnel. To implement the open data policy, the data
awareness and management capabilities of different business personnel
should be improved and more appropriate training programs should be
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established. The government can Establish an exclusive information
training unit or cooperate with public sector training institutions to
establish a functional ability appraisal system to cultivate more talents
for the agency to open up business.
3.
Actively use emerging technologies to meet people’s livelihood needs:
With the development of artificial intelligence, Internet of Things,
5G and other technologies, the integration of open data applications and
emerging technologies will be of great help in solving people's
livelihood problems and improving the convenience of people's lives.
For example, we are currently facing a serious problem of declining
birthrate and aging population. If we can Make good use of artificial
intelligence, big data and graphics applications to integrate silver care,
and notify the elderly immediately when an emergency occurs, thereby
reducing the caregiver's burden and reducing their stress, so that they can
balance their roles at home and work.
4.
Establish data economic benefit evaluation indicators:
As the data economy becomes more and more important to the
overall economic development of the country, by establishing data
economic benefit evaluation indicators to further estimate the data
market output value and data economy scale, the government can
understand the benefits created by data applications for various
industries and then tailor-made Formulate data industry development
policies and promote the development of the overall data economy.
5.
Create opportunities for cooperation with international organizations:
In recent years, international open data competitions have achieved
remarkable results. Through the power of non-governmental
organizations such as the Open Data Alliance, we can seize opportunities
for international cooperation, effectively understand international open
data application trends , exchange developments in various countries,
and establish mutual cooperation with governments of various countries
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on open data. , a platform for learning, and continue to speak out at
international exchange conferences in Asian countries or other world
organizations, and continue to increase the influence of international
open materials.
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