New Jersey State Policy Lab: Catalyzing the Information Economy: Moving Towards Strategic Expansions of Open Data-Driven Value Creation

June 1, 2022

by Shiya John, Snigdha Mishra and Jim Samuel

Open data is expected to influence trillions of dollars in global value creation by 2030, as projected by McKinsey Global Institute: “The boost to the economy from broad adoption of open-data ecosystems could be as high as 1.5 percent of GDP in 2030 in the European Union, the United Kingdom, and the United States, and as much as 4 to 5 percent in India” (White, et al., 2021). Open data, along with developments in big data analytics, allows for better decision-making, new product and service offers, and more accountability (Chui, 2014). Open data can increase understanding of global concerns and challenges. It can help fight crime and diseases, empower individuals, and help in public governance (e.g., tracking the performance of taxpayer-funded government initiatives and increasing government transparency and accountability). Data is no longer a resource with confined value creation potential, but it has now “… become the lifeblood of businesses, communities, and society as a whole” (ODI, 2022). Government open data is no longer an option, it is a necessary provision and the focus has shifted to the quality and usability of open data.

What is “open data?” ‘Data’ is generally used to refer to a systematic representation of factual information, that is used for sensemaking, reasoning, arguments, presentations, and calculations. ‘Open data’ refers to government data, and all data that is made publicly available with little to no restrictions for use, reuse, and distribution, to support transparency, innovation, and creative interactions, leading to insights-driven value creation. In a data-driven world, open data is becoming increasingly crucial for individuals, communities, and institutions to have fair and timely access to high-quality data-driven opportunities. The degree to which open data is usable and useful varies in multiple ways: accessibility, machine readability, quality, timeliness, and re-use and redistribution rights (data.gov, 2022; Kassen, 2013; Lnenicka, et al., 2022).

The expansion of open data has powerful applications for value creation and public benefits, such as through transparency and accountability:

  • Open data makes it easier for the general public to stay engaged and informed about government actions and projects (e.g., public budget expenditures and the effectiveness of government initiatives).
  • Increased transparency leads to more accountability and less corruption. In 2015, the G20 Anti-Corruption Working Group established the G20 Anti-Corruption Open Data Principles (to make critical data accessible to combat corruption.
  • Open data can lead to improved efficiencies and reduced costs of data acquisition, validation, and usage in organizations, corporations, and governments.
  • Open data can lead to a wide variety of data interpretations: The general public, governments, NGOs, researchers, and businesses can use open data to analyze the data, interpret findings and validate them in a variety of ways.
  • Open data may help stakeholders make improved data-driven decisions:
    • Stakeholders who may otherwise not have access to equivalent data can use open data to detect gaps and identify and prioritize the most relevant initiatives.
    • Consumers can also benefit from the expansion of open data. Extending the ideation presented in a McKinsey report, the value of consumer benefit from open data across just the top seven domains of education, transportation, consumer products, electricity, oil and gas, health care, and consumer finance is estimated to be in the trillions of dollars (Chui, 2014).

Large numbers of studies and evaluations of open data initiatives in prominent cities (e.g., New York City and Chicago) have demonstrated the power of open data in catalyzing innovation and progress. More individuals, researchers, and institutions have access to information leading to new methods of analysis, which can expand research, foster creativity, and accelerate progress. For example, NYC Open Data is a library of datasets generated by numerous municipal departments and agencies that are maintained by New York City. Visitors to the site can look at datasets and projects that utilize open data, like the Crashmapper which allows advocates, press, and elected officials to prioritize the most dangerous intersections to be fixed; and scout which is an innovative new way to browse New York City’s open data portal.

The State of New Jersey (NJ) has adopted the open data strategy and the NJOIT Open Data Center  which is an excellent example of an implementation integrating a broad range of NJ databases and sources.   This is NJ’s primary open data portal, facilitating access to data regarding agriculture, banking insurance, children and families, civil service commission, community affairs, corrections, education, environmental protection, health, higher education, homeland security, human services, labor and workforce development, law and public services, military and veterans’ affairs, motor vehicle commission, public utilities, state department, state police, transportation, and treasury.

Numerous notable NJ data portals provide valuable access to open data:

  • The NJ Sandy Transparency site provides downloadable spreadsheets for various departments such as Community Affairs, Children and Family, Education, Health, Human Services, Labor and Workforce Development, Military and Veterans Affairs, Transportation, and Transit.
  • The NJ Department of Education  website is a great place for educational content (e.g., school and student information, accountability and performance data, finance and budget, staff data, certified staff report, and school climate data).
  • The New Jersey Department of Environmental Protection website provides environmental information which can be searched using keywords, sites, and categories.

A common limitation, however, is that data is often provided in difficult to reuse formats such as PDF files.

Importantly, the NJOIT Open Data Center portal is not exhaustive. There are many NJ databases, data sources, and portals that are not included. Nonetheless, it may be unreasonable to expect comprehensive integration at this stage. Due to the complexity of information ecosystems, locating available data can be challenging. As a result, more value-added initiatives are required. The NJ data indexing initiative from the NJ State Policy Lab  and the Rutgers Urban & Civic Informatics Lab represents a valuable strategy to enhance access to data. This initiative aims to facilitate greater visibility of NJ data available from the government and alternative sources by creating a flexible and adaptive index of data portals, databases, and data sources containing NJ data.

Finally, it must be noted that artificial intelligence (AI) is the key to sustainable future value creation. Combinations of open data and AI models are expected to play a transformational role in human society, especially in prominent areas such as healthcare and drug discovery (Jiménez-Luna, et al., 2021). Similar trends are observable across domains as data-dependent AI models continue to improve performance. AI technologies are expected to augment humans and transform society, feeding on new forms of data (Samuel, 2021; Samuel, et al., 2022). However, AI today is data-dependent, and it is necessary to ensure both a wide range of data and high-quality data for successful AI transformations. Expansive open data has the potential to catalyze such AI transformations and to support the next wave of open-data and AI-driven value creation. Hence, there is an urgent need to support and enhance open data initiatives.

References: 

  1. White, O., Madgavkar, A., Townsend, Z., Manyika, J., Olanrewaju, T., Sibanda, T., & Kaufman, S. (2021). Financial data unbound: The value of open data for individuals and institutions. McKinsey Global Institute.
  2. Chui, M., Farrell, D., & Jackson, K. (2014). How government can promote open data and help unleash over $3 trillion in economic value. Innovation in Local Government: Open Data and Information Technology2.
  3. The Open Data Institute. Retrieved May 27, 2022, from https://theodi.org/
  4. Data definition and meaning. Merriam -Webster. Retrieved on May 24, 2022, from https://www.merriam-webster.com/dictionary/data
  5. Kassen, M. (2013). A promising phenomenon of open data: A case study of the Chicago open data project. Government information quarterly30(4), 508-513.
  6. G20 anti-corruption resources. United Nations: Office on Drugs and Crime. (n.d.). Retrieved May 24, 2022, from https://www.unodc.org/unodc/en/corruption/g20-anti-corruption-resources/by-thematic-area.html
  7. G20 Anti-Corruption Open Data Principles. United Nations, Office of Drugs and Crime. (n.d.). Retrieved May 24, 2022, from https://www.unodc.org/documents/corruption/G20-Anti-Corruption-Resources/Thematic-Areas/Public-Sector-Integrity-and-Transparency/G20-Anti-Corruption_Open_Data_Principles_2015.pdf
  8. The city of New York. (n.d.). NYC open data. NYC Open Data WP Engine. Retrieved May 24, 2022, from https://opendata.cityofnewyork.us/
  9. Projects. NYC open data. NYC Open Data WP Engine. Retrieved May 24, 2022, from https://opendata.cityofnewyork.us/projects/
  10. Crashmapper. NYC open data. NYC Open Data WP Engine. Retrieved May 24, 2022, from https://opendata.cityofnewyork.us/projects/crashmapper/
  11. Scout. NYC open data. NYC Open Data WP Engine. Retrieved May 24, 2022, from https://opendata.cityofnewyork.us/projects/scout/
  12. Open data portal: NJOIT open data center. (n.d.). Retrieved May 24, 2022, from https://data.nj.gov/
  13. Downloadable spreadsheet data. (n.d.). Retrieved May 24, 2022, from https://nj.gov/comptroller/sandytransparency/funds/download/index.html
  14. New Jersey Department of Education. (n.d.). Retrieved May 24, 2022, from https://www.nj.gov/education/doedata/
  15. DEP Data Miner. (n.d.). Retrieved May 24, 2022, from https://njems.nj.gov/DataMiner
  16. Jiménez-Luna, J., Grisoni, F., Weskamp, N., & Schneider, G. (2021). Artificial intelligence in drug discovery: recent advances and future perspectives. Expert opinion on drug discovery16(9), 949-959.
  17. Samuel, J., Kashyap, R., Samuel, Y., & Pelaez, A. (2022). Adaptive cognitive fit: Artificial intelligence augmented management of information facets and representations. International journal of information management65, 102505.
  18. Lnenicka, M., Nikiforova, A., Luterek, M., Azeroual, O., Ukpabi, D., Valtenbergs, V., & Machova, R. (2022). Transparency of open data ecosystems in smart cities: Definition and assessment of the maturity of transparency in 22 smart cities. Sustainable Cities and Society82, 103906.
  19. Business case for open data at resources.data.gov. Retrieved May 27, 2022, from https://resources.data.gov/resources/open-data/
  20. Samuel, J. (2021). A call for proactive policies for informatics and artificial intelligence technologies. Scholars Strategy Network.  https://scholars.org/contribution/call-proactive-policies-informatics-and

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