Review of Recent Literature on Data Philanthropy

Par Al Bhanji , Étudiant au doctorat et ancien coordonnateur du PhiLab de l'ouest
13 janvier 2021

Data has become a highly valuable asset that can assist the philanthropic sector in achieving its goals and growing its footprint. The use of data in philanthropy has come to be known as “Data Philanthropy”, “data donations” or “data for good”.

What is Data Philanthropy?

George et al. (2020) believe a new era has come that is changing traditional corporate giving as non-profits see the value and opportunity in Data Philanthropy. In addition to cash and in-kind gifts, Data Philanthropy is becoming the “modern extension of traditional corporate philanthropic activities”. They contend that in improving social welfare, Data Philanthropy is highly effective as it generates potential benefits for organizations by providing more market opportunities, better workforces and greater access to new data and experiences. Data Philanthropy can involve many different participants including corporations, individuals, non-profits, governments and academia. Data Philanthropy provides an opportunity for donors and recipients to work together, creating new opportunities to transform and inform society (George, Yan, and Leidner 2020).

George et al. (2020) also classify Data Philanthropy as a subtype of corporate philanthropy associated with firms that donate technology, human capital and data. The authors contribute that donating data scientists is akin to employee volunteerism within corporate philanthropy. George et al. (2020) believe that Data Philanthropy may be beneficial to organization effectiveness by providing donor firms with tools to better assess risk and to foster innovation. They contend that Data Philanthropy is an advantage in attaining and retaining talent which can be essential for firms to better invest in a rapidly changing dynamic business environment. The authors share how Data Philanthropy has now become an integral part of the data economy and share multiple examples including the example of Aimia that specialize in marketing and loyalty analytics and the example of Ecobee who are leaders in home automation. These two examples are regarded to be some of Canada’s leading participants in Data Philanthropy. (George, Yan, and Leidner 2020).

Using Data to Strengthen Philanthropic Outreach

Brudney et al. (2017) describe one of the core goals of non-profit organizations – building strong and long-lasting relationships within their communities. It is these relationships that non-profit organizations forge that foster social capital and trust within the communities that they represent. The authors contend that non-profits stem from a need or opportunity within a community and thus community building is essential to the success of the non-profit’s organizational goals and objectives. The author’s share how Geographical Information Systems (GIS) use available electronic information to “describe and locate non-profit organizations geospatially in a community”. Shared goals and interests by the public and non-profits have the potential to span across large geographical areas and GIS technologies have the potential to strengthen these ties by identifying areas that cater to specific non-profit interests (Brudney, Russell, and Fischer 2017).

Non-profit organizations are answerable to the communities in which they serve and thus act accordingly on their behalf. Non-profits must effectively select their target communities to be seen as a viable and valued component of the community. Being aware of community belonging and geographical boundaries can aid non-profits in staying relevant and translate their visions into meaningful action. Brudney et al. (2017) suggest that non-profits can benefit from GIS applications by examining economic, environmental and social problems that relate to non-profit goals and outreach areas. GIS tools can help organizations to better identify specific areas of community interests by combining asset mapping and need assessment functions into a singular tool. The authors contend that this would better inform non-profit decision making in specific geographical areas (Brudney, Russell, and Fischer 2017).

Using GIS systems to improve community-based problem solving can help community members and organizations to better develop policies that benefit their community effectively. GIS technologies have the capability to organize information in layers to create targeted and customized outputs. However, Brudney et al. (2017) caution that data illuminating the success and application of GIS systems by non-profit organizations is limited. The use of GIS systems at the time of publication revealed a minority of organizations using such resources. The inability to properly embrace GIS systems is further exacerbated by resource restrictions, political pressures and system sustainability. Brudney et al. (2017) conclude that a wider range of stakeholders would need to realize the full potential of GIS systems by building a coalition of partners and users in order for GIS to operate at an optimum capacity and to be better utilized by more non-profit organizations (Brudney, Russell, and Fischer 2017).

Data Collaborations and the Future

Susha et al. (2019) remind the reader that opening public data for reuse can prove to have many benefits. Some of these benefits include creating a positive impact on societal challenges which include but are not limited to violence protection, proper education access and poverty reduction. In recent years, governments across the globe have opened up important datasets that non-profits and other organizations can use to better coordinate their delivery mechanisms. The private sector as part of their corporate social responsibility have also realized there can be mutual benefits with data sharing. The coordinated collaboration across different fields is being referred to as “data collaboratives”. This is becoming increasingly prevalent as individuals, organizations, companies and governments are coming together to work for a common goal of accumulating and sharing data for “the public good”. The authors describe this phenomenon as a modern creation that goes beyond the “classic public-private partnership model”. In the past, participants across different fields would exchange their data for the public good in isolated and sporadic circumstances. Big data or data collaboratives are now more readily associated with the creation of data on a larger scale for “public good” (Susha, Grönlund, and Van Tulder 2019).

According to Susha et al. (2019) an international practitioner conference that dates back to 2015, is held annually to discuss the use and responsibility of using data to address societal problems. Currently, Data Philanthropy focuses on providing access to data at a nominal cost or at no cost in the name of public good. However, improving societies challenges with data can be a challenge in itself. Susha et al. (2019) describe how data collaboratives are still an unclear concept that face multiple obstacles that include supply and demand difficulties, privacy issues, challenging data discovery, lack of appropriate legislation provisions and costly access. Calculating the success of data sharing or data partnerships is also a challenge as societal impacts can be difficult to measure. However, the authors surmise that It is evident that big data or data collaborations have the potential to contribute to the “public good” and recommend that research should continue and expand as opportunities for data collaborations grow (Susha, Grönlund, and Van Tulder 2019).

The future of using Data Philanthropy in the non-profit sector is certain. Global economies, infrastructures and public policy are highly influenced by international and national data. Taddeo (2017) explains how grasping the ramifications and the value in accessing “data for good” is one of the leading challenges this decade. The author explains how Data Philanthropy in its current state is “morally ambiguous” as it poses various ethical problems. This is not intended to dissuade against the use of Data Philanthropy but rather to create awareness around its many possibilities. Taddeo (2017) recognizes these merits and contends that Data Philanthropy is ultimately likelier to produce morally good results. In the current digital age, data facilitating policy, humanitarian efforts and scientific research is growing exponentially. International organizations such as the United Nations have started to create departments for sharing corporate owned data as demand and the willingness to supply it is increasing. One of the main concerns that critics of Data Philanthropy have is the ownership of the data being shared and how this can adversely affect individual and corporate rights to such data. It is worth noting that under the right circumstances, legislation and policy, this issue can be mitigated by sharing data behind firewalls and through carefully curated privacy agreements (Taddeo 2017).


The donation of data by private companies is becoming increasingly prevalent and will likely continue its growth trajectory in the future. The philanthropic sector has seen the value in accessing data. Much like private companies or governments, non-profits can use data to appropriately position themselves in communities, investments, proposals and social efforts.

Ensuring that data governance meets appropriate methodology and effective change will ensure that the data obtained is of a pristine quality that can be easily managed and utilized by its many users (Wang et al. 2019). Government agencies therefore need to devise proper legislation directly relating to operable data analyses and data application processes to ensure proper data management across all sectors. Incorrect use or dissemination of data can cause organizations to make errors in decision making which can influence poor policy development. Proper regulations should complement Data Philanthropy to address these concerns.

This article is part of our most recent Special Edition on Philanthropy & Data, led by the Western Hub.



Brudney, Jeffrey L., Allison Russell, and Robert L. Fischer. 2017. “Using Data to Build Community: Exploring One Model of Geographically Specific Data Use in the Non-Profit Sector.” Community Development Journal 52 (2): 354–71.

George, Jordana J, Jie Yan, and Dorothy E Leidner. 2020. “Data Philanthropy: Corporate Responsibility with Strategic Value?” Information Systems Management 37 (3): 186–97.

Susha, Iryna, Åke Grönlund, and Rob Van Tulder. 2019. “Data Driven Social Partnerships: Exploring an Emergent Trend in Search of Research Challenges and Questions.” Government Information Quarterly 36 (1): 112–28.

Taddeo, Mariarosaria. 2017. “Data Philanthropy and Individual Rights.” Minds and Machines 27 (1): 1–5.

Wang, Chen-Shu, Shiang-Lin Lin, Tung-Hsiang Chou, and Bo-Yi Li. 2019. “An Integrated Data Analytics Process to Optimize Data Governance of Non-Profit Organization.” Computers in Human Behavior 101: 495–505.