Developing an index for measuring OGD publisher compliance to good practice standards: Insights from opendata.swiss

Abstract

In many countries, public organisations are among the largest creators and gatherers of data. To increase economic growth, governments have therefore begun to liberate access to large parts of government data by developing open government data (OGD) initiatives. Since the emergence of OGD initiatives, many OGD portals have been launched. There is a common belief that sharing OGD throughout platforms would be sufficient to motivate companies to re-use data and improve economic growth. However, there is very little evidence about the quality of shared OGD. For companies to be able to re-use, share and create value from OGD, data publishers must meet certain good practice standards. Following a pragmatic research approach, in this paper we present an index that can be applied for the quality assessment of the published OGD on portals. On the basis of 17,777 published data resources gathered from the Swiss OGD portal (opendata.swiss), we demonstrate the logic of the index and discuss the key learnings we obtained from applying the index to this concrete case. We conclude that, in Switzerland, the adherence to good practice standards for publishing OGD is fairly low.

Keywords

Good practice liberation of data open government data standards

Get full access to this article

View all access options for this article.

References

Abate,

Diegert,

, & Allen,

(1998). A hierarchical approach to improving data quality. Data Quality, 4(1), 365-369.

Alexopoulos,

Loukis,

, & Charalabidis,

(2014). A platform for closing the open data feedback loop based on Web2. 0 functionality. JeDEM-eJournal of eDemocracy and Open Government, 6(1), 62-68.

Alexopoulos,

Zuiderwijk,

Charapabidis,

Loukis,

, & Janssen,

(2014). Designing a second generation of open data platforms: Integrating open data and social media. Paper presented at the International Conference on Electronic Government, Berlin, Heidelberg.

Allison,

(2010). My data can’t tell you that. Open government-Collaboration, transparency, and participation in practice, 257-265.

Askham,

Cook,

Doyle,

Fereday,

Gibson,

Landbeck,

Schwarzenbach,

, et al. (2013). The six primary dimensions for data quality assessment. DAMA UK Working Group, 432-435.

Attard,

Orlandi,

Scerri,

, & Auer,

(2015). A systematic review of open government data initiatives. Government Information Quarterly, 32(4), 399-418.

Atz,

(2014). The tau of data: A new metric to assess the timeliness of data in catalogues. Paper presented at the Conference for E-Democracy and Open Governement, Krems, Austria.

Barry,

, & Bannister,

(2014). Barriers to open data release: A view from the top. Information Polity, 19(1-2), 129-152.

Bates,

(2014). The strategic importance of information policy for the contemporary neoliberal state: The case of open government data in the United Kingdom. Government Information Quarterly, 31(3), 388-395.

10.

Batini,

Cappiello,

Francalanci,

, & Maurino,

(2009). Methodologies for data quality assessment and improvement. ACM Computing Surveys (CSUR), 41(3), 1-16.

11.

Berners-Lee,

(2006). Linked data-design Issues Retrieved from http://www.w3.org/DesignIssues/LinkedData.html.

12.

Charalabidis,

Zuiderwijk,

Alexopoulos,

Janssen,

Lampoltshammer,

, & Ferro,

(2018). Open data evaluation models: Theory and practice. In The World of Open Data, Springer International Publishing, pp. 137-172.

13.

Chatfield,

A.T.

, & Reddick,

C.G.

(2017). A longitudinal cross-sector analysis of open data portal service capability: The case of Australian local governments. Government Information Quarterly, 34(2), 231-243.

14.

Ciancarini,

Poggi,

, & Russo,

(2016). Big data quality: A roadmap for open data. Paper presented at the 2016 IEEE Second International Conference on Big Data Computing Service and Applications (BigDataService), Oxford, United Kingdom.

15.

CKAN Organization. (2018). Data quality, what is it? Retrieved from https://ckan.org/2011/01/20/data-quality-what-is-it/.

16.

Conradie,

, & Choenni,

(2012). Exploring process barriers to release public sector information in local government. Paper presented at the Proceedings of the 6th International Conference on Theory and Practice of Electronic Governance, Albany, New York, United States.

17.

Corsar,

, & Edwards,

(2017). Challenges of open data quality: More than just license, format, and customer support. ACM Journal of Data Information Quality, 9, 1-3.

18.

Danneels,

Viaene,

, & Van den Bergh,

(2017). Open data platforms: Discussing alternative knowledge epistemologies. Government Information Quarterly, 34(3), 365-378.

19.

Davies,

(2010). Open data, democracy and public sector reform: a look at open government data use from data.gov.uk. Oxford, UK: University of Oxford.

20.

Emran,

N.A.

(2015). Data completeness measures. In Pattern Analysis, Intelligent Security and the Internet of Things, Springer, pp. 117-130.

21.

European Data Portal. (2017). Open data in Europe. Retrieved from https://www.europeandataportal.eu/en/dashboard#2017.

22.

Fox,

Levitin,

, & Redman,

(1994). The notion of data and its quality dimensions. Information Processing & Management, 30(1), 9-19.

23.

Gascó-Hernández,

Martin,

E.G.

Reggi,

Pyo,

, & Luna-Reyes,

L.F.

(2018). Promoting the use of open government data: Cases of training and engagement. Government Information Quarterly, 35(2), 233-242.

24.

Goldkuhl,

(2012). Pragmatism vs interpretivism in qualitative information systems research. European Journal of Information Systems, 21(2), 135-146.

25.

Heimstädt,

Saunderson,

, & Heath,

(2014). Conceptualizing open data ecosystems: A timeline analysis of open data development in the UK. Paper presented at the Conference for E-Democracy and Open Governement, Krems, Austria.

26.

Henninger,

(2013). The value and challenges of public sector information. Cosmopolitan Civil Societies: An Interdisciplinary Journal, 5(3), 75-95.

27.

Huh,

Keller,

Redman,

T.C.

, & Watkins,

(1990). Data quality. Information and Software Technology, 32(8), 559-565.

28.

Janssen,

Charalabidis,

, & Zuiderwijk,

(2012). Benefits, adoption barriers and myths of open data and open government. Information Systems Management, 29(4), 258-268.

29.

Jetzek,

Avital,

, & Bjorn-Andersen,

(2014). Data-driven innovation through open government data. Journal of Theoretical and Applied Electronic Commerce Research, 9(2), 100-120.

30.

Kalampokis,

Tambouris,

, & Tarabanis,

(2011). Open government data: A stage model. Paper presented at the International Conference on Electronic Government, Delft, The Netherlands.

31.

Kirstein,

Dittwald,

Dutkowski,

Glikman,

Schimmler,

, & Hauswirth,

(2019). Linked Data in the European Data Portal: A Comprehensive Platform for Applying DCAT-AP. Paper presented at the International Conference on Electronic Government, San Benedetto Del Tronto, Italy.

32.

Kubler,

Robert,

Neumaier,

Umbrich,

, & Le Traon,

(2017). Comparison of metadata quality in open data portals using the Analytic Hierarchy Process. Government Information Quarterly, 35(1), 13-29.

33.

Máchová,

, & Lnénicka,

(2017). Evaluating the quality of open data portals on the national level. Journal of Theoretical and Applied Electronic Commerce Research, 12(1), 21-41.

34.

Martin,

(2014). Barriers to the open government data agenda: Taking a multi-level perspective. Policy & Internet, 6(3), 217-240. doi: 10.1002/1944-2866.POI367.

35.

Maurino,

Spahiu,

Batini,

, & Viscusi,

(2014). Compliance with open government data policies: an empirical evaluation of italian local public administrations. Paper presented at the Twenty Second European Conference on Information Systems, Tel Aviv, Israel.

36.

Munné,

(2016). Big data in the public sector. In Cavanillas,

Curry,

, & Wahlster,

, (Eds.), New Horizons for a Data-driven Economy: A Roadmap for Usage and Exploitation of Big Data in Europe, Springer, pp. 195-208.

37.

Neumaier,

Umbrich,

, & Polleres,

(2016). Automated quality assessment of metadata across open data portals. Journal of Data Information Quality, 8(1), 2.

38.

OECD publishing. (2016). Economic ans social benefits of internet openness. OECD Digital Economy Paper, no 257.

39.

Open Data Index. (2016). Benchmarking data automatically. Retrieved from http://oldsite.theodi.org/guides/benchmarking-data-automatically.

40.

Open Data Monitor. (2018). The open data monitor. Retrieved from https://opendatamonitor.eu/frontend/web/index.php?r=dashboard.

41.

Open Knowledge Fundation. (2018a). Comprehensive knowledge archive network. Retrieved from https://github.com/ckan/ckan.

42.

Open Knowledge Fundation. (2018b). The Open definition. Retrieved from http://opendefinition.org/.

43.

Open Knowledge Fundation. (2018c). Tracking the state of open government data. Retrieved from https://index.okfn.org/place/.

44.

Paré,

Trudel,

M.-C.

Jaana,

, & Kitsiou,

(2015). Synthesizing information systems knowledge: A typology of literature reviews. Information Management, 52(2), 183-199.

45.

Pollock,

(2011). Building the (open) data ecosystem. Retrieved from https://blog.okfn.org/2011/03/31/building-the-open-data-ecosystem/.

46.

Redman,

T.C.

, & Blanton,

(1997). Data quality for the information age: Artech House, Inc.

47.

Reiche,

K.J.

, & Höfig,

(2013). Implementation of metadata quality metrics and application on public government data. Paper presented at the Computer Software and Applications Conference Workshops (COMPSACW), 2013 IEEE 37th Annual, Kyoto, Japan.

48.

Reiche,

K.J.

Höfig,

, & Schieferdecker,

(2014). Assessment and visualization of metadata quality for open government data. Paper presented at the Conference for E-Democracy and Open Governement, Krems, Austria.

49.

Sadiq,

Yeganeh,

N.K.

, & Indulska,

(2011). 20 years of data quality research: themes, trends and synergies. Paper presented at the Proceedings of the Twenty-Second Australasian Database Conference-Volume 115, Perth, Australia.

50.

Sidi,

Panahy,

P.H.S.

Affendey,

L.S.

Jabar,

M.A.

Ibrahim,

, & Mustapha,

(2012). Data quality: A survey of data quality dimensions. Paper presented at the Information Retrieval & Knowledge Management (CAMP), 2012 International Conference, Kuala Lumpur, Malaysia.

51.

Strong,

D.M.

Lee,

Y.W.

, & Wang,

R.Y.

(1997). Data quality in context. Communications of the ACM, 40(5), 103-110.

52.

Sunlight Foundation. (2018). Ten principles for opening up government information. Retrieved from https://sunlightfoundation.com/policy/documents/ten-open-data-principles/.

53.

The European Commission. (2018). Open Data portals. Retrieved from https://ec.europa.eu/digital-single-market/en/open-data-portals.

54.

Torchiano,

Vetrò,

, & Iuliano,

(2017). Preserving the benefits of open government data by measuring and improving their quality: An empirical study. Paper presented at the Computer Software and Applications Conference (COMPSAC), 2017 IEEE 41st Annual.

55.

Ubaldi,

(2013). Open government data: Towards empirical analysis of open government data initiatives. OECD Working Papers on Public Governance, (22), 0-1.

56.

Umbrich,

Neumaier,

, & Polleres,

(2015). Quality assessment and evolution of open data portals. Paper presented at the Future Internet of Things and Cloud (FiCloud), 2015 3rd International Conference.

57.

van Veenstra,

A.F.

, & van den Broek,

T.A.

(2013). Opening moves-drivers, enablers and barriers of open data in a semi-public organization. Paper presented at the International Conference on Electronic Government, Berlin, Heidelberg.

58.

Vetrò,

Canova,

Torchiano,

Minotas,

C.O.

Iemma,

, & Morando,

(2016). Open data quality measurement framework: Definition and application to Open Government Data. Government Information Quarterly, 33(2), 325-337.

59.

Vickery,

(2011). Review of recent studies on PSI re-use and related market developments. Paris: Information Economics.

60.

W3C. (2017). Data on the Web Best Practices. Retrieved from https://www.w3.org/TR/dwbp/.

61.

W3C. (2019). Comparing DKAN and CKAN. Retrieved from https://docs.getdkan.com/en/latest/introduction/dkan-ckan.html.

62.

Wahyudi,

Kuk,

, & Janssen,

(2018). A process pattern model for tackling and improving big data quality. Information Systems Frontiers, 20(3), 457-469.

63.

Wand,

, & Wang,

R.Y.

(1996). Anchoring data quality dimensions in ontological foundations. Communications of the ACM, 39(11), 86-95.

64.

Wang,

R.Y.

, & Strong,

D.M.

(1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5-33.

65.

World Wide Web Foundation. (2018). Open data barometer. Retrieved from https://opendatabarometer.org/?_year=2016&indicator=ODB.

66.

Yang,

H.C.

Lin,

C.S.

, & Yu,

P.H.

(2015). Toward automatic assessment of the categorization structure of open data portals. Paper presented at the International Conference on Multidisciplinary Social Networks Research, Berlin, Heidelberg.

67.

Yang,

Cai,

Zhou,

, & Zhou,

(2005). Development and validation of an instrument to measure user perceived service quality of information presenting web portals. Information & Management, 42(4), 575-589.

68.

Zhang,

Indulska,

, & Sadiq,

(2019). Discovering data quality problems. J Business Information Systems Engineering, 61(5), 575-593.

69.

Zuiderwijk,

Janssen,

van de Kaa,

, & Poulis,

(2016). The wicked problem of commercial value creation in open data ecosystems: Policy guidelines for governments. Information Polity, 21(3), 223-236.

70.

Zuiderwijk,

Shinde,

, & Janssen,

(2018a). Investigating the attainment of open government data objectives: Is there a mismatch between objectives and results? International Review of Administrative Sciences.

71.

Zuiderwijk,

Shinde,

, & Janssen,

(2018b). Investigating the attainment of open government data objectives: Is there a mismatch between objectives and results? International Review of Administrative Sciences (forthcoming).