nach oben

Erschienen in:

2021 | OriginalPaper | Buchkapitel

The Punya Platform: Building Mobile Research Apps with Linked Data and Semantic Features

verfasst von : Evan W. Patton, William Van Woensel, Oshani Seneviratne, Giuseppe Loseto, Floriano Scioscia, Lalana Kagal

Erschienen in: The Semantic Web – ISWC 2021

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Modern smartphones offer advanced sensing, connectivity, and processing capabilities for data acquisition, processing, and generation: but it can be difficult and costly to develop mobile research apps that leverage these features. Nevertheless, in life sciences and other scientific domains, there often exists a need to develop advanced mobile apps that go beyond simple questionnaires: ranging from sensor data collection and processing to self-management tools for chronic patients in healthcare. We present Punya, an open source, web-based platform based on MIT App Inventor that simplifies building Linked Data-enabled, advanced mobile apps that exploit smartphone capabilities. We posit that its integration with Linked Data facilitates the development of complex application and business rules, communication with heterogeneous online services, and interaction with the Internet of Things (IoT) data sources using the smartphone hardware. To that end, Punya includes an embedded semantic rule engine, integration with GraphQL and SPARQL to access remote graph data, and support for IoT devices using Bluetooth Low Energy and Linked Data Platform Constrained Application Protocol (LDP-CoAP). Moreover, Punya supports generating Linked Data descriptions of collected data. The platform includes built-in tutorials to quickly build apps using these different technologies. In this paper, we present a short discussion of the Punya platform, its current adoption that includes over 500 active users as well as the larger app-building MIT App Inventor community of which it is a part, and future development directions that would greatly benefit Semantic Web and Linked Data application developers as well as researchers who leverage Linked Open Data resources for their research.

Resource: http://punya.mit.edu

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel EduCOR: An Educational and Career-Oriented Recommendation Ontology

Nächstes Kapitel BEEO: Semantic Support for Event-Based Data Analytics

https://cordova.apache.org/.

https://reactnative.dev/.

https://web.dev/progressive-web-apps/.

https://developers.google.com/blockly.

http://iot.appinventor.mit.edu/#/bluetoothle/bluetoothleintro.

The authors mention App Inventor, but several Punya LD components were used.

http://punya.appinventor.mit.edu/?repo=RdfNotepad.

http://punya.appinventor.mit.edu/?repo=SleepApnea.

http://punya.appinventor.mit.edu/?repo=LdpCoapTutorial.

https://community.appinventor.mit.edu.

Apache Licensed, see https://github.com/mit-dig/punya.

Adida, B., Birbeck, M., McCarron, S., Herman, I.: RDFa Core 1.1 - Third Edition). W3C Recommendation, World Wide Web Consortium, March 2015. https://www.w3.org/TR/rdfa-core/

Apple Inc.: CareKit. https://developer.apple.com/carekit

Apple Inc.: HealthKit. https://developer.apple.com/health-fitness/

Apple Inc.: ResearchKit. http://researchkit.org/

Arndt, D., Van Woensel, W.: Notation 3 (N3) Community Group (2018). https://www.w3.org/community/n3-dev/

Belleau, F., Nolin, M.A., Tourigny, N., Rigault, P., Morissette, J.: Bio2RDF: towards a mashup to build bioinformatics knowledge systems. J. Biomed. Inform. 41(5), 706–716 (2008)CrossRef

Blackstock, M., Lea, R.: Toward a distributed data flow platform for the web of things (distributed node-red). In: Proceedings of the 5th International Workshop on Web of Things, pp. 34–39 (2014)

Bobed, C., Yus, R., Bobillo, F., Mena, E.: Semantic reasoning on mobile devices: do androids dream of efficient reasoners? Web Semant. Sci. Services Agents World Wide Web 35, 167–183 (2015)CrossRef

Bormann, C., Castellani, A.P., Shelby, Z.: CoAP: an application protocol for billions of tiny internet nodes. IEEE Internet Comput. 16(2), 62–67 (2012)CrossRef

10.

Bottoni, P., Ceriani, M.: Sparql playground: a block programming tool to experiment with sparql. In: VOILA@ ISWC, p. 103 (2015)

11.

Bouton, M.E.: Why behavior change is difficult to sustain. Prev. Med. 68, 29–36 (2014)CrossRef

12.

Brickley, D., Miller, L.: FOAF vocabulary specification 0.91 (2007)

13.

Carroll, J.J., Dickinson, I., Dollin, C., Reynolds, D., Seaborne, A., Wilkinson, K.: Jena: implementing the semantic web recommendations. In: Proceedings of 13th International World Wide Web Conference Papers & Posters, pp. 74–83 (2004)

14.

Cen, L., Patton, E.W.: Block affordances for graphql in mit app inventor. CoolThink@ JC, p. 147 (2019)

15.

Centers for Disease Control and Prevention, U.S. Department of Health and Human Services, National Diabetes Statistics Report, Atlanta (2020)

16.

Dominguez Veiga, J.J., Ward, T.: Data collection requirements for mobile connected health: an end user development approach. In: Proceedings of the 1st International Workshop on Mobile Development, pp. 23–30 (2016)

17.

El-Sappagh, S., Kwak, D., Ali, F., Kwak, K.S.: DMTO: a realistic ontology for standard diabetes mellitus treatment. J. Biomed. Semant. 9(1), 1–30 (2018)CrossRef

18.

Facebook Inc.: GraphQL: a data query language. https://engineering.fb.com/2015/09/14/core-data/graphql-a-data-query-language

19.

Hartig, O., Pérez, J.: Semantics and complexity of GraphQL. In: Proceedings of the 2018 World Wide Web Conference, pp. 1155–1164 (2018)

20.

Hasan, K., Biswas, K., Ahmed, K., Nafi, N.S., Islam, M.S.: A comprehensive review of wireless body area network. J. Netw. Comput. Appl. 143, 178–198 (2019)CrossRef

21.

Haussmann, S., et al.: FoodKG: a semantics-driven knowledge graph for food recommendation. In: Ghidini, C., et al. (eds.) ISWC 2019. LNCS, vol. 11779, pp. 146–162. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-30796-7_10CrossRef

22.

Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M., et al.: SWRL: a semantic web rule language combining OWL and RuleML. W3C Member Submission 21(79), 1–31 (2004)

23.

InVision Inc.: InVision. https://www.invisionapp.com

24.

Kazakov, Y., Klinov, P.: Experimenting with ELK reasoner on android. In: Proceedings of 2nd International Workshop on OWL Reasoner Evaluation, pp. 68–74 (2013)

25.

Kim, H., Mentzer, J., Taira, R.: Developing a physical activity ontology to support the interoperability of physical activity data. J. Med. Internet Res. 21(4), e12776 (2019)

26.

Kinkead, L., Pinheiro, P., McGuinness, D.L.: Automating the collection of semantic sensor network metadata in the field with mobile applications. In: Proceedings of 1st International Workshop on Mobile Deployment of Semantic Technologies, pp. 32–43 (2015)

27.

Laratta, C.R., Ayas, N.T., Povitz, M., Pendharkar, S.R.: Diagnosis and treatment of obstructive sleep apnea in adults. CMAJ 189(48), E1481–E1488 (2017)CrossRef

28.

Li, W., Seneviratne, O., Patton, E.W., Kagal, L.: A semantic platform for developing data-intensive mobile apps. In: Proceedings of 13th International Conference on Semantic Computing (ICSC), pp. 71–78. IEEE (2019)

29.

Li, W.J.: Helping the helpers: a toolkit for mobile humanitarian assistance apps. Master’s thesis, Massachusetts Institute of Technology (2016)

30.

Loseto, G., Ieva, S., Gramegna, F., Ruta, M., Scioscia, F., Di Sciascio, E.: Linked data (in low-resource) platforms: a mapping for constrained application protocol. In: Groth, P., et al. (eds.) ISWC 2016. LNCS, vol. 9982, pp. 131–139. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46547-0_14CrossRef

31.

Marvel Inc.: Marvel. https://marvelapp.com

32.

Mayo Clinic: Polysomnography (sleep study). https://www.mayoclinic.org/tests-procedures/polysomnography/about/pac-20394877

33.

McGuinness, D.L., Van Harmelen, F., et al.: OWL web ontology language overview. W3C Recommendation 10(2) (2004)

34.

Miralles, I., et al.: Smartphone apps for the treatment of mental disorders: systematic review. JMIR Mhealth Uhealth 8(4), e14897 (2020)

35.

MockPlus Inc.: MockPlus. https://www.mockplus.com

36.

Nilsson, M.Y., Andersson, S., Magnusson, L., Hanson, E.: Ambient assisted living technology-mediated interventions for older people and their informal carers in the context of healthy ageing: a scoping review. Health Sci. Rep. 4(1), e225 (2021)

37.

Node-RED community: Node-RED: Low-code programming for event-driven applications. https://nodered.org

38.

Patton, E.W.: Energy aware reasoning agents for the mobile semantic web. Ph.D. thesis, RPI (2016)

39.

Patton, E.W.: A look at component usage in MIT App Inventor (2020). http://appinventor.mit.edu/blogs/evan/2020/12/20/component-usage-mit-app-inventor. Accessed 01 Apr 2021

40.

Patton, E.W., McGuinness, D.L.: A power consumption benchmark for reasoners on mobile devices. In: Mika, P., et al. (eds.) ISWC 2014. LNCS, vol. 8796, pp. 409–424. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11964-9_26CrossRef

41.

Patton, E.W., Scioscia, F., Van Woensel, W.: Building mobile semantic web apps with Punya. In: Proceedings of ISWC 2020 Tutorials (2020)

42.

Pérez, J., Arenas, M., Gutierrez, C.: Semantics and complexity of SPARQL. ACM Trans. Database Syst. (TODS) 34(3), 1–45 (2009)CrossRef

43.

Praino, E., et al.: SScEntry: a personal disease diary app for Systemic Sclerosis patients. Ann. Rheum. Dis. 79, 558–559 (2020). eULAR 2020 European eCongress of Rheumatology

44.

Proto.io Inc.: Proto.io: Prototyping for all. https://proto.io

45.

Qualtrics Inc.: Qualtrics: XM OS - Experience Design and Improvement. https://www.qualtrics.com

46.

Ruta, M., Scioscia, F., Di Sciascio, E.: Enabling the semantic web of things: framework and architecture. In: 2012 IEEE Sixth International Conference on Semantic Computing, pp. 345–347. IEEE (2012)

47.

Sambra, A., et al.: Solid: a platform for decentralized social applications based on linked data. Technical report, MIT CSAIL & Qatar Computing Research Institute (2016)

48.

Shelby, Z.: Constrained RESTful Environments (CoRE) Link Format. RFC 6690, Internet Engineering Task Force, August 2012

49.

Shiffman, S., Stone, A.A., Hufford, M.R.: Ecological momentary assessment. Annu. Rev. Clin. Psychol. 4, 1–32 (2008)CrossRef

50.

Shih, F.: Exploring mobile privacy in context. Ph.D. thesis, MIT (2015)

51.

Sittón-Candanedo, I., Alonso, R.S., Corchado, J.M., Rodríguez-González, S., Casado-Vara, R.: A review of edge computing reference architectures and a new global edge proposal. Futur. Gener. Comput. Syst. 99, 278–294 (2019)CrossRef

52.

Steve Speicher and John Arwe and Ashok Malhotra: Linked Data Platform 1.0. https://www.w3.org/TR/ldp

53.

United Nations Department of Economic and Social Affairs: World Population Prospects 2019. https://population.un.org/wpp/

54.

Van Woensel, W., Abidi, S.: Benchmarking semantic reasoning on mobile platforms: towards optimization using OWL2 RL. Semantic Web 10(4), 637–663 (2019)CrossRef

55.

Van Woensel, W., Roy, P., Abidi, S., Abidi, S.: A mobile and intelligent patient diary for chronic disease self-management. In: Studies in Health Technology and Informatics, vol. 216 (2015)

56.

Wilkinson, M., Vandervalk, B., McCarthy, L.: The semantic automated discovery and integration (SADI) web service design-pattern, API and reference implementation. Nat. Preced. 1 (2011)

57.

Wolber, D., Abelson, H., Friedman, M.: Democratizing computing with app inventor. GetMobile: Mob. Comput. Commun. 18(4), 53–58 (2015)

58.

Yus, R., Bobed, C., Esteban, G., Bobillo, F., Mena, E.: Android goes semantic: DL reasoners on smartphones. In: Proceedings of 2nd International Workshop on OWL Reasoner Evaluation, pp. 46–52 (2013)

Titel: The Punya Platform: Building Mobile Research Apps with Linked Data and Semantic Features
verfasst von: Evan W. Patton
William Van Woensel
Oshani Seneviratne
Giuseppe Loseto
Floriano Scioscia
Lalana Kagal
Verlag: Springer International Publishing
Buch: The Semantic Web – ISWC 2021
Print ISBN: 978-3-030-88360-7

Electronic ISBN: 978-3-030-88361-4

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-88361-4_33

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner