USE AND OPTIMISATION OF PAID CROWDSOURCING FOR THE COLLECTION OF GEODATA

被引:0
|
作者
Walter, V. [1 ]
Laupheimer, D. [1 ]
Fritsch, D. [1 ]
机构
[1] Univ Stuttgart, Inst Photogrammetry, D-70174 Stuttgart, Germany
来源
XXIII ISPRS CONGRESS, COMMISSION IV | 2016年 / 41卷 / B4期
关键词
Crowdsourcing; Data Collection; Geodata;
D O I
10.5194/isprsarchives-XLI-B4-253-2016
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Crowdsourcing is a new technology and a new business model that will change the way in which we work in many fields in the future. Employers divide and source out their work to a huge number of anonymous workers on the Internet. The division and outsourcing is not a trivial process but requires the definition of complete new workflows - from the definition of subtasks, to the execution and quality control. A popular crowdsourcing project in the field of collection of geodata is OpenStreetMap, which is based on the work of unpaid volunteers. Crowdsourcing projects that are based on the work of unpaid volunteers need an active community, whose members are convinced about the importance of the project and who have fun to collaborate. This can only be realized for some tasks. In the field of geodata collection many other tasks exist, which can in principle be solved with crowdsourcing, but where it is difficult to find a sufficient large number of volunteers. Other incentives must be provided in these cases, which can be monetary payments.
引用
收藏
页码:253 / 257
页数:5
相关论文
共 50 条
  • [41] Key Research Issues and Related Technologies in Crowdsourcing Data Collection
    Li, Yunhui
    Chang, Liang
    Li, Long
    Bao, Xuguang
    Gu, Tianlong
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2021, 2021
  • [42] CROWDSOURCING AND VGI IN NATIONAL MAPPING AGENCY'S DATA COLLECTION
    Bol, Daphne
    Grus, Magdalena
    Laakso, Mari
    6TH INTERNATIONAL CONFERENCE ON CARTOGRAPHY AND GIS, VOLS 1 AND 2, 2016, : 493 - 498
  • [43] Crowdsourcing research: Data collection with Amazon's Mechanical Turk
    Sheehan, Kim Bartel
    COMMUNICATION MONOGRAPHS, 2018, 85 (01) : 140 - 156
  • [44] Crowdsourcing as a Method for the Collection of Revealed Preference Data Short Paper
    Assemi, Behrang
    Schlagwein, Daniel
    Safi, Hamid
    Mesbah, Mahmoud
    9TH IEEE INTERNATIONAL SYMPOSIUM ON SERVICE-ORIENTED SYSTEM ENGINEERING (SOSE 2015), 2015, : 378 - 382
  • [45] Internet crowdsourcing as a venue for collection of dermatologic quality of life data
    Ostrowski, A.
    Chen, S.
    Veledar, E.
    Sperduto, A.
    Swerlick, R.
    JOURNAL OF INVESTIGATIVE DERMATOLOGY, 2012, 132 : S45 - S45
  • [46] Measures for Improving Outdoor Crowdsourcing Photo Collection on Smart Phones
    Chen, Huihui
    Guo, Bin
    Yu, Zhiwen
    2019 IEEE SMARTWORLD, UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTING, SCALABLE COMPUTING & COMMUNICATIONS, CLOUD & BIG DATA COMPUTING, INTERNET OF PEOPLE AND SMART CITY INNOVATION (SMARTWORLD/SCALCOM/UIC/ATC/CBDCOM/IOP/SCI 2019), 2019, : 907 - 915
  • [47] Community-Driven Crowdsourcing: Data Collection with Local Developers
    Funk, Christina
    Tseng, Michael
    Rajakumar, Ravindran
    Ha, Linne
    PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2018), 2018, : 1606 - 1609
  • [48] Weigh it and Share it! Crowdsourcing for Pro-Environmental Data Collection
    Schiavo, Gianluca
    Leonardi, Chiara
    Pasolli, Mattia
    Sarti, Silvia
    Zancanaro, Massimo
    PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON HUMAN-COMPUTER INTERACTION WITH MOBILE DEVICES AND SERVICES (MOBILEHCI '17), 2017,
  • [49] Designing a Crowdsourcing System for the Elderly: A Gamified Approach to Speech Collection
    Seong, Eunjin
    Kim, Seungjun
    CHI'20: EXTENDED ABSTRACTS OF THE 2020 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 2020,
  • [50] Collection line optimisation in wind farms using improved ant colony optimisation
    Wu, Yi-wen
    Wang, Yong
    WIND ENGINEERING, 2021, 45 (03) : 589 - 600