Soliciting datasets and tools from past and current sensor deployments and data gathering efforts
Sensor systems are proliferating in many parts of research such as Internet of Things (IoT) and Cyber-Physical Systems (CPS). This proliferation has led to an explosion of activity in many applications that cover a multitude of areas. As these research progresses, sharing of data has become a frequent bottle neck in showing repeatability and allowing follow up research from the community.
The Data: Acquisition To Analysis (DATA) workshop aims to solicit datasets and tools from past and current sensor deployments and data gathering efforts. The workshop aims to bring together community of application researchers, and algorithm researchers in the sensing systems domain to promote breakthroughs from integration of the communities. The workshop will foster cross-domain understanding by enabling both the understanding of algorithmic needs, and data collection limitations.
The workshop seeks contributions describing original datasets in all topics related to the sensor networks, IoT and CPS. Topics of interests include, but are not limited to, the following:
We invite to submit abstracts in PDF format with ACM templates (submit notes), of at most 2 pages in length including figures, tables, and references, in two-column format, and using a minimum of 10-pt font. Issues on licenses will be resolved by generally following the procedure similar to CRAWDAD (https://crawdad.org/joinup.html) and special treatments, if needed, will be discussed separately with the TPC chairs. If IRB approval has been obtained for the data collection procedure, please include such information in the submission.
The dataset submission instruction can be found HERE.
The camera-ready paper must be submitted by the 14th of September 2018 (GMT). You should use the acmart.cls. Please note that ACM uses 9-pt fonts in all conference proceedings, and the style (both LaTeX and Word) implicitly define the font size to be 9-pt. The maximum number of pages is 2, including the references. Please refer to publication chair's Note (link pdf) as well as the User Guide of the new class. Accepted submissions will be available on the ACM digital library on the first day of the conference.
Jie Gao (Stony Brook University)
Pei Zhang (Carnegie Mellon University)
Shijia Pan (Carnegie Mellon University)
Chien-Chun Ni (Yahoo Research)
Trevor Pering (Google)
Pat Pannuto (UC Berkeley)
Yingying Chen (Rutgers, The State University of New Jersey)
Josiah Hester (Northwestern University)
Mooi Choo Chuah (Lehigh University)
Desheng Zhang (Rutgers, The State University of New Jersey)
Jun Huang (Peking University)
Hassan Habibi Gharakheili (University of New South Wales)
Olaf Landsiedel (Chalmers University of Technology)
Rui Tan (Nanyang Technological University)
Simon Duquennoy (SICS)
Haiming Jin (Shanghai Jiao Tong University)
One-Month Beijing Taxi GPS Trajectory Dataset with Taxi IDs and Vehicle Status. Jing Lian, Lin Zhang (Tsinghua-Berkeley Shenzhen Institute, Tsinghua University), Dataset Link
Seat Vibration for Heart Monitoring in a Moving Automobile. Amelie Bonde, Mostafa Mirshekari, Jonathon Fagert, Shijia Pan, Hae Young Noh, Pei Zhang (Carnegie Mellon University), Dataset Link
Vehicle Sensing Data Acquisition and Analysis. Linna Wu (Beihang University), Lizhuo Zhang (Broadsense (Shenzhen) Information Technology Co.Ltd), Huan Li, Hengtian Ding (Beihang University), Dataset Link
Occupant-Induced Office Floor Vibration Dataset for Activity Level Monitoring. Yue Zhang (Tsinghua University), Shijia Pan, Jonathon Fagert, Mostafa Mirshekari, Hae Young Noh, Pei Zhang (Carnegie Mellon University), Lin Zhang (Tsinghua University), Dataset Link
Room-level Occupant Counts, Airflow and CO2 Data from an Office Building. Krzysztof Arendt, Aslak Johansen, Bo Nørregaard Jørgensen, Mikkel Baun Kjærgaard, Claudio Giovanni Mattera, Fisayo Caleb Sangogboye , Jens Hjort Schwee, Christian T. Veje (University of Southern Denmark), Dataset Link
Set and Forget Sensing with Applets on IFTTT. Noah Klugman, Prabal Dutta (University of California, Berkeley), Dataset Link
Bluetooth Low Energy in the Wild Dataset. Thomas Zachariah, Meghan Clark, Prabal Dutta (University of California, Berkeley), Dataset Link
Indoor Ultra Wideband Ranging Samples from the DecaWave DW1000 Including Frequency and Polarization Diversity. Pat Pannuto (University of California, Berkeley), Benjamin Kempke (University of Michigan), Bradford Campbell (University of Virginia), Prabal Dutta (University of California, Berkeley), Dataset Link
ILOS: A Data Collection Tool and Open Datasets for Fingerprint-based Indoor Localization. Mitchell Cooke, Yongyong Wei, Yujiao Hao, Rong Zheng (McMaster University), Dataset Link
Dataset: Single-Anchor Indoor Localization with Decawave DW1000 and Directional Antennas. Bernhard Großwindhager, Michael Rath, Josef Kulmer, Mustafa Bakr, Carlo Alberto Boano, Klaus Witrisal, Kay Römer (Graz University of Technology), Dataset Link
PiMi: Two-Month Indoor/Outdoor PM2.5 Concentrations along with Behavior Labels through Large-Scale Participatory Sensing. Rui Ma, Lin Zhang (Tsinghua University), Dataset Link
A Testbed and Data Yields for Studying Data Center Energy Efficiency and Reliability. Duc Van Le, Yingbo Liu, Rongrong Wang, Rui Tan (Nanyang Technological University, Singapore), Lek Heng Ngoh (Info-communications Media Development Authority, Singapore), Dataset Link
The Big House Dataset: Desired Applications and Interactions. Meghan Clark (University of California, Berkeley), Mark W. Newman (University of Michigan), Prabal Dutta (University of California, Berkeley), Dataset Link
Structural Vibration Sensing to Evaluate Animal Activity on a Pig Farm. Amelie Bonde, Shijia Pan (Carnegie Mellon University), Orathai Sangpetch, Akkarit Sangpetch (King Monkut's Institute of Technology Ladkrabang), Woranun Woramontri (Betagro Group), Hae Young Noh, Pei Zhang (Carnegie Mellon University), Dataset Link